diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..68bc17f9ff2104a9d7b6777058bb4c343ca72609 --- /dev/null +++ b/.gitignore @@ -0,0 +1,160 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# poetry +# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control +#poetry.lock + +# pdm +# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. +#pdm.lock +# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it +# in version control. +# https://pdm.fming.dev/#use-with-ide +.pdm.toml + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +# PyCharm +# JetBrains specific template is maintained in a separate JetBrains.gitignore that can +# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore +# and can be added to the global gitignore or merged into this file. For a more nuclear +# option (not recommended) you can uncomment the following to ignore the entire idea folder. +#.idea/ diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000000000000000000000000000000000000..1b9bdcc88fbcac22293bd3d4554785e58555c5cb --- /dev/null +++ b/Dockerfile @@ -0,0 +1,14 @@ +# read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker +# you will also find guides on how best to write your Dockerfile + +FROM python:3.9 + +WORKDIR /code + +COPY ./requirements.txt /code/requirements.txt + +RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt + +COPY . . + +CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"] diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..6ac2d0c3f5b438a18b879745deb8dbd2bb8193be --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2023 binaychandra + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/app.py b/app.py new file mode 100644 index 0000000000000000000000000000000000000000..47030049e17f86032a34b15eb7b70eb359c2298c --- /dev/null +++ b/app.py @@ -0,0 +1,242 @@ +# Standard Library Imports +from flask import ( Flask, jsonify, render_template, request, + url_for, + make_response, + session, + send_file, + Response, + render_template_string, + redirect) +import pandas as pd +import plotly.graph_objects as go +from sqlalchemy import create_engine +from config import tbl_mapping +from data_connector.sqlite_connector import get_db_connection +from lang_assistant.langhelper import chat_response, summary_extractor_from_df, chat_with_df, generate_graphdata +from utilities.plotting import (get_validation_json, + badges_get_pillar_dougnutdata, + badges_get_badgecompletion_monthwise, + get_wfrankwise_countmom, + get_lst_topdepartment, + get_wfrankwise_count, + get_topfive_badgetitle) +import sqlite3 +import time +import json + +app = Flask(__name__, static_url_path='/static') +app.secret_key = 'test' + +@app.route("/validate_learning", methods=['GET']) +def load_learning(): + # con = sqlite3.connect("database.db") + # df = pd.read_sql_query(f"SELECT * from learning", con) + df = pd.DataFrame({'ID':[12,13], 'Status':['Done', 'In Progress']}) + no_rows, no_cols = df.shape + n_gui = df.GUI.nunique() if 'GUI' in df.columns else 'GUI not Found' + + tablevalues = {'n_rows':no_rows, 'n_cols':no_cols, 'unique_gui':n_gui} + print('Calculation done') + # Data for the bar chart + bar_chart_data = { + 'labels': ['Label 1', 'Label 2', 'Label 3', 'Label 4', 'Label 5'], + 'values': [30, 40, 30, 21, 34] + } + # Data for the pie chart + pie_chart_data = { + 'labels': ['Label A', 'Label B', 'Label C', 'Label D', 'Label E'], + 'values': [45, 30, 25, 9, 34] + } + + # Create the bar chart figure + bar_chart_figure = go.Figure( + data=[ + go.Bar( + x=bar_chart_data['labels'], + y=bar_chart_data['values'], + marker_color='rgba(54, 162, 235, 0.5)', + marker_line_color='rgba(54, 162, 235, 1)', + marker_line_width=1 + ) + ], + layout=go.Layout( + title='Bar Chart', + yaxis=dict(title='Values'), + margin=dict(l=20, r=20, t=40, b=20) + ) + ) + + # Create the pie chart figure + pie_chart_figure = go.Figure( + data=[ + go.Pie( + labels=pie_chart_data['labels'], + values=pie_chart_data['values'], + hole=0.3, + marker=dict(colors=['rgba(255, 99, 132, 0.5)', 'rgba(54, 162, 235, 0.5)', 'rgba(255, 206, 86, 0.5)'], + line=dict(color='rgba(0, 0, 0, 0.5)', width=1)) + ) + ], + layout=go.Layout( + title='Pie Chart', + margin=dict(l=20, r=20, t=40, b=20) + ) + ) + # Convert the figures to HTML + bar_chart_html = bar_chart_figure.to_html(full_html=False) + pie_chart_html = pie_chart_figure.to_html(full_html=False) + + data = { + 'Regex issue': [-90, -10, -5, 0], + 'Null percentage': [-10, -35, 0, 0], + 'Seems ok': [40, 45, 90, 100], + 'data mismatch': [0, -10, -5, 0] + } + + df = pd.DataFrame(data, index=['GTE', 'SMU', 'Service_Line', 'Sub_SL']) + + labels = df.index.to_list() + reg_issue = df['Regex issue'].to_list() + null_issue = df['Null percentage'].to_list() + ok_data = df['Seems ok'].to_list() + mismatch_issue = df['data mismatch'].to_list() + tbl_selected = session.get('tbl_selected', []) + + return render_template("validate_learning.html", + req_tables = tbl_selected, + bar_chart_html=bar_chart_html, + pie_chart_html=pie_chart_html, + table_info = tablevalues, + labels = labels, reg_issue=reg_issue, + null_issue=null_issue, ok_data=ok_data , mismatch_issue=mismatch_issue, + show_sidebar=True) + +@app.route("/validate_badges", methods=['GET', 'POST']) +def load_badges(): + con = sqlite3.connect("database.db") + df = pd.read_sql_query(f"SELECT * from badges", con) + no_rows, no_cols = df.shape + n_gui = df.GUI.nunique() if 'GUI' in df.columns else 'GUI not Found' + + tablevalues = {'n_rows':no_rows, 'n_cols':no_cols, 'unique_gui':n_gui} + print('Calculation done') + + tbl_selected = session.get('tbl_selected', []) + + json_data = get_validation_json('badges') + json_pillar_data = badges_get_pillar_dougnutdata() + json_badgecompletion_data = badges_get_badgecompletion_monthwise() + lst_topfive_badgetitle = get_topfive_badgetitle() + + return render_template("validate_badges.html", + lst_topfive_badgetitle = lst_topfive_badgetitle, + req_tables = tbl_selected, + table_info = tablevalues, + json_data = json_data, + json_pillar_data=json_pillar_data, + json_badgecompletion_data = json_badgecompletion_data, + show_sidebar=True) + +@app.route("/validation", methods=['GET', 'POST']) +@app.route("/validate_workforce", methods=['GET', 'POST']) +def load_workforce(): + # con = sqlite3.connect("database.db") + # df = pd.read_sql_query(f"SELECT * from workforce", con) + df = pd.read_csv(r"referencefiles\workforce.csv") + no_rows, no_cols = df.shape + n_gui = df.GUI.nunique() if 'GUI' in df.columns else 'GUI not Found' + + tablevalues = {'n_rows':no_rows, 'n_cols':no_cols, 'unique_gui':n_gui} + + json_val_data = get_validation_json('workforce') + json_empdist = get_wfrankwise_countmom() + lst_topfive_dept = get_lst_topdepartment() + json_rankwise_empdist = get_wfrankwise_count() + tbl_selected = session.get('tbl_selected', []) #['Badges', 'learning'] + gpt_response = summary_extractor_from_df("""{"male": 56, "female": 44 }""") + + return render_template("validate_workforce.html", + req_tables = tbl_selected, + table_info = tablevalues, + json_data = json_val_data, + json_empdist = json_empdist, + lst_topfive_dept = lst_topfive_dept, + json_rankwise_empdist = json_rankwise_empdist, + aicontent_genderanalysis = gpt_response, + show_sidebar = True) + +@app.route("/validate_miscellaneous", methods=['GET', 'POST']) +def load_miscellaneous(): + tbl_selected = session.get('tbl_selected', []) + return render_template("validate_miscellaneous.html", + req_tables = tbl_selected, + show_sidebar = True) + +@app.route("/timecard.html", methods=['GET', 'POST']) +def load_timecard(): + return render_template("timecard.html") + +@app.route("/get_llmresponse") +def get_bot_response(): + user_message = request.args.get('msg') + dd_table_selected = request.args.get('table_selected') + print(f"user message and table selected : {user_message}, {dd_table_selected}") + print(f"request args : {request.args.get('msg')}") + response_usrmsg = chat_with_df(user_message, table_name = dd_table_selected) + return response_usrmsg + +@app.route("/get_val_llmresponse") +def get_bot_valresponse(): + user_message = request.args.get('msg') + table_selected = request.args.get('table_selected') + print(f"user message and table selected : {user_message}, {table_selected}") + print(f"request args : {request.args.get('msg')}") + + try: + llm_response_dict = generate_graphdata(user_message, table_name = table_selected) + except Exception as e: + llm_response_dict = dict(success=False, + chart_type='text', + chart_label=None, + chart_json_data=None, + text_to_display="Exception : Some error occured while processing, "+str(e)[:50] + "..") + + print(llm_response_dict) + output_gendata = json.dumps(llm_response_dict) + return output_gendata + +@app.route("/data.html", methods=['GET', 'POST']) +@app.route("/data", methods=['GET', 'POST']) +def data(): + tbl_htmls = {} + tbl_selected = session.get('tbl_selected', []) + print(tbl_selected) + for tblname in tbl_selected: + # Read sqlite query results into a pandas DataFrame + # con = sqlite3.connect("database.db") + # df = pd.read_sql_query(f"SELECT * from {tblname}", con) + df = pd.read_csv(f"referencefiles\{tblname}.csv") + top_records = df.copy() + # con.close() + html_top_records = top_records.to_html(index=False, table_id= f'dtable_{tblname}', classes='display nowrap table table-bordered table-striped table-condensed small p-1', justify='left') + html_top_records = html_top_records.replace('', '') + tbl_htmls[tblname] = html_top_records + + return render_template('data.html', table_htmls = tbl_htmls, req_tables = json.dumps(tbl_selected[0])) + +@app.route("/", methods=['GET', 'POST']) +@app.route("/home", methods=['GET', 'POST']) +def hometest(): + if request.method == 'GET': + return render_template('home.html') + elif request.method == 'POST': + session['start_date'] = request.form.get('calendar_value').split(":")[0] + session['end_date'] = request.form.get('calendar_value').split(":")[1] + session['sl_subsl'] = request.form.get('sl_subsl') + session['tbl_selected'] = request.form.getlist('tbl_selected') + return redirect(url_for('data')) + +if __name__ == '__main__': + #app.run(debug=True) + from waitress import serve + serve(app, host="0.0.0.0", port=8080) diff --git a/config.py b/config.py new file mode 100644 index 0000000000000000000000000000000000000000..1517ff7b5f2818f14cf62a7d7a5a0e9834483d7a --- /dev/null +++ b/config.py @@ -0,0 +1,9 @@ +tbl_mapping = { + 'workforce' : '[dbo].[workforce]', + 'badges' : '[dbo].[badges]', + 'learning' : '[dbo].[learning]', + 'lat' : '[dbo].[lat]', + 'mct' : '[dbo].[mct]', + 'profqual' : '[dbo].[profqual]', + 'workexperience' : '[dbo].[workexperience]' +} \ No newline at end of file diff --git a/data_connector/fakedata_generator.py b/data_connector/fakedata_generator.py new file mode 100644 index 0000000000000000000000000000000000000000..b7c6a9f125750440ba1f19d2e199599827b8c184 --- /dev/null +++ b/data_connector/fakedata_generator.py @@ -0,0 +1,14 @@ +import pandas as pd +#from faker import Faker +from datetime import date, timedelta +import random + +def generate_fakedata_badges(num_rows = 1000): + pass + +def generate_fakedata_workforce(num_rows = 1000): + # Initialize the Faker object + pass + +def upload_to_sqlitedb(): + pass \ No newline at end of file diff --git a/data_connector/sqlite_connector.py b/data_connector/sqlite_connector.py new file mode 100644 index 0000000000000000000000000000000000000000..d69696ffa254c42a149472936d05027a8b4d4543 --- /dev/null +++ b/data_connector/sqlite_connector.py @@ -0,0 +1,15 @@ +import sqlite3 + +def get_db_connection(): + conn = sqlite3.connect('database.db') + conn.row_factory = sqlite3.Row + return conn + +def push_to_sqlitedb(df, db_tblname): + # Get the database connection object + conn = get_db_connection() + try: + df.to_sql(db_tblname, conn, index=False, if_exists = 'replace') + except: + raise Exception("Insertion Error : DB Insertion failed..") + return None diff --git a/lang_assistant/langhelper.py b/lang_assistant/langhelper.py new file mode 100644 index 0000000000000000000000000000000000000000..0603c26a3615c8b74f84021a04a47faf054ec739 --- /dev/null +++ b/lang_assistant/langhelper.py @@ -0,0 +1,301 @@ +import langchain +from langchain.chat_models import ChatOpenAI +from langchain.prompts import ChatPromptTemplate +import openai +from langchain.memory import ConversationBufferMemory +import pandas as pd +from langchain import memory +import sqlite3 +import os +import json +from langchain.agents import create_pandas_dataframe_agent +from langchain.agents.agent_types import AgentType +import io +import logging +import requests +import urllib3 +from langchain.prompts import ChatPromptTemplate +from langchain.output_parsers import ResponseSchema +from langchain.output_parsers import StructuredOutputParser +from langchain.callbacks import LLMonitorCallbackHandler +from langchain.chat_models import ChatOpenAI +from langchain.prompts.chat import SystemMessage, HumanMessagePromptTemplate, HumanMessage, AIMessage +from langchain.agents import create_pandas_dataframe_agent + +model_id = 'gpt-3.5-turbo' + +from dotenv import load_dotenv, find_dotenv +_ = load_dotenv(find_dotenv()) # read local .env file + +def summary_extractor_from_df(df:pd.DataFrame)-> str: + chatmodel = ChatOpenAI() + template = "You are an AI assistant and your task is to summarize the workforce distribution based on gender delimited by triple backticks \ + and output should clearly indicate how much percentage one gender is higher than other one, and based on the findings make some comments on includsiveness \ + if this is good for company or not.. limit the output in 50 words```{json_genderdf}```" + prompt_template = ChatPromptTemplate.from_template(template) + + user_message = prompt_template.format_messages(json_genderdf = df) + response = chatmodel(user_message) + # print(response.content) + return response.content + +def chat_response(text:str)->str: + chatmodel = ChatOpenAI(max_tokens=50) + response = chatmodel.predict(text) + return response + +def chat_with_df(query, table_name = None): + if table_name is None: + df = pd.read_csv(r"https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv") + else: + #get data + con = sqlite3.connect("database.db") + df = pd.read_sql_query(f"SELECT * from {table_name}", con) + + agent = create_pandas_dataframe_agent( + ChatOpenAI(temperature=0, model="gpt-3.5-turbo-0613"), + df, + agent_type=AgentType.OPENAI_FUNCTIONS, + verbose=True + ) + try: + res_query = agent.run(query) + except Exception as e: + print(str(e)) + res_query = "ERROR" + + return res_query + +def gen_chartdata(df_out, label, chart_type): + + print("Inside gen_chartdata.....") + print(f"df_out --> {df_out}") + data_dict = { + "labels": None, + "datasets": [ + { + "label": "Default Label", + "data": None, + "type" : chart_type, + "backgroundColor": ["rgba(250, 240, 230, 0.7)"], + "hoverBackgroundColor": ["rgba(250, 240, 230, 1)"], + "borderColor": ["rgba(250, 240, 230, 1)"] + } + ] + } + print(f"df_out.iloc[:,0].to_list() ---> {df_out.iloc[:,0].to_list()}") + print(f"data_dict[\"datasets\"][0][\"label\"] --> {data_dict['datasets'][0]['label']}") + print(f"label : {label}") + print(f"data_dict['datasets'][0]['data'] --> {data_dict['datasets'][0]['data']}") + print(f"df_out.iloc[:,1].to_list() --> {df_out.iloc[:,1].to_list()}") + + data_dict["labels"] = df_out.iloc[:,0].to_list() + data_dict["datasets"][0]["label"] = label + data_dict["datasets"][0]["data"] = df_out.iloc[:,1].to_list() + if chart_type == 'doughnut': + data_dict["datasets"][0]["backgroundColor"] = ["rgba(120, 214, 198, 0.7)", "rgba(255, 105, 105, 0.7)", "rgba(150, 194, 145, 0.7)", "rgba(250, 240, 230, 0.7)"] + data_dict["datasets"][0]["hoverBackgroundColor"] = ["rgba(120, 214, 198, 1)", "rgba(255, 105, 105, 1)", "rgba(150, 194, 145, 1)", "rgba(250, 240, 230, 1)"] + data_dict["datasets"][0]["borderColor"] = ["rgba(120, 214, 198, 1)", "rgba(255, 105, 105, 1)", "rgba(150, 194, 145, 1)", "rgba(250, 240, 230, 1)"] + + # Serializing json + json_object = json.dumps(data_dict, indent = 4) + + return json_object + +def generate_graphdata(query, table_name = None): + if table_name is None: + df = pd.read_csv(r"https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv") + else: + #get data from sqlite db + con = sqlite3.connect("database.db") + df = pd.read_sql_query(f"SELECT * from {table_name}", con) + + jsondf = df.head(5).to_json(orient='records') + + prompt_template = ChatPromptTemplate.from_messages( + [ + SystemMessage( + content=( + "You are a data manager and you have to assign the task to a pandas coder \ + who will be working on the steps provided by you. Assuming the pandas coder has already loaded \ + the dataset in pandas dataframe, your task is to properly provide the steps with \ + proper column names so that pandas coder can easily understand the ask and code till the processing of dataset\ + which can be used for graph creation. include steps only to process the data \ + THE STEPS SHOULD NOT CONTAIN ANY GRAPH CREATION OR PLOTTING INSTRUCTIONS.. \ + always select columns only that are mentioned \ + not any extra columns. also think through if output contains two columns if not then create the steps to \ + only include two appropriate columns in output. Also do not include any steps to select top few records.. \ + the output should be all records from the steps execution.") + ), + HumanMessage(content=("\ + user_input = ```plot the distribution of males and females who survived```\ + use below dataset for reference delimited by <<<>>>\ + <<<[{\"PassengerId\":1,\"Survived\":0,\"Pclass\":3,\"Name\":\"Braund, Mr. Owen Harris\",\"Sex\":\"male\",\"Age\":22.0,\"SibSp\":1,\"Parch\":0,\"Ticket\":\"A\/5 21171\",\"Fare\":7.25,\"Cabin\":null,\"Embarked\":\"S\"},{\"PassengerId\":2,\"Survived\":1,\"Pclass\":1,\"Name\":\"Cumings, Mrs. John Bradley (Florence Briggs Thayer)\",\"Sex\":\"female\",\"Age\":38.0,\"SibSp\":1,\"Parch\":0,\"Ticket\":\"PC 17599\",\"Fare\":71.2833,\"Cabin\":\"C85\",\"Embarked\":\"C\"},{\"PassengerId\":3,\"Survived\":1,\"Pclass\":3,\"Name\":\"Heikkinen, Miss. Laina\",\"Sex\":\"female\",\"Age\":26.0,\"SibSp\":0,\"Parch\":0,\"Ticket\":\"STON\/O2. 3101282\",\"Fare\":7.925,\"Cabin\":null,\"Embarked\":\"S\"},{\"PassengerId\":4,\"Survived\":1,\"Pclass\":1,\"Name\":\"Futrelle, Mrs. Jacques Heath (Lily May Peel)\",\"Sex\":\"female\",\"Age\":35.0,\"SibSp\":1,\"Parch\":0,\"Ticket\":\"113803\",\"Fare\":53.1,\"Cabin\":\"C123\",\"Embarked\":\"S\"},{\"PassengerId\":5,\"Survived\":0,\"Pclass\":3,\"Name\":\"Allen, Mr. William Henry\",\"Sex\":\"male\",\"Age\":35.0,\"SibSp\":0,\"Parch\":0,\"Ticket\":\"373450\",\"Fare\":8.05,\"Cabin\":null,\"Embarked\":\"S\"}]>>>\ + {format_instructions}\ + from these inputs extract the following information\ + steps: the steps to be performed for the execution of task\ + label: suggest label to be displayed on the graph for the required ask in less than 3 words\ + chart_type: extract what type of chart user want to see.. if not specified then suggest which one \ + would be suitable for the task.. should be one of these ['bar', 'line', 'doughnut', 'scatter', 'text']\ + output text if graph cant be plotted or user required the answer in text format")), + AIMessage(content=("{\n\t\"steps\": \"1. Filter the dataframe to include only the rows where \'Survived\' column is equal to 1.\\n\ + 2. Group the filtered dataframe by \'Sex\' column.\\n\ + 3. Count the number of occurrences of each unique value in the \'Sex\' column.\\n\ + 4. Create a new dataframe with two columns: \'Sex\' and \'Count\', where \'Sex\' contains the unique values from the \'Sex\' column and \'Count\' contains the corresponding counts.\\n\ + 5. Select top two records from the dataframe.\",\\n\ + 6. Convert the dataset to Json and create the bar graph.\"t\ + \"label\": \"Distribution of Males and Females who Survived\",\\n\t\ + \"chart_type\": \"bar\"\\n}")), + HumanMessage(content=("The output seems not correct. the provided steps include importing matplotlib and creating the bar diagram\ + which was clearly mentioned not to include. Also steps include selecting top two records where it was mentioned \ + not to select top few records for output. you should output all records unless asked otherwise. Also steps include \ + the conversion to json which should not have been included. the output should be only pandas dataframe..\ + can you correct these and provide the response.")), + AIMessage(content=("{\n\t\"steps\": 1. Filter the dataframe to include only the rows where \'Survived\' column is equal to 1.\\n\ + 2. Group the filtered dataframe by \'Sex\' column.\\n\ + 3. Count the number of occurrences of each unique value in the \'Sex\' column.\\n\ + 4. Create a new dataframe with two columns: \'Sex\' and \'Count\', where \'Sex\' contains the unique values from the \'Sex\' column and \'Count\' contains the corresponding counts.\\n\ + 5. Return the new dataframe.\",\\n\t\ + \"label\": \"Distribution of Males and Females who Survived\",\\n\t\ + \"chart_type\": \"bar\"\\n}")), + HumanMessage(content=("Now the output looks perfect. This was just the way I wanted. Thanks a lot..")), + AIMessage(content=("Thanks for the feedback, I will double check these things next time..")), + HumanMessage(content=("\ + user_input = ```draw the bar chart for distribution of pclass and for only sex=males```\ + use below dataset for reference delimited by <<<>>>\ + <<<[{\"PassengerId\":1,\"Survived\":0,\"Pclass\":3,\"Name\":\"Braund, Mr. Owen Harris\",\"Sex\":\"male\",\"Age\":22.0,\"SibSp\":1,\"Parch\":0,\"Ticket\":\"A\/5 21171\",\"Fare\":7.25,\"Cabin\":null,\"Embarked\":\"S\"},{\"PassengerId\":2,\"Survived\":1,\"Pclass\":1,\"Name\":\"Cumings, Mrs. John Bradley (Florence Briggs Thayer)\",\"Sex\":\"female\",\"Age\":38.0,\"SibSp\":1,\"Parch\":0,\"Ticket\":\"PC 17599\",\"Fare\":71.2833,\"Cabin\":\"C85\",\"Embarked\":\"C\"},{\"PassengerId\":3,\"Survived\":1,\"Pclass\":3,\"Name\":\"Heikkinen, Miss. Laina\",\"Sex\":\"female\",\"Age\":26.0,\"SibSp\":0,\"Parch\":0,\"Ticket\":\"STON\/O2. 3101282\",\"Fare\":7.925,\"Cabin\":null,\"Embarked\":\"S\"},{\"PassengerId\":4,\"Survived\":1,\"Pclass\":1,\"Name\":\"Futrelle, Mrs. Jacques Heath (Lily May Peel)\",\"Sex\":\"female\",\"Age\":35.0,\"SibSp\":1,\"Parch\":0,\"Ticket\":\"113803\",\"Fare\":53.1,\"Cabin\":\"C123\",\"Embarked\":\"S\"},{\"PassengerId\":5,\"Survived\":0,\"Pclass\":3,\"Name\":\"Allen, Mr. William Henry\",\"Sex\":\"male\",\"Age\":35.0,\"SibSp\":0,\"Parch\":0,\"Ticket\":\"373450\",\"Fare\":8.05,\"Cabin\":null,\"Embarked\":\"S\"}]>>>\ + {format_instructions}\ + from these inputs extract the following information\ + steps: the steps to be performed for the execution of task\ + label: suggest label to be displayed on the graph for the required ask in less than 3 words\ + chart_type: extract what type of chart user want to see.. if not specified then suggest which one \ + would be suitable for the task.. should be one of these ['bar', 'line', 'doughnut', 'scatter', 'text']\ + output text if graph cant be plotted or user required the answer in text format")), + AIMessage(content=("{\"\n\t\"steps\": \"1. Filter the dataframe to include only rows where Sex is \'male\'\\n\ + 2. Group the data by Pclass and count the number of occurrences\\n\ + 3. Create a new dataframe with the Pclass and count columns\\n\ + 4. Sort the dataframe by Pclass\\n\ + 5. Output the resulting dataframe\",\n\t\ + \"label\": \"Distribution of Pclass for males\",\n\t\ + \"chart_type\": \"bar\"\n}")), + HumanMessage(content=("The output looks perfect. This is exactly the response I was looking for.")), + AIMessage(content=("Thanks! Now I am more confident about the requirement. ")), + HumanMessagePromptTemplate.from_template( + "user_input = ```{user_input}```\ + use sample dataset below for reference delimited by <<<>>>\ + <<<{reference_data}>>>\ + {format_instructions}\ + from these inputs extract the following information\ + steps: the steps to be performed for the execution of task. stritcly remember to not include any graph or plotting related instructions..\ + label: suggest label to be displayed on the graph for the required ask in less than 3 words\ + chart_type: extract what type of chart user want to see.. if not specified then suggest which one \ + would be suitable for the task.. should be one of these ['bar', 'line', 'doughnut', 'scatter', 'text']\ + output text if graph cant be plotted or user required the answer in text format" + ), + ] + ) + + step_schema = ResponseSchema(name="steps", + description="steps to be performed for the execution of task. stritcly remember to not include any graph or plotting related instructions..") + label_schema = ResponseSchema(name="label", + description="suggest label to be displayed on the graph for the required ask") + chart_type_schema = ResponseSchema(name="chart_type", + description="Suggest the type of chart to be created.. if user specified\ + any chart type, select that.. otherwise suggest what would be suitable for the user ask\ + From the user input.. should be one of these ['bar', 'line', 'doughnut', 'scatter', 'text']\ + output text if graph cant be plotted or user required the answer in text format") + + response_schemas = [step_schema, label_schema, chart_type_schema] + output_parser = StructuredOutputParser.from_response_schemas(response_schemas) + format_instructions = output_parser.get_format_instructions() + + customer_messages = prompt_template.format_messages(user_input=query, + reference_data=jsondf, + format_instructions=format_instructions) + + llm = ChatOpenAI(model = 'gpt-3.5-turbo-0613', temperature = 0) + response = llm(customer_messages) + json_pandassteps_charttype = output_parser.parse(response.content) + print("pandas steps and charttype" , json_pandassteps_charttype) + agent = create_pandas_dataframe_agent( + ChatOpenAI(temperature=0, model="gpt-3.5-turbo-0613"), + df, + agent_type=AgentType.OPENAI_FUNCTIONS, + verbose=True, + return_intermediate_steps=True + ) + try: + if json_pandassteps_charttype['chart_type'] != "text": + agent_response = agent({ + 'input': f"Remove any steps related to charts or plotting from the steps mentioned in triple backticks\ + and Execute the Python script combining all the steps after remoing the chart related steps\ + Please don't use any print statements. Output should be a pandas dataframe only \ + steps to be performed : {json_pandassteps_charttype['steps']}" + }) + else: + chart_type, chart_label, chart_json_data = "text", None, None + print("The text block has been activated") + text_to_display = chat_with_df(query, table_name) + success = True + except langchain.schema.output_parser.OutputParserException as e: + success = False + chart_type, chart_label, chart_json_data = "text", None, None + text_to_display = "OutputParserException : " + str(e)[:25] + "...." + print(f"OutputParserException Occurred --> {str(e)}") + except Exception as e: + success = False + chart_type, chart_label, chart_json_data = "text", None, None + text_to_display = "AgentException : " + str(e)[:25] + "...." + print(f"Exception Occurred --> {str(e)}") + else: + graph_data_df = agent_response['intermediate_steps'][-1][-1] + print("intermediate steps " , agent_response['intermediate_steps']) + if isinstance(graph_data_df, pd.DataFrame): + final_data = dataframe_sanitizer(graph_data_df) + chart_label = json_pandassteps_charttype['label'] + chart_type = json_pandassteps_charttype['chart_type'] + chart_json_data = gen_chartdata(final_data, chart_label, chart_type) + success = True + text_to_display = None + else: + chart_type, chart_label, chart_json_data = "text", None, None + text_to_display = graph_data_df + success = True + finally: + final_response = dict(success=success, + chart_type=chart_type, + chart_label=chart_label, + chart_json_data=chart_json_data, + text_to_display=text_to_display) + return final_response + +def dataframe_sanitizer(raw_dataframe): + # Check if reset index is required or not + new_df = raw_dataframe.copy() + if new_df.index.name: + new_df = new_df.reset_index() + + print("new_df --> ", new_df) + # Rearrange the columns as object and int + object_columns = [col for col, dtype in new_df.dtypes.items() if dtype not in ['int8','int16','int32','int64', 'float64', 'float32']] + int_columns = [col for col, dtype in new_df.dtypes.items() if dtype in ['int8','int16','int32','int64', 'float64', 'float32']] + reordered_columns = object_columns + int_columns + print(f"object Columns , reordered columns : {object_columns}, {reordered_columns}") + new_df_reordered = new_df[reordered_columns] + print(f"New ordered columns : {new_df_reordered}") + + #Check if first column is object and second column is int + try: + if (new_df_reordered.shape[1] != 2) & (new_df_reordered.dtypes[1] not in ('int8','int16','int32','int64', 'float64', 'float32')): + print("========Exception in shape and type==========") + return_string = f"The output dataframe has columns count as {new_df_reordered.shape[1]}..\ + and the datatypes of columns present as {new_df_reordered.dtypes}..\ + so cant proceed further with plotting the same.." + print(return_string) + raise Exception(return_string) + + else: + new_df_reordered[new_df_reordered.columns[0]] = new_df_reordered[new_df_reordered.columns[0]].astype(str) + return new_df_reordered + except Exception as e: + print("Exception occurred" , str(e)) \ No newline at end of file diff --git a/referencefiles/badges.csv b/referencefiles/badges.csv new file mode 100644 index 0000000000000000000000000000000000000000..b54151ec59d79c56e78818636ca5d4741d69dc4c --- /dev/null +++ b/referencefiles/badges.csv @@ -0,0 +1,1001 @@ +GUI,BadgeID,BadgeType,BadgeStatus,Domain,InitiateaBadgeDate,EmployeeStatus,RankName,Service_Line,SubSL,Country,City,Badge Title,Pillar,BadgeEarnedDate +74224,7622,Platinum,Inactive,Finance,2022-12-10,Active,Manager,RMS,SubSL_3,Canada,New York,TAX01,,2023-04-09 +83243,6785,Bronze,Active,Finance,2022-10-21,Inactive,Director,TAX,SubSL_1,Canada,London,DS02,Technology,2023-04-10 +77659,1122,Gold,Active,Marketing,2023-05-12,Active,Supervisor,TAX,SubSL_1,Canada,London,TAX01,Technology,2022-12-27 +30762,3461,Platinum,Inactive,Data Strategy,2023-03-02,Active,Director,Consulting,SubSL_2,Canada,Toronto,TAX01,Technology,2023-05-07 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Strategy,2023-05-16,Active,Director,IT,SubSL_1,Canada,Los Angeles,DS02,Technology,2023-02-09 +47541,6697,Gold,Active,Finance,2022-12-19,Active,Supervisor,TAX,SubSL_1,Canada,Toronto,TAX01,Leadership,2023-01-29 +17379,3685,Platinum,Inactive,IT,2022-09-21,Inactive,Manager,TAX,SubSL_2,UK,Toronto,AI001,Business,2022-12-18 +33223,9093,Gold,Active,Finance,2023-06-13,Active,Employee,RMS,SubSL_1,UK,London,BI002,,2023-07-27 +20201,8832,Bronze,Inactive,HR,2023-03-24,Inactive,Manager,RMS,SubSL_1,Canada,New York,DS02,Technology,2023-08-08 +82652,4882,Silver,Inactive,HR,2023-01-31,Active,Supervisor,IT,SubSL_2,Canada,Toronto,TAX01,,2022-10-08 +93521,6101,Platinum,Active,Marketing,2022-11-03,Inactive,Manager,TAX,SubSL_3,UK,Toronto,BI002,,2023-03-26 +40745,7829,Gold,Active,IT,2023-03-25,Active,Supervisor,TAX,SubSL_1,USA,Toronto,DS02,,2022-10-29 +36847,8332,Gold,Inactive,Data Strategy,2023-05-01,Active,Supervisor,Consulting,SubSL_3,USA,London,AI001,Business,2023-02-04 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+79333,8657,Bronze,Inactive,Marketing,2023-04-17,Active,Director,Audit,SubSL_1,Canada,London,TAX01,,2022-10-31 +80671,8689,Bronze,Inactive,HR,2022-09-21,Active,Director,Audit,SubSL_2,USA,London,AI001,Technology,2023-09-03 +53569,3904,Bronze,Active,Marketing,2022-11-03,Active,Supervisor,TAX,SubSL_3,Canada,Los Angeles,AI001,Leadership,2023-06-30 +83316,6759,Bronze,Inactive,Finance,2023-05-28,Active,Supervisor,TAX,SubSL_2,UK,Los Angeles,DS02,Technology,2023-04-29 +12245,6353,Silver,Inactive,HR,2023-06-05,Inactive,Employee,IT,SubSL_3,UK,Los Angeles,BI002,Business,2023-01-30 +83058,6538,Bronze,Inactive,Marketing,2022-11-28,Inactive,Manager,IT,SubSL_1,USA,Toronto,AI001,Leadership,2023-07-18 +56552,2700,Gold,Inactive,HR,2023-03-03,Inactive,Supervisor,Audit,SubSL_2,Canada,London,AI001,Technology,2022-10-03 +87255,5027,Silver,Inactive,Data Strategy,2023-02-02,Active,Employee,Consulting,SubSL_1,USA,Los Angeles,AI001,Business,2023-01-24 +70546,7630,Gold,Active,Marketing,2023-09-15,Inactive,Supervisor,RMS,SubSL_2,UK,Toronto,AI001,,2023-09-12 +48311,4800,Bronze,Inactive,Data Strategy,2023-02-24,Inactive,Director,Consulting,SubSL_3,Canada,New York,TAX01,Leadership,2023-06-01 +91841,5433,Gold,Active,HR,2023-07-03,Inactive,Supervisor,Consulting,SubSL_2,USA,Los Angeles,AI001,,2022-10-14 +31389,2859,Platinum,Inactive,IT,2022-12-09,Active,Manager,Consulting,SubSL_2,USA,London,TAX01,,2022-10-31 +70578,4967,Platinum,Active,Finance,2022-12-17,Active,Employee,IT,SubSL_2,UK,New York,BI002,Technology,2023-07-13 +11959,8353,Gold,Active,Marketing,2023-03-26,Active,Manager,TAX,SubSL_3,UK,New York,AI001,,2023-04-28 +14142,4456,Platinum,Active,Data Strategy,2022-10-26,Inactive,Director,IT,SubSL_2,USA,Los Angeles,TAX01,Leadership,2023-08-13 +67875,7661,Gold,Active,HR,2022-12-19,Active,Director,RMS,SubSL_1,USA,Los Angeles,AI001,,2023-09-07 +91594,7119,Gold,Inactive,IT,2023-06-08,Inactive,Manager,IT,SubSL_3,Canada,Toronto,TAX01,Business,2023-01-13 +52683,4664,Gold,Inactive,Data Strategy,2023-06-08,Inactive,Manager,Audit,SubSL_2,USA,Toronto,AI001,Technology,2022-10-13 +57539,7980,Platinum,Inactive,HR,2023-02-02,Inactive,Director,Consulting,SubSL_2,USA,New York,TAX01,Technology,2023-04-19 +42651,4407,Silver,Active,Finance,2022-09-23,Active,Employee,Audit,SubSL_2,USA,Los Angeles,TAX01,Leadership,2023-03-22 +35728,5476,Gold,Active,Finance,2023-09-07,Inactive,Employee,IT,SubSL_1,USA,New York,DS02,Technology,2022-10-11 +18364,8850,Gold,Active,IT,2023-06-26,Active,Manager,TAX,SubSL_1,Canada,New York,BI002,,2023-01-29 +70117,5539,Bronze,Inactive,HR,2023-04-28,Active,Supervisor,TAX,SubSL_3,UK,London,DS02,Technology,2023-06-27 +11399,9110,Gold,Active,IT,2023-05-14,Inactive,Director,RMS,SubSL_1,USA,Toronto,DS02,Business,2023-09-17 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York,TAX01,Technology,2022-12-26 +64022,7871,Platinum,Inactive,IT,2023-08-01,Inactive,Manager,IT,SubSL_2,Canada,New York,TAX01,,2023-07-18 +81257,8836,Bronze,Inactive,IT,2022-11-13,Active,Manager,RMS,SubSL_3,USA,New York,TAX01,Technology,2023-05-24 +36675,5531,Bronze,Inactive,Finance,2022-10-03,Active,Supervisor,Audit,SubSL_1,Canada,New York,AI001,Technology,2023-08-27 +95793,2414,Gold,Active,Marketing,2023-06-08,Active,Supervisor,IT,SubSL_1,Canada,Los Angeles,BI002,,2022-09-21 +66853,6414,Bronze,Active,Finance,2023-02-11,Inactive,Manager,Audit,SubSL_2,Canada,London,TAX01,Technology,2023-07-19 +12266,4963,Gold,Inactive,Finance,2022-10-18,Inactive,Director,Audit,SubSL_1,UK,New York,TAX01,Leadership,2022-12-23 +78442,1511,Gold,Active,HR,2023-03-18,Active,Manager,TAX,SubSL_3,UK,New York,DS02,Technology,2023-01-23 +73658,7969,Silver,Inactive,Finance,2022-10-17,Active,Manager,Consulting,SubSL_3,Canada,Toronto,BI002,,2023-02-12 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Angeles,DS02,Leadership,2023-07-07 +87283,7361,Gold,Active,Marketing,2023-03-14,Active,Director,Consulting,SubSL_3,UK,Los Angeles,DS02,Business,2023-06-10 +54045,3950,Gold,Inactive,HR,2022-12-12,Inactive,Director,Consulting,SubSL_3,Canada,London,DS02,Technology,2023-08-15 +99276,3410,Bronze,Active,Finance,2023-09-11,Inactive,Employee,TAX,SubSL_1,UK,Los Angeles,TAX01,Business,2023-06-12 +95647,6490,Silver,Inactive,IT,2023-01-31,Inactive,Manager,TAX,SubSL_3,Canada,Los Angeles,AI001,,2022-11-15 +45411,3686,Bronze,Inactive,Finance,2023-08-05,Inactive,Employee,IT,SubSL_2,Canada,Los Angeles,BI002,Technology,2022-10-25 +64914,8213,Bronze,Active,Finance,2023-05-13,Active,Supervisor,IT,SubSL_2,Canada,Los Angeles,DS02,Leadership,2023-04-16 +66132,7221,Bronze,Inactive,IT,2023-02-13,Inactive,Employee,Consulting,SubSL_1,USA,New York,DS02,,2023-03-08 +93947,8326,Gold,Inactive,Marketing,2023-03-05,Inactive,Employee,Consulting,SubSL_1,USA,New York,TAX01,Business,2022-11-14 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York,BI002,Technology,2023-05-08 +47355,2631,Gold,Inactive,Data Strategy,2023-09-18,Inactive,Manager,Audit,SubSL_3,USA,Los Angeles,TAX01,Business,2023-06-21 +63902,3345,Silver,Active,Finance,2023-03-07,Active,Director,Audit,SubSL_1,UK,Toronto,DS02,,2022-12-27 +26616,1391,Silver,Active,HR,2022-11-12,Active,Supervisor,RMS,SubSL_1,UK,New York,BI002,Technology,2023-05-30 +78291,2296,Bronze,Inactive,Data Strategy,2023-08-24,Active,Director,Consulting,SubSL_1,Canada,New York,TAX01,,2022-11-02 +75767,6267,Silver,Active,HR,2023-03-21,Active,Supervisor,IT,SubSL_1,USA,London,DS02,Business,2023-05-17 +29232,2161,Platinum,Inactive,HR,2023-01-23,Inactive,Director,Consulting,SubSL_3,UK,Los Angeles,BI002,Leadership,2023-06-02 +77383,9033,Gold,Active,Marketing,2023-03-25,Active,Director,Audit,SubSL_1,Canada,New York,AI001,Leadership,2023-08-16 +94848,7172,Gold,Inactive,Finance,2022-09-21,Inactive,Employee,TAX,SubSL_3,UK,Los Angeles,DS02,Business,2023-06-12 +68671,1819,Silver,Inactive,Marketing,2022-11-14,Inactive,Manager,TAX,SubSL_3,UK,London,AI001,Technology,2023-04-29 +78431,6378,Bronze,Active,Data Strategy,2022-10-08,Active,Employee,Consulting,SubSL_1,Canada,Toronto,DS02,Leadership,2023-02-26 +96378,7378,Bronze,Inactive,Marketing,2022-12-31,Inactive,Manager,Consulting,SubSL_1,USA,Toronto,DS02,,2022-10-03 +68481,4023,Gold,Active,Finance,2023-08-25,Inactive,Manager,Consulting,SubSL_1,Canada,New York,AI001,Leadership,2023-09-07 +79580,7107,Bronze,Active,Data Strategy,2023-06-21,Active,Director,Consulting,SubSL_1,USA,New York,DS02,,2022-10-03 +46638,3721,Gold,Active,IT,2023-08-18,Inactive,Director,TAX,SubSL_3,USA,New York,DS02,Technology,2022-11-14 +42384,7639,Bronze,Inactive,IT,2023-08-03,Active,Supervisor,Audit,SubSL_3,USA,Los Angeles,BI002,,2022-11-29 +39102,1344,Silver,Inactive,Finance,2023-08-25,Inactive,Supervisor,Audit,SubSL_3,UK,Toronto,TAX01,Leadership,2023-03-18 +40246,9181,Silver,Active,Data Strategy,2023-05-30,Active,Manager,TAX,SubSL_3,Canada,London,DS02,,2022-09-27 +51770,1774,Bronze,Active,IT,2023-02-08,Inactive,Supervisor,IT,SubSL_2,USA,London,TAX01,Technology,2023-05-13 +55933,2066,Platinum,Active,IT,2023-05-30,Active,Supervisor,IT,SubSL_3,Canada,Los Angeles,TAX01,,2023-01-13 +85305,4396,Gold,Inactive,Marketing,2023-07-06,Active,Employee,RMS,SubSL_2,Canada,London,BI002,Technology,2023-09-17 +98197,8087,Bronze,Inactive,Finance,2023-06-18,Inactive,Manager,RMS,SubSL_3,USA,New York,BI002,Business,2023-01-19 +24860,6387,Platinum,Inactive,Marketing,2022-10-18,Active,Director,IT,SubSL_2,Canada,Los Angeles,AI001,Technology,2022-12-27 +53995,5781,Bronze,Inactive,IT,2023-06-03,Inactive,Supervisor,TAX,SubSL_1,USA,New York,TAX01,Leadership,2023-03-09 +41556,7223,Gold,Active,IT,2023-05-29,Inactive,Director,RMS,SubSL_1,USA,Toronto,TAX01,Leadership,2023-05-04 +83850,3584,Silver,Active,Marketing,2023-01-20,Inactive,Supervisor,TAX,SubSL_1,UK,New York,TAX01,Leadership,2023-06-12 +43004,3418,Gold,Inactive,HR,2022-10-15,Inactive,Supervisor,Audit,SubSL_3,UK,London,BI002,,2023-05-13 +78678,8214,Gold,Active,IT,2023-06-23,Inactive,Director,RMS,SubSL_2,UK,London,TAX01,Leadership,2022-10-19 +83946,8332,Gold,Inactive,IT,2023-05-27,Active,Employee,IT,SubSL_3,UK,London,DS02,Leadership,2023-08-03 +81709,1524,Silver,Inactive,Data Strategy,2023-03-15,Inactive,Manager,Audit,SubSL_3,USA,New York,AI001,Technology,2023-09-07 +87410,9229,Bronze,Active,Finance,2023-07-02,Inactive,Supervisor,Consulting,SubSL_1,USA,Los Angeles,BI002,Leadership,2023-03-14 +77318,7983,Gold,Active,IT,2023-02-05,Inactive,Director,RMS,SubSL_1,USA,Los Angeles,DS02,Business,2023-02-08 +48251,7591,Gold,Inactive,Marketing,2023-04-09,Inactive,Employee,Consulting,SubSL_1,UK,Los Angeles,DS02,Technology,2023-09-08 +85861,4292,Gold,Inactive,HR,2022-12-28,Inactive,Employee,Audit,SubSL_3,Canada,Los Angeles,AI001,Technology,2023-04-18 +74581,7736,Gold,Active,HR,2022-11-18,Inactive,Supervisor,IT,SubSL_2,Canada,New York,BI002,Leadership,2022-12-04 +23153,6926,Silver,Inactive,Data Strategy,2023-05-30,Inactive,Director,TAX,SubSL_2,Canada,London,TAX01,Technology,2023-02-15 +63080,3501,Gold,Inactive,HR,2022-12-22,Inactive,Manager,Consulting,SubSL_1,Canada,New York,TAX01,Leadership,2023-07-08 +47800,8484,Gold,Active,Finance,2023-05-16,Inactive,Employee,TAX,SubSL_2,UK,Toronto,DS02,Technology,2022-10-14 +70903,3343,Platinum,Active,IT,2023-08-29,Active,Employee,TAX,SubSL_2,UK,Los Angeles,AI001,Leadership,2023-06-10 +41561,9010,Gold,Active,Marketing,2022-09-27,Inactive,Director,IT,SubSL_1,Canada,Toronto,BI002,Leadership,2023-07-20 +94094,4568,Bronze,Active,IT,2023-05-24,Active,Director,TAX,SubSL_3,UK,Toronto,TAX01,Leadership,2022-10-13 +21059,7105,Platinum,Inactive,Marketing,2023-01-11,Active,Supervisor,TAX,SubSL_3,Canada,Toronto,TAX01,Leadership,2023-08-21 +52673,6896,Platinum,Active,IT,2022-10-18,Active,Director,Consulting,SubSL_2,UK,Los Angeles,TAX01,Leadership,2023-02-25 +93395,5921,Bronze,Active,Data Strategy,2023-03-22,Inactive,Manager,IT,SubSL_1,UK,London,BI002,Leadership,2023-01-09 +57291,7300,Platinum,Active,IT,2022-11-08,Inactive,Employee,IT,SubSL_2,USA,Toronto,TAX01,Business,2023-04-23 +79746,7667,Silver,Inactive,Data Strategy,2022-11-14,Active,Employee,TAX,SubSL_1,Canada,Los Angeles,TAX01,,2023-09-14 +93628,9632,Platinum,Inactive,HR,2023-04-04,Inactive,Supervisor,RMS,SubSL_2,Canada,Los Angeles,BI002,Leadership,2022-12-06 +60363,1098,Platinum,Active,Data Strategy,2023-02-20,Active,Employee,TAX,SubSL_2,Canada,London,TAX01,Leadership,2023-06-08 +79121,5810,Bronze,Active,HR,2023-03-16,Inactive,Manager,RMS,SubSL_3,Canada,Los Angeles,AI001,Business,2022-10-07 +82577,9689,Gold,Inactive,Finance,2023-02-02,Inactive,Employee,TAX,SubSL_3,Canada,Toronto,BI002,Technology,2022-11-01 +29484,1601,Platinum,Active,Data Strategy,2023-04-05,Active,Employee,TAX,SubSL_1,USA,Los Angeles,TAX01,Leadership,2023-08-09 +23454,1806,Gold,Inactive,Finance,2023-04-22,Inactive,Manager,RMS,SubSL_3,USA,London,TAX01,Leadership,2023-08-27 +78659,5928,Platinum,Inactive,Data Strategy,2023-08-13,Inactive,Manager,Consulting,SubSL_2,USA,New York,AI001,,2023-02-28 +90326,5831,Silver,Active,HR,2022-12-06,Inactive,Supervisor,Audit,SubSL_3,Canada,Toronto,BI002,Business,2023-01-29 +81451,1417,Bronze,Active,Data Strategy,2022-10-05,Active,Supervisor,RMS,SubSL_2,USA,Los Angeles,AI001,Leadership,2022-12-27 +30237,9369,Bronze,Inactive,Data Strategy,2023-01-11,Inactive,Director,Consulting,SubSL_1,USA,New York,DS02,Leadership,2023-05-08 +46737,4946,Platinum,Active,Finance,2023-08-17,Inactive,Supervisor,IT,SubSL_1,Canada,Los Angeles,DS02,Business,2023-06-28 +29688,1802,Gold,Active,Finance,2023-03-30,Inactive,Manager,IT,SubSL_1,USA,Toronto,BI002,,2023-08-14 +55607,7791,Silver,Active,HR,2023-06-13,Active,Employee,Consulting,SubSL_1,UK,Los Angeles,AI001,Technology,2023-07-06 +15269,8124,Silver,Inactive,Marketing,2023-08-09,Active,Employee,TAX,SubSL_2,Canada,London,AI001,Leadership,2022-11-23 +82309,7744,Silver,Inactive,Data Strategy,2023-07-28,Active,Manager,Audit,SubSL_3,Canada,Los Angeles,BI002,Leadership,2023-02-04 +46743,2787,Bronze,Active,Data Strategy,2022-11-20,Inactive,Employee,TAX,SubSL_3,USA,London,BI002,Leadership,2023-08-10 +81355,6443,Gold,Active,Data Strategy,2023-01-25,Inactive,Director,RMS,SubSL_2,UK,Toronto,TAX01,Business,2023-01-26 +72638,5871,Gold,Inactive,Finance,2022-10-11,Inactive,Director,RMS,SubSL_3,USA,New York,BI002,Business,2023-01-29 +99676,2738,Silver,Active,Data Strategy,2022-10-29,Inactive,Supervisor,Consulting,SubSL_1,USA,Los Angeles,DS02,,2023-03-11 +12661,3512,Bronze,Active,Finance,2023-01-13,Active,Director,RMS,SubSL_3,UK,London,AI001,,2023-09-06 +66761,2913,Silver,Inactive,Finance,2023-02-22,Inactive,Employee,TAX,SubSL_3,UK,Los Angeles,DS02,Technology,2023-06-24 +17886,6436,Silver,Active,Marketing,2023-06-25,Inactive,Director,IT,SubSL_1,USA,New York,TAX01,Business,2023-02-11 +83591,9615,Silver,Inactive,Marketing,2023-03-30,Inactive,Employee,Audit,SubSL_2,UK,New York,DS02,Business,2023-03-12 +86651,2135,Silver,Active,Finance,2023-02-05,Active,Supervisor,Consulting,SubSL_2,UK,New York,AI001,Technology,2023-04-23 +50303,6368,Silver,Inactive,IT,2023-02-26,Active,Manager,Consulting,SubSL_2,USA,Toronto,BI002,Technology,2023-03-05 +17162,6596,Silver,Active,Marketing,2023-05-21,Active,Manager,IT,SubSL_1,UK,London,AI001,Leadership,2023-09-02 +23826,2725,Platinum,Inactive,Data Strategy,2023-07-10,Active,Employee,RMS,SubSL_3,Canada,Los Angeles,TAX01,Business,2022-10-21 +56621,7422,Bronze,Active,Data Strategy,2023-03-15,Active,Supervisor,Consulting,SubSL_2,UK,New York,BI002,Technology,2022-11-22 +55869,8883,Gold,Inactive,Finance,2023-01-15,Active,Manager,RMS,SubSL_2,UK,London,TAX01,Leadership,2022-12-15 +54848,2074,Gold,Active,Marketing,2023-07-04,Active,Employee,Consulting,SubSL_2,USA,New York,DS02,Business,2023-05-06 +46072,5935,Platinum,Active,Data Strategy,2022-12-05,Inactive,Manager,Consulting,SubSL_1,USA,Los Angeles,AI001,,2023-02-16 +60720,2217,Platinum,Active,Finance,2022-11-05,Inactive,Employee,TAX,SubSL_1,Canada,New York,DS02,Technology,2023-08-07 +49150,5498,Gold,Inactive,HR,2023-01-15,Inactive,Employee,IT,SubSL_2,Canada,Toronto,TAX01,Leadership,2023-09-12 +62828,3833,Platinum,Inactive,Data Strategy,2023-01-30,Active,Director,RMS,SubSL_1,Canada,Los Angeles,TAX01,Leadership,2023-09-12 +57459,3758,Bronze,Active,Data Strategy,2022-11-28,Inactive,Employee,Audit,SubSL_3,UK,London,AI001,Business,2022-09-23 +78682,7588,Silver,Inactive,Data Strategy,2023-02-08,Active,Manager,Consulting,SubSL_1,Canada,New York,AI001,,2023-04-30 +56732,2789,Gold,Inactive,HR,2022-09-21,Inactive,Employee,TAX,SubSL_3,USA,New York,BI002,,2022-11-24 +26927,8461,Silver,Active,Marketing,2023-07-28,Inactive,Manager,TAX,SubSL_3,UK,Los Angeles,BI002,,2022-11-09 +52844,6574,Platinum,Inactive,Marketing,2023-03-27,Inactive,Director,TAX,SubSL_3,UK,London,BI002,,2023-05-10 +34584,3332,Gold,Active,Data Strategy,2022-11-21,Active,Director,Consulting,SubSL_2,UK,New York,AI001,Leadership,2022-12-15 +37932,8145,Silver,Active,Marketing,2022-11-09,Active,Manager,Consulting,SubSL_1,Canada,New York,DS02,Leadership,2023-04-22 +17515,4667,Gold,Active,HR,2023-02-14,Inactive,Supervisor,TAX,SubSL_1,UK,London,BI002,,2023-08-19 +31471,2528,Platinum,Active,Marketing,2022-12-12,Inactive,Manager,Consulting,SubSL_2,Canada,New York,DS02,Technology,2022-10-31 +20829,5911,Gold,Inactive,Data Strategy,2023-06-26,Active,Director,Audit,SubSL_1,UK,Los Angeles,DS02,Leadership,2023-08-16 +43722,3307,Platinum,Active,HR,2022-11-03,Active,Director,TAX,SubSL_3,USA,New York,AI001,Technology,2022-10-16 +87788,2261,Gold,Inactive,Marketing,2022-11-05,Inactive,Supervisor,TAX,SubSL_2,USA,London,AI001,Business,2023-07-29 +58773,9185,Platinum,Active,Marketing,2022-11-16,Active,Director,TAX,SubSL_2,Canada,Los Angeles,DS02,Business,2022-11-25 +95883,3860,Bronze,Inactive,Data Strategy,2023-02-02,Active,Supervisor,TAX,SubSL_2,Canada,Los Angeles,AI001,Business,2023-07-21 +35191,6104,Platinum,Active,IT,2023-02-18,Active,Manager,Consulting,SubSL_1,Canada,Toronto,AI001,,2023-06-26 +39610,3655,Bronze,Active,HR,2023-05-21,Inactive,Supervisor,Consulting,SubSL_3,Canada,Toronto,DS02,Business,2023-09-17 +89110,8640,Silver,Inactive,IT,2022-12-26,Active,Supervisor,IT,SubSL_2,UK,Toronto,BI002,Leadership,2022-12-23 +86377,4405,Platinum,Inactive,IT,2023-02-28,Inactive,Supervisor,RMS,SubSL_2,UK,Toronto,DS02,,2023-07-27 +35337,7082,Platinum,Inactive,Finance,2023-02-28,Inactive,Supervisor,Audit,SubSL_2,Canada,London,DS02,,2023-03-17 +85606,4479,Gold,Active,HR,2023-08-06,Active,Supervisor,Audit,SubSL_2,Canada,Los Angeles,TAX01,Technology,2023-01-21 +16294,4676,Bronze,Active,Marketing,2022-09-20,Active,Supervisor,TAX,SubSL_2,USA,London,DS02,Technology,2023-07-06 +88784,8423,Platinum,Active,Data Strategy,2022-12-20,Inactive,Director,IT,SubSL_3,Canada,Toronto,AI001,Business,2023-04-04 +47394,1097,Platinum,Active,IT,2022-11-22,Inactive,Supervisor,TAX,SubSL_1,Canada,Toronto,DS02,Business,2023-07-09 +24305,8475,Gold,Inactive,Data Strategy,2023-07-31,Inactive,Supervisor,Audit,SubSL_2,UK,Los Angeles,AI001,Technology,2023-01-14 +65269,9313,Gold,Inactive,Data Strategy,2022-11-04,Active,Employee,Consulting,SubSL_3,USA,New York,BI002,Business,2023-09-10 +27472,9378,Gold,Active,Marketing,2022-12-26,Active,Manager,RMS,SubSL_1,Canada,New York,AI001,,2023-04-20 +84742,1466,Gold,Active,Data Strategy,2023-09-10,Active,Director,IT,SubSL_2,UK,Toronto,TAX01,Technology,2023-06-10 +76538,5074,Silver,Active,HR,2023-06-27,Active,Manager,Audit,SubSL_3,Canada,New York,AI001,,2023-01-06 +78652,7955,Platinum,Active,IT,2023-04-10,Active,Employee,Audit,SubSL_3,USA,London,AI001,Leadership,2022-11-16 +26971,5935,Platinum,Active,HR,2023-04-20,Active,Employee,Audit,SubSL_3,Canada,Toronto,AI001,Technology,2022-11-03 +21099,8808,Platinum,Inactive,IT,2023-01-08,Active,Employee,RMS,SubSL_3,USA,Los Angeles,DS02,,2023-05-02 +84818,2039,Bronze,Inactive,Marketing,2023-07-16,Active,Employee,IT,SubSL_3,Canada,New York,DS02,,2023-09-16 +53247,3849,Bronze,Active,Marketing,2023-07-18,Active,Supervisor,TAX,SubSL_1,USA,London,AI001,,2022-09-24 +13977,4626,Gold,Inactive,Finance,2022-11-05,Active,Manager,RMS,SubSL_2,USA,New York,AI001,Technology,2022-10-24 +44036,4581,Silver,Active,Marketing,2022-11-08,Active,Director,Audit,SubSL_1,Canada,New York,TAX01,Technology,2023-02-21 +25166,4291,Bronze,Active,Data Strategy,2023-06-21,Inactive,Director,Consulting,SubSL_3,USA,Toronto,DS02,,2023-02-20 +73658,1822,Platinum,Active,Data Strategy,2023-06-30,Inactive,Manager,Consulting,SubSL_3,UK,New York,TAX01,,2022-12-25 +14678,7391,Bronze,Active,Finance,2023-09-05,Inactive,Director,Audit,SubSL_3,UK,Los Angeles,TAX01,Leadership,2023-04-03 +93326,6109,Gold,Inactive,Finance,2022-12-31,Active,Supervisor,TAX,SubSL_1,USA,London,TAX01,,2022-11-12 +68432,8184,Gold,Active,Finance,2023-09-02,Inactive,Manager,Audit,SubSL_1,UK,New York,DS02,Technology,2023-02-06 +22559,8078,Gold,Inactive,IT,2023-06-11,Active,Director,IT,SubSL_1,USA,New York,TAX01,Leadership,2022-12-05 +87228,5282,Gold,Inactive,Marketing,2023-01-01,Active,Employee,Audit,SubSL_1,UK,London,BI002,,2023-06-24 +55269,1457,Silver,Inactive,Data Strategy,2023-03-21,Active,Director,Consulting,SubSL_2,Canada,Los Angeles,DS02,,2023-07-03 +90892,4335,Bronze,Active,IT,2023-06-26,Inactive,Director,Audit,SubSL_1,UK,Los Angeles,AI001,,2023-01-16 +43078,2191,Platinum,Active,IT,2022-11-17,Active,Employee,Consulting,SubSL_1,Canada,New York,DS02,,2023-05-09 +41872,9672,Platinum,Active,Marketing,2023-08-03,Active,Employee,RMS,SubSL_2,Canada,New York,AI001,Technology,2022-10-18 +26033,7581,Bronze,Active,Finance,2023-04-06,Active,Director,Consulting,SubSL_2,Canada,Los Angeles,BI002,,2023-05-23 +19204,7452,Silver,Active,HR,2023-01-17,Inactive,Supervisor,Consulting,SubSL_3,Canada,Los Angeles,TAX01,Technology,2022-09-22 +25254,6913,Silver,Active,IT,2023-05-26,Active,Manager,RMS,SubSL_1,UK,New York,TAX01,Leadership,2023-02-26 +72605,2352,Bronze,Inactive,Finance,2023-05-03,Active,Director,Audit,SubSL_3,USA,Los Angeles,AI001,Leadership,2023-03-07 +64665,7122,Platinum,Inactive,IT,2023-08-04,Active,Director,RMS,SubSL_2,Canada,New York,DS02,Technology,2023-08-28 +56684,2399,Silver,Inactive,Data Strategy,2023-03-09,Inactive,Director,Audit,SubSL_2,USA,New York,AI001,Business,2022-11-12 +29376,7331,Silver,Active,HR,2023-02-28,Inactive,Employee,Consulting,SubSL_3,USA,London,TAX01,Business,2023-06-12 +39727,8441,Bronze,Active,Marketing,2023-05-11,Inactive,Supervisor,TAX,SubSL_3,UK,Los Angeles,DS02,,2023-03-29 +26688,6157,Silver,Active,IT,2023-05-18,Inactive,Employee,Consulting,SubSL_1,USA,London,DS02,Technology,2023-05-28 +97017,7822,Platinum,Inactive,IT,2023-08-17,Active,Director,IT,SubSL_1,Canada,Toronto,TAX01,Technology,2023-03-10 +76096,4960,Silver,Active,Data Strategy,2022-11-24,Active,Employee,Audit,SubSL_1,Canada,Toronto,DS02,Business,2023-06-01 +35682,7626,Silver,Active,HR,2023-08-31,Inactive,Employee,RMS,SubSL_2,Canada,Los Angeles,BI002,,2023-01-25 +27085,3487,Gold,Inactive,Marketing,2023-03-11,Inactive,Manager,TAX,SubSL_2,Canada,Los Angeles,AI001,Business,2022-12-27 +31580,6079,Silver,Active,Data Strategy,2023-04-29,Active,Supervisor,TAX,SubSL_3,UK,New York,BI002,Business,2023-02-05 +70968,5759,Gold,Active,Marketing,2023-04-09,Active,Supervisor,Consulting,SubSL_1,UK,London,DS02,,2022-11-16 +61388,5249,Gold,Active,Marketing,2023-04-23,Active,Employee,TAX,SubSL_3,UK,Toronto,AI001,Technology,2023-08-29 +93755,8022,Gold,Active,Finance,2023-03-06,Active,Employee,IT,SubSL_2,Canada,New York,BI002,Technology,2022-11-26 +89111,6814,Platinum,Inactive,Marketing,2023-07-27,Active,Director,TAX,SubSL_1,USA,New York,AI001,Technology,2023-05-14 +29502,9783,Bronze,Active,HR,2023-05-17,Active,Manager,RMS,SubSL_2,UK,Toronto,DS02,Business,2023-03-22 +60957,9915,Bronze,Active,HR,2022-12-10,Inactive,Supervisor,TAX,SubSL_2,Canada,Los Angeles,TAX01,Technology,2023-07-05 +29227,5983,Gold,Active,Data Strategy,2023-02-23,Inactive,Manager,IT,SubSL_1,UK,Toronto,TAX01,Technology,2023-01-13 +89837,4662,Silver,Inactive,HR,2023-07-15,Inactive,Employee,TAX,SubSL_3,UK,Toronto,BI002,Technology,2023-07-24 +87309,9446,Silver,Active,Finance,2023-04-20,Active,Manager,Consulting,SubSL_2,USA,Toronto,TAX01,Technology,2023-01-28 +48284,9026,Silver,Inactive,Marketing,2022-11-22,Active,Director,IT,SubSL_1,UK,Toronto,DS02,Leadership,2022-10-05 +79246,2261,Silver,Active,HR,2023-07-08,Active,Employee,TAX,SubSL_2,USA,Toronto,AI001,Technology,2023-01-07 +48985,5597,Platinum,Active,Finance,2022-11-06,Inactive,Supervisor,TAX,SubSL_3,USA,Los Angeles,AI001,Leadership,2023-05-07 +64214,4310,Bronze,Inactive,Marketing,2023-03-07,Active,Employee,IT,SubSL_2,UK,New York,BI002,Business,2023-06-10 +99333,4597,Platinum,Active,Data Strategy,2023-09-18,Active,Employee,TAX,SubSL_3,USA,Toronto,BI002,,2023-07-13 +40545,2448,Silver,Inactive,Marketing,2023-03-15,Active,Director,Audit,SubSL_1,Canada,Los Angeles,TAX01,,2022-10-04 +87233,3198,Bronze,Inactive,Finance,2023-04-29,Inactive,Director,Audit,SubSL_2,Canada,Toronto,BI002,,2023-09-07 +39539,5014,Bronze,Inactive,IT,2022-12-05,Inactive,Employee,Consulting,SubSL_1,UK,London,BI002,,2023-05-03 +89435,1308,Gold,Inactive,IT,2023-09-12,Active,Employee,TAX,SubSL_1,UK,New York,AI001,,2023-01-09 +31278,4148,Platinum,Active,IT,2023-07-24,Inactive,Director,Consulting,SubSL_3,USA,New York,DS02,,2022-09-22 +44039,6682,Silver,Inactive,Marketing,2023-04-08,Active,Manager,TAX,SubSL_2,UK,Los Angeles,DS02,Business,2023-09-16 +22809,4610,Silver,Inactive,Marketing,2023-04-08,Active,Employee,RMS,SubSL_3,USA,Toronto,DS02,Business,2023-03-14 +96921,1003,Bronze,Active,Finance,2023-05-16,Inactive,Employee,TAX,SubSL_1,Canada,Los Angeles,DS02,Technology,2023-09-19 +28346,8164,Gold,Inactive,Data Strategy,2023-08-02,Inactive,Director,RMS,SubSL_2,Canada,London,TAX01,Technology,2023-07-29 +97341,4582,Silver,Active,Finance,2023-08-06,Active,Manager,TAX,SubSL_3,UK,London,TAX01,Leadership,2022-10-30 +53312,1953,Gold,Active,Finance,2023-09-15,Inactive,Director,TAX,SubSL_1,Canada,London,DS02,Business,2022-12-06 +32728,8681,Platinum,Active,Data Strategy,2023-08-28,Active,Manager,Audit,SubSL_1,UK,Toronto,BI002,Leadership,2023-04-05 +56525,5821,Platinum,Active,Marketing,2023-03-26,Active,Employee,Audit,SubSL_1,Canada,New York,TAX01,Business,2023-05-23 +36131,7538,Gold,Active,Finance,2022-12-03,Active,Director,TAX,SubSL_1,UK,London,AI001,Business,2022-12-16 +79481,5037,Gold,Inactive,Marketing,2023-08-24,Active,Supervisor,Consulting,SubSL_1,UK,Los Angeles,AI001,Business,2022-12-25 +73265,4414,Bronze,Active,Finance,2023-02-20,Inactive,Director,Consulting,SubSL_1,UK,London,DS02,Leadership,2023-07-04 +35355,6345,Bronze,Active,Finance,2023-03-29,Inactive,Manager,RMS,SubSL_1,Canada,Toronto,TAX01,,2023-08-13 +55615,3309,Gold,Inactive,Finance,2023-06-16,Active,Supervisor,Consulting,SubSL_1,Canada,Los Angeles,DS02,Leadership,2023-06-08 +77462,2651,Bronze,Inactive,HR,2023-08-25,Active,Employee,Consulting,SubSL_1,Canada,Los Angeles,AI001,Technology,2023-05-01 +71884,6782,Bronze,Active,Data Strategy,2022-11-25,Inactive,Manager,RMS,SubSL_2,UK,Toronto,DS02,Technology,2023-06-08 +91482,3364,Bronze,Active,Data Strategy,2023-04-30,Active,Manager,Audit,SubSL_1,Canada,London,BI002,Technology,2023-04-01 +88502,6020,Silver,Active,HR,2023-03-05,Active,Manager,IT,SubSL_2,UK,Toronto,AI001,Leadership,2022-10-27 +47709,9469,Gold,Inactive,HR,2023-06-15,Inactive,Manager,TAX,SubSL_1,UK,Toronto,BI002,Leadership,2023-08-14 +14533,9349,Platinum,Inactive,HR,2022-12-07,Active,Supervisor,Audit,SubSL_2,UK,New York,BI002,,2023-05-19 +48480,5729,Bronze,Inactive,IT,2023-04-14,Inactive,Supervisor,RMS,SubSL_3,USA,Toronto,DS02,Leadership,2023-08-22 +92393,1521,Gold,Inactive,Marketing,2023-07-05,Inactive,Director,RMS,SubSL_1,Canada,Toronto,BI002,Business,2023-06-10 +83693,4101,Platinum,Inactive,IT,2023-01-11,Inactive,Manager,Audit,SubSL_1,USA,New York,AI001,Technology,2023-01-23 +94014,2005,Silver,Active,Finance,2023-03-28,Active,Director,IT,SubSL_1,UK,New York,TAX01,,2023-06-02 +11245,7586,Platinum,Inactive,Finance,2023-05-13,Inactive,Director,Consulting,SubSL_2,Canada,New York,DS02,Business,2023-07-09 +15669,4126,Silver,Inactive,HR,2023-01-16,Active,Supervisor,Consulting,SubSL_2,Canada,Toronto,TAX01,Leadership,2023-06-24 +29074,8097,Bronze,Inactive,HR,2022-10-23,Active,Employee,TAX,SubSL_2,UK,Toronto,BI002,,2022-11-07 +58077,3607,Platinum,Inactive,Finance,2022-11-11,Inactive,Director,Consulting,SubSL_3,UK,London,AI001,Business,2022-12-28 +88983,9589,Silver,Active,Finance,2023-01-19,Inactive,Director,Consulting,SubSL_2,USA,New York,BI002,Business,2022-11-18 +26807,2831,Silver,Active,IT,2022-09-20,Inactive,Director,RMS,SubSL_3,Canada,Toronto,TAX01,Technology,2023-03-27 +25019,5192,Platinum,Active,Marketing,2023-04-27,Inactive,Manager,Audit,SubSL_2,USA,Los Angeles,TAX01,Technology,2023-04-17 +73441,4677,Silver,Active,Data Strategy,2023-05-30,Inactive,Employee,Consulting,SubSL_1,UK,London,BI002,Business,2022-09-30 +99694,4492,Bronze,Active,Finance,2023-01-13,Inactive,Director,TAX,SubSL_1,USA,New York,DS02,Technology,2023-01-30 +96958,4200,Silver,Inactive,Data Strategy,2022-12-16,Inactive,Supervisor,RMS,SubSL_3,USA,New York,AI001,Technology,2023-07-28 +58013,6818,Silver,Inactive,HR,2022-09-25,Inactive,Employee,Audit,SubSL_2,UK,Los Angeles,BI002,Technology,2023-08-12 +19952,9374,Silver,Active,Finance,2023-08-11,Active,Manager,TAX,SubSL_2,UK,Toronto,TAX01,,2022-11-16 +68819,4717,Silver,Inactive,Data Strategy,2022-10-15,Inactive,Director,RMS,SubSL_1,Canada,London,DS02,Technology,2023-03-06 +52989,4035,Platinum,Inactive,Marketing,2023-03-13,Inactive,Manager,IT,SubSL_3,Canada,New York,TAX01,Business,2023-07-02 +25745,9572,Silver,Active,Marketing,2022-11-03,Inactive,Manager,Consulting,SubSL_1,USA,Toronto,TAX01,Business,2023-03-06 +42140,2484,Gold,Active,Data Strategy,2023-05-04,Inactive,Director,IT,SubSL_1,UK,London,DS02,Technology,2023-09-11 +47305,2005,Gold,Inactive,IT,2023-06-13,Active,Manager,IT,SubSL_3,USA,Los Angeles,BI002,,2023-03-16 +66405,1104,Silver,Inactive,Data Strategy,2022-10-15,Active,Director,RMS,SubSL_3,USA,Los Angeles,DS02,,2023-03-16 +34921,4431,Silver,Inactive,Finance,2023-02-17,Active,Manager,Audit,SubSL_3,UK,Los Angeles,AI001,Business,2022-12-25 +41361,3010,Bronze,Inactive,IT,2023-08-05,Inactive,Director,TAX,SubSL_1,Canada,London,BI002,Technology,2023-07-10 +64164,6415,Silver,Inactive,HR,2023-02-07,Active,Manager,Consulting,SubSL_3,Canada,London,AI001,Business,2022-11-24 +62139,7908,Platinum,Inactive,IT,2023-03-09,Inactive,Supervisor,IT,SubSL_1,USA,London,DS02,,2022-11-19 +67106,2369,Bronze,Active,Finance,2023-08-30,Inactive,Supervisor,TAX,SubSL_3,UK,Los Angeles,TAX01,Business,2023-07-24 +60631,1441,Bronze,Inactive,Marketing,2023-02-21,Inactive,Manager,Audit,SubSL_2,USA,Toronto,AI001,Leadership,2022-09-25 +70903,4417,Gold,Inactive,Finance,2023-01-28,Active,Employee,Audit,SubSL_3,UK,Los Angeles,AI001,Business,2023-08-22 +58002,7893,Silver,Active,Data Strategy,2023-08-22,Inactive,Supervisor,RMS,SubSL_1,Canada,Los Angeles,BI002,,2023-05-21 +94935,3702,Silver,Active,Marketing,2022-09-19,Active,Manager,Audit,SubSL_2,UK,London,AI001,Business,2023-03-22 +33910,6136,Platinum,Active,IT,2023-09-02,Active,Supervisor,RMS,SubSL_3,USA,Los Angeles,BI002,,2022-12-31 +75657,1379,Gold,Inactive,Finance,2023-06-28,Inactive,Director,Consulting,SubSL_1,UK,London,AI001,Technology,2023-08-31 +32249,9287,Bronze,Active,Data Strategy,2023-01-03,Inactive,Manager,IT,SubSL_2,UK,London,DS02,Leadership,2023-09-16 +64664,9556,Silver,Active,Data Strategy,2023-08-16,Inactive,Director,Consulting,SubSL_3,Canada,New York,DS02,Leadership,2022-12-02 +33937,8278,Silver,Inactive,Marketing,2022-10-21,Active,Supervisor,RMS,SubSL_1,Canada,New York,BI002,,2023-03-18 +37259,6949,Bronze,Active,IT,2023-04-13,Inactive,Employee,TAX,SubSL_2,UK,London,TAX01,Technology,2023-01-16 +14574,3373,Gold,Inactive,Marketing,2023-01-31,Active,Supervisor,TAX,SubSL_2,UK,Los Angeles,AI001,Leadership,2023-09-09 +99607,7619,Platinum,Inactive,HR,2023-03-23,Active,Manager,TAX,SubSL_2,UK,London,AI001,Leadership,2022-11-27 +30263,6124,Silver,Active,Marketing,2023-06-14,Inactive,Supervisor,IT,SubSL_1,Canada,Los Angeles,AI001,Leadership,2023-05-27 +55985,7400,Bronze,Active,IT,2023-05-12,Active,Manager,Consulting,SubSL_1,Canada,Los Angeles,DS02,,2023-04-11 +28641,3047,Silver,Active,Marketing,2023-03-05,Active,Manager,IT,SubSL_2,UK,Toronto,DS02,Business,2022-11-01 +40658,3885,Gold,Active,IT,2023-07-03,Inactive,Director,IT,SubSL_1,Canada,New York,DS02,Business,2023-05-06 +70383,1923,Bronze,Inactive,Marketing,2023-08-06,Inactive,Director,IT,SubSL_1,UK,London,AI001,,2023-04-19 +60811,1191,Platinum,Inactive,Finance,2023-04-03,Active,Supervisor,Audit,SubSL_2,UK,Los Angeles,BI002,Leadership,2022-12-13 +47208,6136,Platinum,Active,Data Strategy,2023-04-10,Inactive,Manager,IT,SubSL_3,UK,London,DS02,Technology,2023-06-21 +59960,7884,Platinum,Active,Marketing,2023-03-11,Inactive,Manager,Audit,SubSL_3,USA,New York,TAX01,,2023-08-30 +24104,4491,Silver,Active,Data Strategy,2023-08-15,Inactive,Employee,IT,SubSL_1,Canada,New York,DS02,Leadership,2023-04-28 +36667,6875,Bronze,Active,IT,2023-06-30,Active,Employee,IT,SubSL_1,USA,London,BI002,Leadership,2023-01-17 +72744,1845,Platinum,Inactive,IT,2022-12-20,Active,Manager,IT,SubSL_3,Canada,New York,TAX01,,2023-08-30 +96446,8191,Silver,Inactive,HR,2023-03-14,Active,Employee,IT,SubSL_3,UK,Los Angeles,TAX01,,2023-01-12 +84961,1000,Silver,Active,Data Strategy,2022-10-01,Inactive,Supervisor,Audit,SubSL_3,UK,Toronto,TAX01,Leadership,2023-02-27 +68166,9893,Platinum,Active,Finance,2022-12-06,Active,Director,Consulting,SubSL_3,UK,New York,DS02,Technology,2023-04-01 +27834,8881,Bronze,Inactive,Data Strategy,2023-06-27,Inactive,Manager,TAX,SubSL_2,UK,London,BI002,,2023-01-11 +71885,4282,Bronze,Inactive,Marketing,2023-09-01,Active,Manager,IT,SubSL_1,Canada,New York,TAX01,Technology,2022-12-19 +22170,4737,Gold,Active,HR,2023-01-11,Active,Supervisor,Audit,SubSL_1,UK,New York,AI001,Technology,2022-11-23 +74894,9336,Silver,Inactive,Marketing,2023-06-19,Inactive,Director,TAX,SubSL_2,Canada,Toronto,AI001,Business,2022-09-30 +53126,1485,Platinum,Active,Marketing,2023-02-14,Inactive,Supervisor,Audit,SubSL_3,USA,Los Angeles,BI002,,2023-07-04 +18114,8917,Silver,Inactive,HR,2022-11-27,Inactive,Director,Consulting,SubSL_3,USA,Los Angeles,DS02,Business,2023-03-01 +39751,7382,Silver,Active,HR,2022-11-18,Inactive,Employee,IT,SubSL_2,UK,London,AI001,Technology,2023-04-14 +74281,1714,Bronze,Inactive,Data Strategy,2023-07-18,Active,Supervisor,TAX,SubSL_1,USA,New York,AI001,Technology,2023-04-27 +77130,9251,Platinum,Active,HR,2023-03-04,Active,Employee,IT,SubSL_3,Canada,New York,DS02,Technology,2023-08-31 +51064,6939,Platinum,Active,Data Strategy,2023-07-01,Active,Director,Consulting,SubSL_3,Canada,Toronto,DS02,Leadership,2023-03-28 +96488,9605,Gold,Inactive,IT,2023-05-16,Active,Supervisor,Audit,SubSL_3,USA,New York,BI002,Leadership,2023-08-08 +19255,6959,Gold,Active,HR,2023-03-29,Active,Director,TAX,SubSL_3,UK,New York,AI001,Technology,2022-11-29 +82951,6558,Bronze,Inactive,IT,2022-12-14,Active,Supervisor,Audit,SubSL_2,USA,Toronto,BI002,Technology,2022-09-28 +80409,7561,Platinum,Inactive,Marketing,2023-01-16,Active,Director,IT,SubSL_3,UK,Los Angeles,BI002,Leadership,2022-10-21 +93492,2495,Bronze,Inactive,HR,2023-07-22,Inactive,Supervisor,RMS,SubSL_2,UK,Los Angeles,TAX01,Leadership,2023-02-07 +68960,9543,Platinum,Inactive,IT,2023-05-24,Active,Manager,TAX,SubSL_1,Canada,Los Angeles,AI001,Business,2023-06-11 +75967,9153,Platinum,Active,HR,2022-10-24,Inactive,Director,RMS,SubSL_3,Canada,Toronto,BI002,Technology,2023-01-16 +14054,1337,Gold,Inactive,Finance,2022-09-23,Inactive,Director,TAX,SubSL_3,USA,Los Angeles,DS02,Technology,2022-10-07 +44072,3054,Silver,Active,Finance,2023-06-14,Inactive,Supervisor,Audit,SubSL_3,UK,New York,BI002,,2023-07-22 +96524,7013,Platinum,Inactive,Data Strategy,2023-04-20,Inactive,Employee,RMS,SubSL_2,USA,Los Angeles,DS02,Business,2022-12-17 +73972,5168,Platinum,Inactive,Marketing,2022-12-14,Active,Supervisor,RMS,SubSL_3,UK,London,AI001,Business,2023-04-13 +38480,7787,Bronze,Inactive,Data Strategy,2023-02-28,Inactive,Supervisor,TAX,SubSL_2,Canada,Toronto,TAX01,Business,2023-02-22 +54719,5008,Silver,Inactive,IT,2022-10-06,Inactive,Manager,Audit,SubSL_2,USA,London,DS02,Technology,2023-07-21 +11183,4098,Platinum,Inactive,IT,2022-11-16,Active,Director,RMS,SubSL_2,UK,Los Angeles,TAX01,Leadership,2022-10-04 +62030,7524,Silver,Inactive,Marketing,2023-05-13,Active,Manager,RMS,SubSL_2,Canada,New York,DS02,Leadership,2022-12-02 +91167,6950,Bronze,Inactive,Marketing,2023-08-02,Active,Employee,TAX,SubSL_1,UK,London,BI002,Technology,2022-11-25 +91847,8214,Silver,Active,Marketing,2023-02-24,Active,Employee,Consulting,SubSL_3,USA,Los Angeles,TAX01,,2022-10-07 +12239,1652,Gold,Inactive,Data Strategy,2023-04-30,Active,Employee,IT,SubSL_1,UK,Toronto,DS02,Technology,2023-05-24 +67797,9244,Silver,Inactive,IT,2023-08-15,Inactive,Director,TAX,SubSL_2,Canada,London,BI002,Technology,2023-05-12 +35502,5832,Gold,Active,HR,2023-06-07,Active,Supervisor,RMS,SubSL_2,USA,Los Angeles,TAX01,Business,2023-01-02 +19785,3409,Platinum,Active,Data Strategy,2022-10-27,Active,Employee,Audit,SubSL_2,Canada,New York,AI001,Technology,2023-02-05 +50420,7904,Platinum,Active,Marketing,2023-01-23,Active,Manager,IT,SubSL_1,Canada,New York,DS02,Technology,2023-07-26 +12309,8186,Platinum,Active,Data Strategy,2023-05-30,Active,Supervisor,RMS,SubSL_1,UK,Toronto,TAX01,Technology,2022-11-14 +63359,9817,Bronze,Active,HR,2023-05-27,Inactive,Manager,Audit,SubSL_1,UK,Toronto,DS02,Leadership,2023-04-10 +96997,1619,Platinum,Active,Marketing,2022-12-31,Active,Director,RMS,SubSL_2,UK,London,BI002,Technology,2023-04-30 +69502,1447,Bronze,Active,IT,2022-09-30,Inactive,Employee,Consulting,SubSL_2,Canada,New York,AI001,Technology,2022-10-28 +71407,5478,Platinum,Inactive,HR,2023-05-08,Active,Supervisor,IT,SubSL_2,Canada,Los Angeles,TAX01,Technology,2023-07-25 +85252,6301,Gold,Inactive,HR,2023-04-02,Active,Director,IT,SubSL_1,USA,New York,BI002,Technology,2023-07-19 +87887,8493,Silver,Active,HR,2023-03-24,Inactive,Supervisor,Consulting,SubSL_1,USA,Toronto,AI001,Business,2022-09-20 +54211,1777,Platinum,Active,Finance,2023-06-21,Active,Supervisor,RMS,SubSL_3,USA,London,DS02,Business,2023-05-23 +51473,1002,Bronze,Active,Data Strategy,2023-07-21,Inactive,Manager,Audit,SubSL_1,UK,New York,TAX01,Business,2023-05-13 +98301,3456,Silver,Active,Data Strategy,2022-09-25,Inactive,Employee,RMS,SubSL_3,USA,London,DS02,Business,2023-04-12 +93288,1884,Platinum,Active,Data Strategy,2023-05-08,Inactive,Supervisor,Consulting,SubSL_3,Canada,New York,BI002,,2023-04-17 +14063,1344,Gold,Inactive,Marketing,2023-01-04,Active,Manager,RMS,SubSL_2,UK,New York,AI001,Leadership,2023-07-21 +51945,3236,Platinum,Active,Finance,2023-02-16,Inactive,Manager,RMS,SubSL_2,USA,London,BI002,Leadership,2023-05-29 +42557,1283,Gold,Inactive,HR,2023-07-28,Active,Director,Consulting,SubSL_3,Canada,Los Angeles,DS02,,2023-03-22 +74821,7479,Gold,Inactive,Marketing,2023-04-18,Active,Employee,TAX,SubSL_2,Canada,London,DS02,Leadership,2023-04-04 +83162,6967,Platinum,Active,HR,2023-04-02,Active,Director,Audit,SubSL_2,Canada,Los Angeles,BI002,Leadership,2023-01-06 +78389,1850,Gold,Active,Data Strategy,2023-08-01,Inactive,Director,IT,SubSL_2,Canada,Toronto,TAX01,Leadership,2023-05-05 +82811,1589,Gold,Inactive,Finance,2023-08-23,Active,Supervisor,RMS,SubSL_3,UK,New York,BI002,Leadership,2022-12-15 +19372,6273,Platinum,Inactive,Data Strategy,2023-09-08,Inactive,Manager,IT,SubSL_2,USA,Los Angeles,BI002,,2023-08-04 +41089,4048,Platinum,Active,Data Strategy,2023-03-02,Inactive,Director,RMS,SubSL_2,Canada,New York,TAX01,Technology,2023-06-03 +12570,9843,Gold,Active,Marketing,2023-01-18,Inactive,Director,TAX,SubSL_2,UK,London,AI001,,2023-08-26 +38406,3624,Silver,Inactive,Marketing,2022-11-21,Inactive,Employee,RMS,SubSL_2,USA,Toronto,BI002,Technology,2023-06-13 +70797,1767,Platinum,Inactive,Marketing,2022-10-13,Inactive,Director,Audit,SubSL_2,USA,London,TAX01,Leadership,2023-09-16 +84318,1708,Bronze,Active,Data Strategy,2023-06-22,Active,Employee,IT,SubSL_1,USA,London,DS02,Business,2023-01-03 +25052,9748,Gold,Active,HR,2023-06-27,Inactive,Director,TAX,SubSL_1,Canada,New York,BI002,Leadership,2022-12-08 +73490,8490,Platinum,Inactive,HR,2023-06-14,Active,Director,Audit,SubSL_1,Canada,London,AI001,,2022-10-09 +65954,1800,Silver,Inactive,Finance,2023-07-17,Inactive,Supervisor,RMS,SubSL_2,USA,London,BI002,Business,2023-08-13 +46958,3682,Silver,Active,HR,2022-11-18,Inactive,Manager,Audit,SubSL_3,USA,New York,TAX01,,2023-08-15 +58925,3297,Platinum,Active,HR,2023-08-21,Active,Employee,RMS,SubSL_1,USA,New York,DS02,Business,2023-07-10 +86782,5678,Gold,Active,IT,2022-12-22,Active,Director,IT,SubSL_2,USA,New York,DS02,Technology,2023-07-07 +16408,8344,Silver,Active,IT,2022-12-23,Active,Manager,Audit,SubSL_2,UK,Los Angeles,AI001,Business,2022-11-07 +69012,3136,Bronze,Inactive,Finance,2023-08-24,Inactive,Director,Consulting,SubSL_3,UK,Los Angeles,TAX01,,2022-12-17 +58853,8344,Silver,Active,HR,2023-01-18,Active,Supervisor,Consulting,SubSL_2,Canada,New York,BI002,,2023-04-29 +59232,9770,Gold,Inactive,Data Strategy,2023-04-04,Inactive,Employee,IT,SubSL_1,UK,Los Angeles,DS02,Leadership,2023-05-25 +35168,3103,Bronze,Inactive,Data Strategy,2023-05-24,Active,Supervisor,Consulting,SubSL_1,Canada,Toronto,TAX01,Leadership,2023-06-18 +73674,8881,Bronze,Inactive,Finance,2022-11-19,Inactive,Director,RMS,SubSL_3,UK,New York,DS02,,2023-05-12 +87317,5937,Silver,Active,Marketing,2023-06-30,Active,Director,IT,SubSL_3,USA,Los Angeles,BI002,Leadership,2022-10-25 +30808,1973,Platinum,Active,IT,2023-03-18,Inactive,Manager,RMS,SubSL_1,UK,Toronto,DS02,Technology,2023-05-23 +50111,1413,Bronze,Inactive,Finance,2023-09-08,Inactive,Supervisor,Audit,SubSL_3,USA,Toronto,AI001,,2023-04-05 +62290,3138,Bronze,Inactive,Marketing,2023-02-25,Inactive,Director,RMS,SubSL_1,USA,London,AI001,,2023-01-17 +18168,1706,Bronze,Active,IT,2023-04-17,Inactive,Employee,TAX,SubSL_2,Canada,New York,DS02,Technology,2022-09-22 +32784,7020,Bronze,Inactive,Marketing,2023-06-27,Active,Director,Audit,SubSL_3,Canada,Toronto,BI002,Business,2023-04-26 +96077,5313,Gold,Active,IT,2022-09-23,Active,Manager,Consulting,SubSL_3,Canada,London,DS02,Business,2023-09-09 +77265,1252,Bronze,Inactive,Marketing,2023-05-13,Inactive,Manager,Consulting,SubSL_3,Canada,London,BI002,Leadership,2023-02-22 +34370,9678,Gold,Active,Data Strategy,2023-02-24,Active,Supervisor,Audit,SubSL_2,Canada,London,TAX01,Business,2023-04-27 +46132,2961,Silver,Active,Marketing,2023-09-18,Inactive,Director,Consulting,SubSL_2,USA,New York,DS02,,2022-11-06 +59616,8523,Silver,Inactive,IT,2023-04-04,Active,Director,Audit,SubSL_1,UK,Toronto,BI002,,2023-04-13 +82509,8103,Bronze,Inactive,Data Strategy,2023-03-18,Inactive,Employee,Audit,SubSL_2,UK,Toronto,BI002,,2022-12-31 +65191,3115,Bronze,Inactive,Marketing,2023-07-07,Active,Supervisor,RMS,SubSL_2,Canada,New York,BI002,Leadership,2023-03-08 +84121,9483,Platinum,Inactive,Marketing,2023-08-03,Active,Employee,TAX,SubSL_2,USA,Toronto,AI001,Business,2023-06-28 +44649,3606,Gold,Active,Finance,2023-02-27,Active,Employee,Audit,SubSL_2,UK,New York,DS02,Business,2023-01-21 +33904,8715,Bronze,Active,HR,2023-05-20,Active,Supervisor,Consulting,SubSL_3,UK,Los Angeles,TAX01,Technology,2022-11-20 +22390,7279,Bronze,Inactive,IT,2023-03-07,Inactive,Employee,Consulting,SubSL_2,USA,Toronto,DS02,Business,2023-01-07 +63283,4352,Gold,Inactive,Data Strategy,2023-01-11,Inactive,Director,TAX,SubSL_1,UK,New York,DS02,,2023-02-25 +23931,3825,Gold,Inactive,Marketing,2023-05-24,Active,Supervisor,TAX,SubSL_1,UK,New York,TAX01,,2023-06-22 +14707,3833,Gold,Active,HR,2023-07-18,Inactive,Employee,RMS,SubSL_2,UK,Los Angeles,TAX01,Business,2023-04-14 +57117,9090,Silver,Inactive,IT,2023-01-31,Active,Supervisor,TAX,SubSL_2,USA,Toronto,AI001,,2023-03-11 +47451,6422,Gold,Active,HR,2023-07-02,Active,Manager,Audit,SubSL_1,USA,Los Angeles,BI002,,2023-07-14 +32322,6975,Bronze,Active,Data Strategy,2023-06-20,Inactive,Employee,Audit,SubSL_3,Canada,Los Angeles,DS02,Leadership,2023-06-06 +90490,9920,Silver,Inactive,Data Strategy,2023-03-05,Inactive,Manager,RMS,SubSL_1,UK,Los Angeles,TAX01,Technology,2023-01-10 +97078,5411,Gold,Active,Marketing,2023-01-27,Inactive,Supervisor,RMS,SubSL_2,Canada,Los Angeles,TAX01,Technology,2023-07-23 +27909,9330,Platinum,Active,Data Strategy,2023-06-22,Active,Supervisor,TAX,SubSL_3,USA,Toronto,TAX01,,2023-08-17 +39446,5327,Platinum,Active,Data Strategy,2023-03-03,Inactive,Manager,IT,SubSL_3,USA,Toronto,TAX01,Leadership,2022-12-29 +47255,8153,Gold,Inactive,HR,2023-05-07,Inactive,Employee,IT,SubSL_2,Canada,Los Angeles,DS02,Technology,2022-09-26 +23595,3636,Gold,Inactive,Data Strategy,2023-02-08,Active,Director,RMS,SubSL_1,UK,Los Angeles,BI002,Business,2023-03-10 +86493,8436,Platinum,Inactive,Marketing,2022-11-14,Inactive,Manager,RMS,SubSL_2,USA,London,AI001,Business,2023-07-18 +63963,2669,Gold,Active,IT,2023-05-10,Active,Director,RMS,SubSL_2,Canada,Los Angeles,DS02,Business,2023-03-09 +93403,6053,Platinum,Active,Marketing,2023-07-11,Inactive,Supervisor,IT,SubSL_1,Canada,New York,TAX01,,2023-07-09 +55046,3642,Silver,Active,Finance,2022-12-21,Active,Manager,Audit,SubSL_2,UK,New York,AI001,Technology,2023-04-23 +50992,7303,Gold,Active,HR,2022-12-14,Active,Manager,Audit,SubSL_3,UK,Los Angeles,BI002,Technology,2022-12-04 +38859,1614,Silver,Inactive,Marketing,2023-01-01,Inactive,Director,Consulting,SubSL_2,USA,Toronto,BI002,Technology,2022-10-17 +16455,6783,Gold,Active,Marketing,2023-08-03,Active,Director,TAX,SubSL_3,USA,New York,AI001,Business,2022-12-14 +19543,6776,Silver,Active,Finance,2023-03-03,Inactive,Supervisor,Consulting,SubSL_2,UK,London,BI002,Business,2023-06-04 +97334,4239,Gold,Inactive,Data Strategy,2022-11-05,Inactive,Manager,RMS,SubSL_2,UK,Toronto,BI002,Business,2023-08-15 +85404,3658,Gold,Active,Finance,2023-02-03,Inactive,Director,IT,SubSL_1,Canada,New York,TAX01,Business,2023-08-01 +76083,7176,Platinum,Inactive,Data Strategy,2022-10-12,Inactive,Director,RMS,SubSL_1,UK,London,DS02,Leadership,2022-09-20 +18548,2619,Bronze,Active,Data Strategy,2022-12-15,Inactive,Supervisor,Audit,SubSL_1,USA,Los Angeles,AI001,Leadership,2023-03-19 +10264,1239,Platinum,Active,HR,2022-12-19,Inactive,Manager,Consulting,SubSL_3,USA,Toronto,DS02,Technology,2023-07-18 +68827,6382,Silver,Active,Finance,2022-10-20,Active,Manager,Consulting,SubSL_2,UK,London,AI001,,2022-10-19 +22544,9890,Platinum,Active,HR,2022-10-14,Inactive,Manager,IT,SubSL_3,UK,Toronto,DS02,Leadership,2023-08-26 +82100,5863,Silver,Active,Marketing,2022-12-31,Inactive,Supervisor,RMS,SubSL_2,USA,Toronto,BI002,Technology,2022-12-20 +58122,7611,Silver,Inactive,IT,2023-02-27,Inactive,Supervisor,Audit,SubSL_3,UK,Los Angeles,BI002,Technology,2023-04-10 +99689,6285,Gold,Active,HR,2022-12-05,Inactive,Supervisor,IT,SubSL_2,Canada,Los Angeles,DS02,Leadership,2022-12-14 +46322,9541,Platinum,Inactive,Marketing,2022-12-06,Active,Manager,Audit,SubSL_1,USA,Toronto,TAX01,Technology,2023-06-27 +72391,8753,Platinum,Active,HR,2022-12-05,Active,Director,RMS,SubSL_2,UK,London,TAX01,,2023-02-26 +49640,3081,Silver,Inactive,Finance,2022-11-29,Active,Manager,Audit,SubSL_1,Canada,Toronto,AI001,Technology,2022-10-06 +27396,4952,Gold,Active,Data Strategy,2023-07-01,Inactive,Manager,IT,SubSL_1,USA,New York,DS02,Business,2022-11-15 +69036,8348,Bronze,Active,HR,2023-05-25,Active,Director,TAX,SubSL_1,USA,London,DS02,Business,2023-09-03 +70873,8969,Gold,Active,IT,2023-08-14,Inactive,Manager,Consulting,SubSL_3,USA,Toronto,AI001,Technology,2023-06-06 +46028,9771,Bronze,Active,IT,2022-11-26,Inactive,Manager,RMS,SubSL_3,USA,London,BI002,,2023-08-08 +21090,7883,Gold,Active,HR,2023-05-06,Inactive,Employee,TAX,SubSL_1,UK,New York,AI001,Leadership,2023-05-09 +89055,8235,Platinum,Active,Finance,2022-10-30,Inactive,Director,Consulting,SubSL_1,Canada,London,TAX01,Business,2023-03-10 +14887,1882,Gold,Active,Data Strategy,2023-05-08,Inactive,Director,TAX,SubSL_1,USA,Toronto,TAX01,Leadership,2022-11-26 +67876,1028,Silver,Active,Data Strategy,2023-06-16,Inactive,Supervisor,TAX,SubSL_2,Canada,London,AI001,,2023-08-24 +47996,7074,Platinum,Active,Marketing,2022-09-24,Inactive,Supervisor,Audit,SubSL_1,UK,New York,DS02,,2023-07-09 +45216,1405,Platinum,Active,Data Strategy,2023-03-29,Inactive,Manager,Audit,SubSL_3,UK,New York,BI002,,2022-10-24 +44965,3401,Platinum,Active,HR,2022-12-12,Inactive,Supervisor,Consulting,SubSL_2,UK,Toronto,AI001,Leadership,2022-10-21 +86658,9258,Gold,Inactive,Data Strategy,2023-01-22,Inactive,Manager,IT,SubSL_2,USA,New York,TAX01,Technology,2022-11-18 +51654,5348,Gold,Inactive,Marketing,2023-05-02,Active,Supervisor,RMS,SubSL_1,USA,Los Angeles,DS02,,2023-08-03 +66822,4711,Platinum,Active,IT,2023-03-12,Inactive,Director,Audit,SubSL_2,Canada,Los Angeles,BI002,Business,2023-03-07 +61484,5079,Silver,Inactive,Data Strategy,2022-09-19,Active,Supervisor,Audit,SubSL_3,USA,Toronto,AI001,,2023-02-12 +71723,7775,Silver,Inactive,IT,2022-09-27,Inactive,Manager,RMS,SubSL_1,UK,Toronto,AI001,Leadership,2022-11-16 +90108,9602,Platinum,Active,Finance,2023-03-23,Active,Supervisor,RMS,SubSL_2,USA,New York,DS02,Business,2023-08-14 +33813,9654,Platinum,Active,Marketing,2022-11-04,Active,Director,Audit,SubSL_1,Canada,Toronto,AI001,Technology,2023-04-22 +21906,2040,Silver,Active,Data Strategy,2023-05-21,Inactive,Manager,RMS,SubSL_1,Canada,Los Angeles,TAX01,Leadership,2022-10-22 +56992,2547,Silver,Inactive,HR,2022-11-08,Active,Director,TAX,SubSL_1,UK,Toronto,AI001,,2023-02-25 +74578,7191,Gold,Inactive,Finance,2023-06-16,Inactive,Employee,RMS,SubSL_3,USA,Los Angeles,TAX01,Leadership,2023-07-08 +78876,2720,Platinum,Inactive,Finance,2023-08-19,Inactive,Manager,RMS,SubSL_3,Canada,New York,BI002,,2023-03-02 +49949,4743,Gold,Inactive,HR,2023-03-03,Active,Director,Audit,SubSL_3,UK,Toronto,TAX01,Leadership,2022-10-28 +13712,3164,Bronze,Inactive,Marketing,2023-02-13,Inactive,Manager,IT,SubSL_1,USA,London,DS02,Leadership,2022-09-29 +26895,6744,Platinum,Active,IT,2022-10-17,Active,Supervisor,Audit,SubSL_1,UK,Toronto,DS02,,2022-12-01 +52976,2569,Silver,Inactive,HR,2022-12-18,Active,Manager,IT,SubSL_1,UK,Los Angeles,AI001,Leadership,2023-09-05 +36764,3718,Bronze,Inactive,HR,2023-03-06,Active,Manager,TAX,SubSL_2,Canada,New York,TAX01,Technology,2023-05-26 +32351,7192,Platinum,Inactive,IT,2023-03-31,Inactive,Director,Consulting,SubSL_2,UK,Toronto,TAX01,Technology,2023-04-17 +44339,6552,Bronze,Inactive,Finance,2023-03-16,Inactive,Employee,IT,SubSL_1,Canada,Toronto,BI002,,2023-05-06 +51803,2865,Platinum,Inactive,HR,2023-03-11,Active,Supervisor,IT,SubSL_1,USA,Toronto,DS02,Business,2023-03-21 +45727,7293,Platinum,Active,Data Strategy,2023-07-28,Active,Supervisor,Audit,SubSL_2,Canada,Toronto,BI002,Leadership,2023-05-21 +90630,3451,Gold,Active,Finance,2023-03-29,Active,Manager,TAX,SubSL_2,Canada,Los Angeles,BI002,Business,2022-11-04 +31424,5275,Bronze,Active,Data Strategy,2023-03-25,Inactive,Director,IT,SubSL_2,Canada,New York,AI001,,2023-08-14 +17143,1799,Bronze,Inactive,HR,2023-02-01,Active,Director,Consulting,SubSL_1,USA,London,DS02,,2023-09-08 +71966,2452,Bronze,Active,Finance,2023-05-02,Inactive,Supervisor,Consulting,SubSL_1,USA,Los Angeles,BI002,Business,2023-03-29 +34903,7448,Gold,Inactive,Data Strategy,2022-10-08,Inactive,Supervisor,Consulting,SubSL_1,USA,Los Angeles,DS02,,2023-04-01 +77133,3950,Gold,Inactive,Marketing,2022-12-24,Active,Supervisor,Consulting,SubSL_2,UK,New York,DS02,Business,2023-04-16 +15908,5161,Platinum,Active,Finance,2023-05-21,Active,Employee,RMS,SubSL_1,USA,Los Angeles,AI001,Business,2022-10-12 +50935,2636,Gold,Active,Finance,2023-01-28,Inactive,Employee,IT,SubSL_1,Canada,London,DS02,,2023-02-09 +45107,9530,Silver,Inactive,Marketing,2023-05-01,Active,Director,Audit,SubSL_2,UK,London,AI001,Business,2023-02-27 +53431,2261,Platinum,Active,IT,2022-10-25,Inactive,Manager,Consulting,SubSL_1,USA,New York,TAX01,Business,2023-08-16 +32121,6417,Bronze,Active,Marketing,2023-03-15,Inactive,Director,Consulting,SubSL_1,Canada,Los Angeles,AI001,Technology,2022-12-24 +31780,5029,Gold,Inactive,Data Strategy,2023-01-24,Inactive,Supervisor,TAX,SubSL_2,Canada,Toronto,TAX01,Leadership,2023-05-16 +62858,5513,Silver,Active,Marketing,2022-10-17,Inactive,Director,TAX,SubSL_3,USA,Toronto,DS02,,2022-11-09 +76178,3535,Gold,Active,HR,2023-02-08,Active,Supervisor,RMS,SubSL_1,USA,Toronto,TAX01,Business,2023-02-01 +45479,3001,Bronze,Active,HR,2022-10-21,Inactive,Director,Consulting,SubSL_2,Canada,Los Angeles,BI002,Technology,2023-05-05 +62318,3999,Bronze,Inactive,Finance,2023-02-21,Inactive,Employee,Audit,SubSL_3,USA,London,DS02,Leadership,2023-09-19 +59196,5971,Gold,Inactive,Data Strategy,2022-12-01,Inactive,Employee,IT,SubSL_1,Canada,Los Angeles,AI001,Technology,2023-03-10 +19766,2733,Gold,Active,HR,2023-01-28,Active,Supervisor,Consulting,SubSL_1,Canada,London,AI001,,2023-02-17 +26555,8354,Bronze,Active,IT,2023-04-12,Active,Employee,Consulting,SubSL_3,USA,Toronto,TAX01,Technology,2023-04-15 +42926,9305,Gold,Inactive,Finance,2023-08-08,Inactive,Supervisor,Consulting,SubSL_3,Canada,London,TAX01,Technology,2023-05-29 +19011,4133,Platinum,Inactive,Finance,2023-09-02,Active,Supervisor,IT,SubSL_2,UK,Toronto,AI001,Technology,2022-10-26 +40950,4652,Bronze,Inactive,IT,2023-05-28,Inactive,Director,Consulting,SubSL_2,Canada,New York,TAX01,,2022-11-28 +39671,1923,Bronze,Active,HR,2023-03-05,Active,Supervisor,IT,SubSL_3,USA,Toronto,AI001,Leadership,2023-01-15 +48407,6241,Platinum,Inactive,Marketing,2023-07-07,Active,Manager,Consulting,SubSL_2,UK,Los Angeles,TAX01,Leadership,2023-05-11 +19222,4629,Silver,Active,Marketing,2023-05-21,Active,Manager,Consulting,SubSL_1,Canada,London,DS02,Technology,2023-05-21 +50913,2850,Bronze,Inactive,IT,2023-03-24,Inactive,Director,Consulting,SubSL_2,Canada,Los Angeles,DS02,,2023-08-26 +76267,2622,Bronze,Active,Data Strategy,2023-06-15,Active,Director,TAX,SubSL_2,USA,Toronto,TAX01,Technology,2023-01-04 +69368,8194,Bronze,Active,HR,2023-04-19,Inactive,Director,Consulting,SubSL_2,USA,Los Angeles,TAX01,Leadership,2022-12-07 +65119,3663,Platinum,Active,Data Strategy,2022-12-05,Inactive,Manager,Consulting,SubSL_2,Canada,Los Angeles,DS02,Leadership,2023-07-06 +82655,6959,Platinum,Inactive,Finance,2023-04-16,Active,Director,RMS,SubSL_1,UK,London,DS02,,2023-03-08 +17177,5805,Gold,Active,IT,2023-07-27,Inactive,Manager,TAX,SubSL_1,USA,Toronto,BI002,,2022-10-05 +60136,4361,Bronze,Active,Marketing,2023-04-17,Active,Manager,Consulting,SubSL_3,Canada,Los Angeles,AI001,,2023-05-03 +94377,5271,Bronze,Active,Finance,2023-01-31,Active,Director,Consulting,SubSL_2,UK,London,BI002,Leadership,2023-03-13 +17605,1093,Silver,Active,IT,2023-04-01,Active,Employee,TAX,SubSL_2,USA,Toronto,BI002,Leadership,2023-03-18 +73264,8482,Bronze,Inactive,Marketing,2023-09-16,Active,Director,Consulting,SubSL_3,USA,Los Angeles,BI002,Technology,2023-06-30 +14663,6237,Platinum,Active,IT,2023-05-13,Active,Supervisor,TAX,SubSL_3,Canada,Los Angeles,AI001,Leadership,2023-08-26 +33771,3436,Silver,Inactive,Finance,2023-03-02,Active,Supervisor,Audit,SubSL_1,Canada,New York,TAX01,Leadership,2023-07-28 +21415,8300,Platinum,Active,HR,2023-01-28,Inactive,Director,Consulting,SubSL_3,Canada,Los Angeles,DS02,,2022-10-07 +88531,4778,Silver,Active,Marketing,2022-10-05,Inactive,Supervisor,TAX,SubSL_3,Canada,Los Angeles,DS02,Technology,2023-01-06 +73847,2841,Silver,Active,HR,2023-02-03,Active,Director,TAX,SubSL_2,USA,Los Angeles,AI001,Business,2023-04-09 +95927,4231,Bronze,Active,HR,2023-07-18,Inactive,Employee,TAX,SubSL_3,Canada,Los Angeles,DS02,Business,2022-11-22 +29481,6380,Platinum,Active,Data Strategy,2023-03-03,Active,Manager,Consulting,SubSL_2,Canada,Los Angeles,DS02,Business,2023-06-09 +78509,2279,Bronze,Active,Data Strategy,2022-11-19,Inactive,Manager,Audit,SubSL_3,Canada,Toronto,DS02,,2023-02-09 +71598,6907,Silver,Inactive,Finance,2023-03-27,Inactive,Employee,TAX,SubSL_1,UK,Los Angeles,BI002,Leadership,2023-01-11 +30891,9120,Platinum,Inactive,IT,2022-12-11,Active,Manager,IT,SubSL_3,Canada,London,TAX01,Technology,2023-06-17 +71705,1304,Silver,Inactive,Finance,2022-12-31,Inactive,Supervisor,Consulting,SubSL_2,UK,Toronto,AI001,,2022-10-03 +37357,8422,Silver,Active,IT,2023-03-03,Active,Supervisor,RMS,SubSL_2,UK,New York,DS02,,2023-04-09 +45811,7064,Silver,Active,IT,2023-08-17,Active,Manager,Consulting,SubSL_3,Canada,Toronto,DS02,,2023-04-19 +26754,5500,Bronze,Active,HR,2022-12-07,Active,Director,Audit,SubSL_3,UK,Los Angeles,BI002,Leadership,2023-06-01 +60938,4033,Platinum,Active,Marketing,2022-10-31,Active,Manager,Audit,SubSL_1,USA,Los Angeles,BI002,Technology,2023-05-05 +50746,4968,Bronze,Inactive,Data Strategy,2023-02-03,Inactive,Director,Consulting,SubSL_2,UK,Los Angeles,DS02,,2023-02-25 +98633,4530,Platinum,Inactive,Finance,2023-04-07,Active,Supervisor,IT,SubSL_3,UK,Toronto,TAX01,Leadership,2023-02-06 +36527,3900,Bronze,Active,IT,2023-08-29,Active,Director,Audit,SubSL_2,Canada,London,DS02,Leadership,2022-09-27 +62864,6671,Platinum,Active,IT,2023-03-07,Inactive,Supervisor,Audit,SubSL_1,UK,London,TAX01,Business,2023-04-22 +49205,7081,Gold,Inactive,Data Strategy,2023-09-12,Inactive,Employee,Consulting,SubSL_2,UK,Toronto,AI001,Business,2023-07-21 +31315,8153,Platinum,Inactive,IT,2023-08-14,Active,Director,IT,SubSL_2,UK,Toronto,TAX01,Business,2023-04-04 +40575,3591,Platinum,Inactive,Marketing,2023-01-19,Active,Employee,Consulting,SubSL_3,UK,Toronto,DS02,Technology,2023-03-26 +26839,1388,Platinum,Inactive,Marketing,2023-01-10,Inactive,Director,Consulting,SubSL_1,UK,New York,AI001,Technology,2023-07-17 +79171,4666,Silver,Active,Data Strategy,2022-11-29,Active,Employee,RMS,SubSL_3,USA,London,TAX01,Leadership,2022-11-06 +91966,9628,Bronze,Inactive,Finance,2022-12-05,Active,Supervisor,Consulting,SubSL_1,USA,London,BI002,Business,2023-09-13 +12557,2326,Silver,Inactive,Marketing,2022-10-24,Inactive,Director,TAX,SubSL_2,Canada,Toronto,BI002,Leadership,2023-08-07 +63866,3107,Platinum,Active,IT,2022-12-29,Inactive,Manager,Audit,SubSL_3,USA,Los Angeles,TAX01,,2023-09-04 +26469,3888,Silver,Active,IT,2022-11-05,Active,Manager,Consulting,SubSL_2,UK,Los Angeles,TAX01,,2023-03-17 +88276,4075,Platinum,Inactive,Finance,2022-10-04,Inactive,Manager,Audit,SubSL_2,Canada,London,AI001,Leadership,2022-11-15 +67836,8971,Silver,Active,HR,2023-01-20,Active,Supervisor,IT,SubSL_2,USA,New York,BI002,,2023-05-31 +35196,7016,Gold,Inactive,IT,2022-11-30,Active,Manager,Consulting,SubSL_2,Canada,New York,BI002,Business,2023-07-18 +26450,4970,Bronze,Inactive,Marketing,2023-01-14,Active,Supervisor,IT,SubSL_1,UK,London,BI002,Leadership,2022-11-11 +71999,3681,Gold,Inactive,Finance,2022-12-02,Inactive,Supervisor,RMS,SubSL_1,Canada,Los Angeles,DS02,Business,2023-06-22 +96934,5974,Silver,Inactive,Marketing,2022-10-10,Active,Manager,Audit,SubSL_3,UK,London,AI001,Technology,2023-09-14 +84739,4981,Silver,Active,Finance,2023-05-14,Inactive,Supervisor,Consulting,SubSL_2,USA,Toronto,AI001,Technology,2023-07-07 +62617,9674,Gold,Inactive,Data Strategy,2022-12-18,Active,Employee,TAX,SubSL_2,USA,Toronto,AI001,Technology,2023-07-14 +34375,2577,Bronze,Active,Finance,2023-03-03,Active,Manager,IT,SubSL_1,Canada,Toronto,TAX01,Leadership,2023-07-15 +13991,1413,Platinum,Inactive,HR,2023-04-08,Inactive,Supervisor,Audit,SubSL_3,USA,London,DS02,Business,2023-07-12 +98450,4380,Gold,Inactive,Finance,2022-11-27,Active,Supervisor,Audit,SubSL_1,USA,Toronto,BI002,Leadership,2023-08-01 +10430,4556,Bronze,Active,IT,2023-06-27,Inactive,Director,RMS,SubSL_2,UK,Los Angeles,DS02,Business,2023-08-21 +46928,5796,Bronze,Active,Data Strategy,2023-09-17,Active,Director,Audit,SubSL_2,UK,New York,BI002,,2023-03-22 +99730,6760,Silver,Active,HR,2023-03-21,Inactive,Director,IT,SubSL_3,Canada,London,TAX01,Business,2023-06-18 +44283,9251,Bronze,Active,IT,2022-10-21,Active,Manager,Audit,SubSL_1,USA,London,TAX01,Technology,2022-11-04 +58785,2331,Platinum,Inactive,Finance,2022-10-10,Active,Manager,Audit,SubSL_1,Canada,London,BI002,,2023-07-01 +54675,8469,Gold,Active,HR,2023-08-03,Inactive,Director,IT,SubSL_2,Canada,London,TAX01,,2022-12-16 +42065,5542,Gold,Inactive,Data Strategy,2023-05-15,Active,Employee,Audit,SubSL_3,USA,Los Angeles,AI001,Technology,2023-01-18 +49532,1739,Silver,Inactive,Marketing,2023-07-24,Inactive,Director,Audit,SubSL_1,UK,Los Angeles,DS02,Leadership,2023-05-02 +35996,6660,Silver,Active,Marketing,2023-08-03,Inactive,Manager,IT,SubSL_1,USA,Toronto,AI001,Technology,2023-04-14 +11105,8698,Platinum,Active,HR,2023-03-15,Active,Director,Consulting,SubSL_2,UK,Toronto,AI001,,2023-05-02 +38677,7799,Gold,Active,IT,2023-05-04,Inactive,Director,Audit,SubSL_1,USA,London,BI002,,2023-03-24 +33484,5774,Bronze,Active,Data Strategy,2023-09-09,Active,Manager,Audit,SubSL_3,Canada,New York,TAX01,Leadership,2023-07-22 +56278,4328,Bronze,Inactive,Data Strategy,2023-07-20,Inactive,Manager,Audit,SubSL_2,UK,New York,AI001,,2022-12-03 +62006,1703,Silver,Active,Finance,2023-01-15,Inactive,Manager,Consulting,SubSL_1,USA,Los Angeles,DS02,Technology,2023-07-14 +47074,6078,Silver,Inactive,HR,2023-02-01,Active,Employee,IT,SubSL_2,USA,London,BI002,Business,2023-07-04 +22324,2508,Gold,Inactive,Finance,2022-11-14,Active,Supervisor,Audit,SubSL_3,UK,London,AI001,Technology,2023-06-21 +64722,2572,Bronze,Active,Data Strategy,2023-07-02,Active,Manager,IT,SubSL_2,Canada,London,AI001,Technology,2023-04-05 +16241,7779,Gold,Active,HR,2022-10-13,Inactive,Director,Audit,SubSL_1,USA,London,AI001,Leadership,2022-12-24 +99134,1697,Platinum,Inactive,HR,2023-09-13,Inactive,Manager,RMS,SubSL_2,Canada,Toronto,AI001,Leadership,2022-11-27 +13152,7385,Gold,Inactive,Finance,2022-12-06,Inactive,Manager,RMS,SubSL_1,Canada,London,AI001,Technology,2023-03-25 +82496,4759,Silver,Active,HR,2023-09-08,Active,Employee,Audit,SubSL_1,Canada,New York,TAX01,,2022-10-12 +31185,8930,Platinum,Inactive,Marketing,2023-07-16,Active,Employee,RMS,SubSL_1,Canada,London,DS02,,2022-10-20 +81074,6054,Platinum,Inactive,Data Strategy,2022-11-15,Inactive,Director,Consulting,SubSL_3,Canada,New York,BI002,Business,2023-05-23 +95742,4549,Platinum,Active,Marketing,2022-09-27,Inactive,Manager,Consulting,SubSL_2,USA,Toronto,TAX01,Technology,2022-10-12 +60677,1560,Platinum,Active,Data Strategy,2023-04-14,Inactive,Supervisor,TAX,SubSL_1,UK,New York,DS02,,2022-11-11 +82156,6113,Silver,Inactive,IT,2023-07-07,Inactive,Manager,IT,SubSL_1,UK,Los Angeles,TAX01,Technology,2022-11-17 +14983,6281,Gold,Active,Finance,2023-01-03,Inactive,Employee,RMS,SubSL_3,UK,London,AI001,Technology,2023-01-01 +75869,9075,Gold,Active,IT,2023-08-29,Active,Manager,IT,SubSL_2,USA,London,DS02,Business,2023-07-05 +87345,2550,Platinum,Inactive,HR,2023-04-15,Inactive,Manager,RMS,SubSL_3,USA,New York,TAX01,Business,2023-06-15 +82003,7610,Bronze,Inactive,Marketing,2022-10-08,Active,Employee,TAX,SubSL_1,UK,New York,AI001,Business,2023-09-14 +17753,5496,Platinum,Inactive,Marketing,2023-06-09,Inactive,Employee,Consulting,SubSL_1,UK,Toronto,BI002,Technology,2023-06-26 +90715,5581,Bronze,Active,Data Strategy,2022-09-28,Inactive,Supervisor,Consulting,SubSL_3,USA,Toronto,DS02,,2023-05-22 +94597,8847,Gold,Active,Data Strategy,2023-08-18,Active,Employee,TAX,SubSL_2,Canada,Los Angeles,TAX01,Technology,2023-04-29 +88458,7968,Silver,Inactive,Finance,2023-09-08,Inactive,Manager,IT,SubSL_1,Canada,Los Angeles,DS02,,2022-11-30 +89015,3620,Gold,Active,HR,2023-07-06,Inactive,Employee,IT,SubSL_1,USA,Los Angeles,TAX01,Business,2023-02-13 +70440,4413,Silver,Inactive,Marketing,2022-11-20,Inactive,Manager,Consulting,SubSL_1,USA,Los Angeles,AI001,Leadership,2023-04-10 +95417,4870,Silver,Inactive,IT,2023-02-18,Inactive,Manager,TAX,SubSL_1,UK,London,AI001,Leadership,2022-11-20 +33125,5328,Silver,Inactive,IT,2023-03-24,Inactive,Director,RMS,SubSL_3,USA,Toronto,AI001,,2023-01-21 +38762,9943,Gold,Inactive,IT,2023-02-15,Active,Director,Audit,SubSL_3,UK,Los Angeles,TAX01,Business,2022-11-19 +24157,5111,Platinum,Active,HR,2022-12-02,Active,Manager,TAX,SubSL_1,USA,New York,DS02,Technology,2022-10-12 +62462,1230,Bronze,Inactive,Marketing,2023-01-20,Inactive,Employee,TAX,SubSL_2,USA,Los Angeles,BI002,Technology,2023-07-24 +58409,5367,Platinum,Inactive,IT,2023-07-31,Inactive,Supervisor,IT,SubSL_3,UK,Toronto,AI001,Leadership,2023-01-31 +86814,7591,Bronze,Active,Data Strategy,2022-12-01,Inactive,Supervisor,RMS,SubSL_1,Canada,Toronto,AI001,Technology,2022-10-21 +11323,7155,Platinum,Active,Finance,2023-03-02,Inactive,Manager,TAX,SubSL_2,UK,Toronto,TAX01,,2023-04-19 +62903,4978,Silver,Inactive,Finance,2022-12-31,Inactive,Director,IT,SubSL_3,UK,London,DS02,,2022-10-02 +53731,2836,Silver,Active,Finance,2022-11-23,Inactive,Supervisor,Consulting,SubSL_2,Canada,Toronto,AI001,Technology,2023-03-04 +59398,4700,Bronze,Active,IT,2023-08-04,Active,Director,Consulting,SubSL_3,UK,Los Angeles,DS02,Technology,2022-10-07 +31601,2716,Silver,Active,HR,2023-08-10,Inactive,Manager,TAX,SubSL_2,USA,Toronto,BI002,,2023-07-31 +65894,7183,Silver,Active,HR,2022-12-26,Inactive,Supervisor,TAX,SubSL_3,Canada,Los Angeles,TAX01,Technology,2023-08-04 +85866,3183,Silver,Inactive,HR,2023-01-16,Inactive,Director,RMS,SubSL_1,Canada,Toronto,AI001,Business,2022-11-06 +65049,4120,Silver,Active,HR,2023-01-14,Active,Manager,IT,SubSL_1,UK,London,BI002,Technology,2023-06-25 +82147,1507,Platinum,Inactive,Finance,2022-12-22,Active,Employee,Consulting,SubSL_3,UK,Toronto,BI002,,2023-05-24 +40227,8806,Bronze,Active,Data Strategy,2023-05-13,Active,Manager,Consulting,SubSL_2,Canada,Los Angeles,TAX01,Business,2023-01-03 +48914,1208,Platinum,Inactive,Finance,2023-04-13,Inactive,Supervisor,IT,SubSL_2,Canada,Toronto,TAX01,Technology,2023-09-07 +35865,2227,Bronze,Active,IT,2023-06-23,Inactive,Manager,IT,SubSL_2,USA,New York,DS02,Leadership,2023-01-24 +22317,1910,Silver,Active,Data Strategy,2022-10-03,Inactive,Manager,Consulting,SubSL_1,USA,New York,TAX01,Leadership,2023-07-07 +16777,3469,Silver,Inactive,Data Strategy,2023-06-14,Active,Director,TAX,SubSL_3,UK,London,AI001,Business,2023-07-30 +78100,5825,Bronze,Inactive,Finance,2023-01-30,Active,Supervisor,Audit,SubSL_1,Canada,London,BI002,,2023-07-06 +29360,4614,Silver,Inactive,Finance,2023-08-03,Active,Supervisor,RMS,SubSL_2,Canada,New York,TAX01,Leadership,2022-10-30 +93196,3466,Silver,Inactive,HR,2023-03-29,Active,Employee,Consulting,SubSL_3,UK,Los Angeles,AI001,Leadership,2023-08-03 +69769,7800,Silver,Active,Finance,2022-12-17,Active,Manager,IT,SubSL_3,USA,New York,DS02,Business,2022-12-18 +99561,9840,Bronze,Inactive,HR,2022-12-29,Active,Manager,RMS,SubSL_1,UK,New York,DS02,Business,2022-12-10 +15244,7219,Silver,Active,HR,2023-04-01,Active,Supervisor,IT,SubSL_2,USA,Los Angeles,BI002,,2022-11-04 +95144,2826,Gold,Active,Finance,2023-05-25,Active,Director,Audit,SubSL_1,UK,Toronto,BI002,Leadership,2022-10-02 +12880,7238,Gold,Active,Data Strategy,2023-08-06,Active,Employee,RMS,SubSL_3,Canada,London,AI001,,2022-12-05 +55764,4166,Bronze,Inactive,IT,2023-01-04,Inactive,Supervisor,IT,SubSL_1,USA,London,DS02,Technology,2022-10-27 +88836,2999,Gold,Inactive,IT,2023-07-28,Inactive,Director,Audit,SubSL_3,USA,New York,DS02,Business,2022-11-27 +36719,7543,Gold,Inactive,Finance,2022-10-31,Inactive,Employee,RMS,SubSL_2,USA,Toronto,DS02,,2023-06-11 +98397,1398,Silver,Inactive,IT,2023-02-02,Active,Supervisor,Consulting,SubSL_2,USA,Toronto,DS02,,2023-04-16 +86383,8764,Platinum,Active,HR,2023-08-24,Inactive,Director,RMS,SubSL_3,USA,Los Angeles,AI001,Technology,2022-10-10 +47691,4757,Platinum,Inactive,IT,2022-09-21,Inactive,Director,RMS,SubSL_2,Canada,New York,DS02,Technology,2023-07-08 +81369,9444,Gold,Active,IT,2023-09-08,Inactive,Manager,TAX,SubSL_3,UK,Toronto,AI001,Leadership,2022-11-27 +66897,3515,Gold,Active,IT,2023-09-07,Active,Director,RMS,SubSL_2,USA,Toronto,AI001,Leadership,2022-11-26 +84190,9436,Platinum,Active,IT,2022-10-23,Active,Supervisor,TAX,SubSL_1,Canada,Toronto,BI002,Leadership,2023-09-11 +92165,6415,Gold,Active,IT,2023-07-07,Inactive,Supervisor,Consulting,SubSL_1,USA,Toronto,BI002,Technology,2023-06-02 +54982,8442,Silver,Active,Marketing,2023-09-03,Inactive,Employee,IT,SubSL_2,USA,Toronto,TAX01,Leadership,2023-01-18 +89805,9655,Gold,Active,Data Strategy,2023-06-30,Inactive,Manager,Consulting,SubSL_1,UK,New York,BI002,Leadership,2022-10-21 +18960,4358,Gold,Active,Data Strategy,2023-05-08,Active,Supervisor,TAX,SubSL_2,UK,Los Angeles,BI002,,2023-07-18 +66675,4571,Platinum,Inactive,Marketing,2023-05-21,Active,Manager,Consulting,SubSL_2,UK,Los Angeles,BI002,Leadership,2022-10-22 +23966,9224,Silver,Inactive,IT,2023-06-12,Inactive,Director,Consulting,SubSL_1,USA,New York,AI001,Technology,2023-01-03 +10112,6716,Gold,Inactive,Finance,2023-01-28,Active,Supervisor,Audit,SubSL_1,USA,New York,BI002,Business,2022-11-20 +29117,7527,Silver,Active,Finance,2022-09-28,Active,Employee,IT,SubSL_3,Canada,Toronto,BI002,,2023-05-19 +85994,1974,Silver,Active,Data Strategy,2022-12-21,Active,Supervisor,RMS,SubSL_3,UK,Toronto,BI002,Business,2023-09-12 +69204,6026,Gold,Active,Finance,2023-02-23,Inactive,Employee,Consulting,SubSL_2,USA,Los Angeles,DS02,,2023-05-20 +93909,6289,Silver,Active,IT,2023-05-28,Active,Director,TAX,SubSL_2,UK,Toronto,BI002,,2023-01-19 +72821,5660,Platinum,Inactive,IT,2023-09-08,Inactive,Manager,TAX,SubSL_2,USA,London,TAX01,Leadership,2022-10-21 +28517,2497,Bronze,Inactive,HR,2023-04-03,Inactive,Director,IT,SubSL_2,Canada,Los Angeles,AI001,Technology,2023-02-16 +11584,7038,Platinum,Inactive,Finance,2023-03-14,Inactive,Manager,IT,SubSL_2,UK,Toronto,BI002,Leadership,2022-11-20 +83226,9533,Gold,Inactive,IT,2023-07-10,Inactive,Employee,IT,SubSL_2,USA,New York,BI002,Leadership,2023-04-21 +90553,6450,Bronze,Active,Marketing,2023-01-28,Active,Employee,IT,SubSL_3,USA,Toronto,TAX01,Business,2022-09-27 +33179,3089,Silver,Inactive,Data Strategy,2023-08-05,Inactive,Employee,RMS,SubSL_1,UK,Los Angeles,TAX01,Technology,2023-04-02 +75355,3537,Bronze,Active,Data Strategy,2023-01-04,Inactive,Director,IT,SubSL_1,USA,New York,BI002,,2023-08-17 +72795,4224,Bronze,Active,Finance,2023-03-18,Inactive,Manager,IT,SubSL_1,USA,Los Angeles,TAX01,Leadership,2022-10-18 +33958,9768,Bronze,Inactive,IT,2023-07-13,Inactive,Director,TAX,SubSL_2,Canada,New York,DS02,Business,2023-04-04 +32558,7007,Silver,Inactive,IT,2023-01-31,Active,Director,Audit,SubSL_1,USA,Toronto,AI001,Leadership,2023-03-15 +53865,6133,Bronze,Active,Marketing,2022-12-20,Active,Supervisor,TAX,SubSL_1,USA,London,AI001,,2023-08-27 +75063,1612,Bronze,Inactive,HR,2023-06-30,Inactive,Director,TAX,SubSL_1,UK,Los Angeles,TAX01,Leadership,2023-03-01 +79521,4117,Bronze,Inactive,Data Strategy,2023-07-27,Active,Manager,Consulting,SubSL_3,UK,New York,TAX01,Business,2023-06-20 +19289,1198,Platinum,Inactive,IT,2022-11-17,Active,Manager,TAX,SubSL_3,Canada,New York,AI001,Technology,2023-07-19 +64205,7730,Silver,Inactive,Finance,2022-11-02,Active,Director,Audit,SubSL_3,USA,Los Angeles,BI002,Business,2022-10-26 +29042,4814,Silver,Inactive,Finance,2023-08-08,Active,Employee,TAX,SubSL_1,USA,New York,AI001,Technology,2022-09-30 +98542,3978,Gold,Inactive,HR,2022-10-04,Active,Employee,Audit,SubSL_2,UK,New York,AI001,Technology,2023-04-28 +84667,6322,Platinum,Inactive,Data Strategy,2023-07-12,Active,Employee,RMS,SubSL_3,USA,Toronto,DS02,Business,2023-01-09 +15078,8182,Bronze,Active,Data Strategy,2023-07-27,Active,Supervisor,TAX,SubSL_3,Canada,Los Angeles,TAX01,,2023-08-05 +73094,2642,Silver,Inactive,HR,2023-05-10,Inactive,Employee,Consulting,SubSL_3,UK,Toronto,DS02,,2022-11-27 +53001,1443,Gold,Active,Finance,2023-08-08,Inactive,Supervisor,Audit,SubSL_1,UK,New York,AI001,,2023-01-10 +35939,1355,Silver,Inactive,HR,2023-07-23,Inactive,Employee,Consulting,SubSL_2,UK,New York,TAX01,Leadership,2023-06-03 +97218,8996,Gold,Inactive,Marketing,2022-11-11,Inactive,Director,TAX,SubSL_3,USA,Toronto,TAX01,Leadership,2023-08-19 +96058,8257,Platinum,Inactive,Finance,2023-06-01,Inactive,Director,Audit,SubSL_2,Canada,Los Angeles,AI001,,2023-09-11 +37941,8111,Bronze,Inactive,Finance,2023-06-18,Inactive,Employee,IT,SubSL_2,Canada,New York,BI002,Business,2023-06-05 +34492,6203,Bronze,Active,Data Strategy,2022-10-02,Inactive,Manager,Audit,SubSL_2,UK,Toronto,TAX01,,2023-05-20 +30901,2226,Gold,Inactive,Finance,2023-08-03,Active,Employee,TAX,SubSL_2,UK,New York,DS02,Business,2022-11-23 +70855,8320,Bronze,Inactive,Finance,2022-11-15,Active,Director,TAX,SubSL_2,Canada,Los Angeles,BI002,Business,2022-11-07 +94608,8375,Bronze,Inactive,Data Strategy,2023-06-20,Active,Manager,Consulting,SubSL_2,Canada,Toronto,AI001,Technology,2023-01-06 +28609,4715,Bronze,Active,Data Strategy,2022-09-26,Active,Supervisor,Consulting,SubSL_3,Canada,London,DS02,,2022-09-21 +73165,8584,Bronze,Active,Data Strategy,2023-08-28,Inactive,Supervisor,TAX,SubSL_2,Canada,Toronto,TAX01,Technology,2022-12-20 +85572,6146,Platinum,Active,Data Strategy,2023-01-22,Active,Supervisor,Audit,SubSL_1,Canada,Los Angeles,TAX01,,2023-07-28 +23588,3021,Platinum,Active,Data Strategy,2023-05-26,Active,Supervisor,IT,SubSL_2,USA,Toronto,AI001,,2023-08-22 +94745,9433,Bronze,Inactive,Data Strategy,2023-01-07,Inactive,Employee,Audit,SubSL_2,UK,New York,TAX01,Leadership,2022-11-27 +12890,6682,Silver,Inactive,Finance,2023-01-01,Active,Manager,RMS,SubSL_2,Canada,London,AI001,Technology,2023-06-01 +26513,2527,Gold,Active,Finance,2023-05-21,Inactive,Supervisor,RMS,SubSL_2,Canada,Los Angeles,TAX01,Technology,2022-11-04 +82254,5233,Platinum,Active,Data Strategy,2023-08-20,Inactive,Director,RMS,SubSL_2,USA,London,TAX01,,2023-05-01 +77348,6900,Silver,Inactive,Marketing,2022-12-12,Inactive,Manager,TAX,SubSL_1,USA,London,DS02,Leadership,2022-09-22 +96261,8553,Platinum,Inactive,HR,2022-09-28,Inactive,Employee,Audit,SubSL_1,USA,Los Angeles,TAX01,Business,2023-02-17 +93091,2538,Silver,Inactive,HR,2023-06-07,Active,Director,Audit,SubSL_2,UK,London,DS02,Technology,2023-02-22 +97400,2748,Gold,Active,HR,2023-05-11,Inactive,Director,RMS,SubSL_3,UK,Toronto,AI001,,2023-01-09 +79391,8744,Silver,Active,IT,2023-05-28,Inactive,Employee,TAX,SubSL_3,UK,Toronto,AI001,Leadership,2023-02-11 +97096,8825,Gold,Inactive,Data Strategy,2023-02-05,Inactive,Employee,RMS,SubSL_1,UK,New York,DS02,Leadership,2023-03-06 +13426,7460,Silver,Inactive,Data Strategy,2023-02-13,Inactive,Employee,Consulting,SubSL_3,Canada,New York,DS02,Leadership,2023-01-27 +14952,2485,Silver,Inactive,HR,2023-05-08,Inactive,Manager,RMS,SubSL_2,Canada,New York,AI001,Technology,2023-07-10 +57441,3875,Silver,Active,HR,2023-05-14,Inactive,Manager,RMS,SubSL_2,UK,London,AI001,Leadership,2023-08-28 +12517,1186,Bronze,Active,Marketing,2023-04-29,Active,Employee,IT,SubSL_1,Canada,Los Angeles,DS02,,2023-04-27 +50074,5784,Silver,Inactive,IT,2023-09-07,Active,Supervisor,RMS,SubSL_3,UK,London,BI002,Technology,2022-12-25 +85826,1022,Gold,Inactive,IT,2023-05-05,Inactive,Supervisor,Consulting,SubSL_1,USA,Los Angeles,TAX01,Technology,2023-08-27 +77476,8531,Bronze,Inactive,Finance,2023-09-08,Active,Employee,IT,SubSL_1,UK,Toronto,TAX01,Technology,2023-06-24 +66670,6641,Platinum,Inactive,Data Strategy,2023-09-19,Active,Manager,Consulting,SubSL_2,USA,New York,BI002,Business,2023-07-17 +64432,4603,Gold,Inactive,Marketing,2022-10-10,Inactive,Employee,RMS,SubSL_1,Canada,Los Angeles,AI001,,2023-03-02 +12824,6935,Gold,Active,IT,2023-04-09,Active,Manager,Consulting,SubSL_3,UK,Toronto,BI002,Leadership,2023-05-31 +38034,6928,Platinum,Active,IT,2022-12-31,Active,Manager,RMS,SubSL_1,USA,London,DS02,Business,2023-01-19 +95009,4281,Gold,Inactive,Marketing,2023-05-18,Active,Director,Consulting,SubSL_1,UK,New York,DS02,Technology,2022-12-27 +58056,9069,Platinum,Inactive,Finance,2023-08-25,Inactive,Manager,Audit,SubSL_3,Canada,New York,DS02,Leadership,2023-07-23 +73206,9037,Platinum,Active,IT,2022-12-20,Inactive,Employee,Consulting,SubSL_2,UK,London,AI001,,2023-04-25 +37568,1751,Gold,Inactive,IT,2023-04-24,Inactive,Manager,TAX,SubSL_1,UK,New York,TAX01,Business,2022-10-25 +52278,9258,Silver,Active,Finance,2022-11-26,Active,Employee,IT,SubSL_3,USA,Los Angeles,TAX01,Technology,2023-02-26 +52991,9229,Silver,Inactive,Data Strategy,2023-05-01,Active,Director,RMS,SubSL_1,USA,New York,TAX01,Leadership,2022-12-23 +56568,4472,Platinum,Inactive,Marketing,2022-11-08,Active,Manager,IT,SubSL_1,USA,London,TAX01,Technology,2023-03-28 +95032,3054,Platinum,Active,Marketing,2022-11-06,Inactive,Director,IT,SubSL_1,Canada,London,TAX01,,2023-01-07 +20602,3077,Bronze,Active,HR,2023-02-10,Inactive,Supervisor,TAX,SubSL_1,UK,London,TAX01,Business,2023-02-10 +42153,7124,Gold,Active,Data Strategy,2023-02-06,Active,Employee,Consulting,SubSL_1,Canada,Toronto,BI002,Leadership,2023-07-11 +53426,6061,Silver,Active,Finance,2023-01-01,Inactive,Supervisor,IT,SubSL_1,USA,London,AI001,Business,2023-07-24 +64313,8609,Gold,Active,Data Strategy,2023-09-10,Inactive,Employee,IT,SubSL_3,UK,Toronto,BI002,Business,2023-03-08 +53921,9460,Silver,Inactive,Finance,2023-05-13,Active,Manager,TAX,SubSL_1,Canada,London,BI002,Business,2022-12-12 +71928,8002,Platinum,Inactive,HR,2023-09-10,Active,Manager,RMS,SubSL_1,USA,New York,TAX01,Leadership,2023-04-21 +88130,7067,Bronze,Active,Marketing,2023-05-28,Active,Manager,IT,SubSL_1,USA,New York,AI001,Business,2023-03-28 +39979,7004,Bronze,Active,HR,2023-04-02,Active,Director,TAX,SubSL_2,Canada,Los Angeles,TAX01,Technology,2023-01-27 +46853,6614,Bronze,Active,Data Strategy,2023-06-02,Inactive,Manager,IT,SubSL_2,USA,Los Angeles,AI001,Business,2023-04-14 +48733,5771,Bronze,Inactive,Marketing,2023-06-30,Inactive,Employee,TAX,SubSL_3,Canada,Los Angeles,BI002,Technology,2023-03-06 +22939,3962,Platinum,Active,Marketing,2023-08-02,Inactive,Manager,Consulting,SubSL_3,UK,London,AI001,Leadership,2022-09-30 +34293,3696,Gold,Active,Marketing,2023-02-04,Active,Manager,TAX,SubSL_1,UK,Los Angeles,AI001,Leadership,2023-01-25 +49680,3608,Gold,Active,Finance,2022-09-24,Active,Manager,TAX,SubSL_3,USA,London,AI001,Technology,2023-03-04 +34489,4350,Gold,Active,Finance,2022-12-21,Inactive,Manager,Audit,SubSL_2,Canada,Los Angeles,TAX01,Leadership,2022-10-31 +73565,6499,Platinum,Active,IT,2022-12-11,Inactive,Employee,Consulting,SubSL_1,UK,Los Angeles,AI001,Leadership,2023-05-30 +15333,8865,Silver,Active,HR,2022-10-01,Inactive,Supervisor,Audit,SubSL_1,Canada,London,TAX01,Technology,2023-05-04 +15073,9667,Gold,Inactive,Marketing,2023-05-21,Inactive,Supervisor,RMS,SubSL_3,USA,Los Angeles,DS02,Leadership,2022-11-01 +68580,1693,Gold,Active,IT,2023-01-29,Inactive,Manager,RMS,SubSL_1,UK,Toronto,AI001,Technology,2023-05-18 +33644,6245,Gold,Inactive,Data Strategy,2022-11-10,Inactive,Employee,Consulting,SubSL_2,UK,New York,DS02,Leadership,2022-11-28 +90907,5649,Gold,Inactive,Data Strategy,2023-04-09,Active,Supervisor,IT,SubSL_3,USA,Toronto,TAX01,Technology,2022-12-12 +89463,7771,Silver,Inactive,Finance,2023-08-26,Active,Director,Audit,SubSL_1,UK,Los Angeles,BI002,Leadership,2022-10-22 +29620,9433,Gold,Inactive,HR,2023-02-01,Inactive,Director,TAX,SubSL_3,Canada,New York,TAX01,Business,2022-09-22 +48819,6409,Silver,Active,Data Strategy,2023-04-30,Inactive,Employee,Consulting,SubSL_2,UK,Los Angeles,TAX01,,2023-06-10 +54806,4099,Silver,Active,IT,2023-07-26,Inactive,Manager,RMS,SubSL_1,Canada,Toronto,AI001,Technology,2023-03-23 +98766,4096,Platinum,Active,HR,2023-07-19,Inactive,Manager,IT,SubSL_3,USA,Los Angeles,AI001,Technology,2023-08-25 +78192,8952,Gold,Active,IT,2022-10-28,Active,Director,IT,SubSL_3,USA,Toronto,AI001,Technology,2023-01-28 +25630,6992,Gold,Inactive,Marketing,2023-01-20,Inactive,Supervisor,Consulting,SubSL_1,UK,Los Angeles,BI002,Technology,2023-07-23 +37351,5072,Gold,Inactive,HR,2023-09-09,Active,Director,Audit,SubSL_1,USA,London,BI002,Business,2023-08-23 +86995,3656,Silver,Inactive,HR,2023-02-19,Inactive,Director,Audit,SubSL_1,UK,London,DS02,Business,2023-01-13 +82494,6815,Bronze,Active,IT,2023-01-04,Active,Supervisor,Consulting,SubSL_2,Canada,New York,BI002,,2022-12-26 +81492,9196,Bronze,Active,IT,2022-11-15,Inactive,Employee,TAX,SubSL_1,USA,New York,AI001,,2022-10-07 +64085,8938,Bronze,Active,Marketing,2022-10-21,Inactive,Manager,Audit,SubSL_1,UK,Toronto,AI001,Leadership,2023-04-07 +40964,4064,Gold,Inactive,IT,2022-10-11,Active,Manager,Consulting,SubSL_1,UK,New York,BI002,,2022-11-25 +51957,8503,Silver,Inactive,Marketing,2023-06-29,Active,Employee,RMS,SubSL_1,USA,Los Angeles,BI002,Business,2023-05-11 +61819,7479,Bronze,Inactive,Finance,2023-07-02,Active,Supervisor,RMS,SubSL_2,Canada,Los Angeles,AI001,Leadership,2023-03-16 +82712,4437,Gold,Inactive,IT,2023-02-06,Inactive,Manager,IT,SubSL_3,UK,London,AI001,,2023-03-26 +97055,1444,Platinum,Inactive,Finance,2022-12-03,Inactive,Director,Consulting,SubSL_2,USA,Toronto,TAX01,Technology,2022-11-30 +40552,1246,Gold,Inactive,IT,2022-10-14,Active,Supervisor,Audit,SubSL_2,Canada,Los Angeles,BI002,,2023-01-06 +88343,7584,Silver,Inactive,Data Strategy,2023-07-12,Inactive,Supervisor,IT,SubSL_2,UK,London,AI001,Technology,2022-10-15 +18712,3102,Silver,Active,Marketing,2023-04-06,Active,Employee,IT,SubSL_2,UK,Los Angeles,DS02,Technology,2022-12-11 +21651,5168,Bronze,Active,IT,2023-01-02,Active,Manager,Audit,SubSL_3,Canada,New York,BI002,Leadership,2022-11-27 +86106,2520,Platinum,Inactive,Finance,2022-10-04,Active,Director,TAX,SubSL_3,UK,London,AI001,Leadership,2023-01-12 +34682,7769,Silver,Active,IT,2023-04-22,Inactive,Manager,Consulting,SubSL_2,Canada,Toronto,AI001,Leadership,2022-12-27 +94253,7214,Gold,Inactive,HR,2023-03-29,Inactive,Director,Audit,SubSL_3,USA,Toronto,AI001,Leadership,2023-06-30 +61812,5549,Bronze,Active,Finance,2022-11-14,Active,Director,Consulting,SubSL_1,Canada,New York,BI002,Leadership,2022-11-18 +45840,7873,Silver,Active,Finance,2023-05-23,Active,Employee,Consulting,SubSL_2,UK,New York,BI002,,2023-03-08 +58742,3470,Platinum,Inactive,Data Strategy,2022-12-04,Inactive,Director,TAX,SubSL_2,Canada,Toronto,AI001,Leadership,2023-06-03 +32279,6793,Platinum,Active,Data Strategy,2023-01-24,Inactive,Manager,RMS,SubSL_1,USA,London,DS02,Business,2022-11-21 +93144,3604,Bronze,Active,Data Strategy,2023-04-14,Inactive,Manager,TAX,SubSL_3,UK,London,AI001,Technology,2022-12-10 +28086,9057,Bronze,Inactive,Finance,2023-04-24,Inactive,Manager,RMS,SubSL_2,UK,Toronto,TAX01,Business,2023-04-19 +93275,6809,Silver,Inactive,HR,2023-06-25,Active,Director,Consulting,SubSL_1,USA,Los Angeles,TAX01,Business,2023-09-11 +14852,5018,Platinum,Inactive,HR,2023-08-28,Inactive,Employee,IT,SubSL_3,USA,London,DS02,Technology,2023-02-25 +33766,4158,Silver,Inactive,Marketing,2023-04-28,Active,Director,TAX,SubSL_3,USA,New York,TAX01,Technology,2023-05-14 +51176,6305,Bronze,Active,Marketing,2023-04-28,Inactive,Manager,IT,SubSL_2,UK,London,TAX01,Business,2023-03-12 +14917,3831,Silver,Inactive,IT,2023-04-29,Inactive,Director,Audit,SubSL_2,Canada,Los Angeles,TAX01,Technology,2023-02-27 +58823,9307,Platinum,Active,Data Strategy,2022-12-01,Active,Employee,Audit,SubSL_1,UK,New York,BI002,Technology,2023-01-07 +27922,2849,Platinum,Active,IT,2022-11-18,Active,Manager,RMS,SubSL_1,USA,Los Angeles,TAX01,Technology,2022-11-26 +91700,5138,Platinum,Active,IT,2023-08-20,Inactive,Director,RMS,SubSL_3,USA,New York,DS02,Leadership,2022-10-26 +70455,2407,Platinum,Inactive,IT,2023-09-17,Inactive,Manager,IT,SubSL_3,USA,London,BI002,,2022-10-03 +26656,3538,Gold,Active,Data Strategy,2023-04-10,Active,Employee,TAX,SubSL_2,USA,London,BI002,Technology,2022-09-29 +67084,7396,Silver,Inactive,Data Strategy,2023-01-31,Inactive,Director,RMS,SubSL_1,Canada,Los Angeles,AI001,,2023-07-19 +33409,8895,Gold,Active,Marketing,2023-05-16,Inactive,Supervisor,IT,SubSL_1,Canada,New York,BI002,Leadership,2022-12-20 +11720,7650,Platinum,Inactive,IT,2022-10-13,Active,Supervisor,RMS,SubSL_3,Canada,Toronto,BI002,,2023-08-28 +49130,1593,Gold,Inactive,HR,2022-12-22,Inactive,Employee,Consulting,SubSL_3,USA,Los Angeles,DS02,,2023-01-30 +69258,5176,Silver,Inactive,Data Strategy,2022-11-04,Inactive,Employee,Consulting,SubSL_2,UK,Los Angeles,TAX01,,2022-10-08 +80427,5849,Silver,Inactive,Finance,2022-11-09,Active,Employee,Audit,SubSL_2,Canada,Toronto,AI001,Business,2023-07-05 +86813,1846,Platinum,Inactive,Finance,2023-03-10,Inactive,Director,IT,SubSL_1,UK,Toronto,BI002,,2023-05-08 +53015,9925,Silver,Active,Data Strategy,2023-07-05,Active,Director,IT,SubSL_3,UK,New York,TAX01,,2023-05-04 +53412,7791,Silver,Inactive,Marketing,2023-06-08,Active,Employee,TAX,SubSL_2,UK,New York,DS02,,2023-07-01 +85402,9697,Platinum,Inactive,IT,2023-07-25,Active,Employee,Consulting,SubSL_1,UK,New York,DS02,,2023-02-09 +12418,4217,Gold,Inactive,IT,2023-06-07,Active,Manager,RMS,SubSL_3,USA,London,AI001,Technology,2023-09-18 +85554,1663,Platinum,Active,Finance,2023-07-12,Inactive,Director,RMS,SubSL_3,Canada,London,AI001,Business,2023-01-01 +25560,1750,Platinum,Inactive,Finance,2023-02-14,Active,Director,Consulting,SubSL_1,Canada,London,DS02,Business,2023-02-07 +85109,5497,Platinum,Inactive,HR,2022-11-15,Active,Employee,IT,SubSL_1,Canada,New York,TAX01,Technology,2023-07-31 +80861,2982,Silver,Active,Data Strategy,2023-08-03,Active,Employee,TAX,SubSL_2,UK,Toronto,TAX01,,2023-04-15 +92464,8479,Platinum,Inactive,Finance,2023-09-09,Inactive,Manager,TAX,SubSL_1,UK,London,TAX01,Business,2022-10-21 +73173,1169,Gold,Active,IT,2023-02-20,Active,Employee,RMS,SubSL_3,UK,Toronto,TAX01,Technology,2022-12-18 +93852,5254,Gold,Active,IT,2022-09-20,Active,Director,RMS,SubSL_1,USA,Toronto,DS02,,2023-09-02 +12752,5891,Gold,Active,IT,2023-09-15,Inactive,Employee,Audit,SubSL_1,USA,New York,TAX01,Business,2022-11-27 +11570,7369,Platinum,Active,Marketing,2023-04-15,Inactive,Employee,Audit,SubSL_1,USA,New York,DS02,,2022-12-18 +90505,5938,Silver,Active,HR,2023-07-15,Inactive,Employee,RMS,SubSL_3,Canada,Toronto,BI002,Business,2023-09-08 +52122,8572,Platinum,Inactive,Marketing,2022-11-27,Active,Employee,TAX,SubSL_1,Canada,Los Angeles,DS02,Leadership,2023-04-10 +66734,9793,Bronze,Inactive,HR,2023-01-13,Active,Employee,Consulting,SubSL_1,UK,New York,BI002,Business,2023-08-02 +70980,7800,Bronze,Active,HR,2023-04-17,Active,Manager,Consulting,SubSL_1,Canada,New York,AI001,,2023-08-26 +78771,9601,Silver,Inactive,Data Strategy,2023-05-02,Active,Manager,TAX,SubSL_3,Canada,Toronto,AI001,,2022-12-11 +75239,2692,Bronze,Active,Data Strategy,2023-07-22,Active,Manager,RMS,SubSL_2,UK,London,DS02,Technology,2022-10-11 +46775,2459,Bronze,Active,HR,2023-09-15,Active,Manager,Consulting,SubSL_3,USA,Toronto,DS02,,2022-11-21 +74268,1958,Platinum,Inactive,Data Strategy,2022-11-01,Inactive,Director,IT,SubSL_1,USA,Toronto,AI001,,2023-04-23 +16275,2967,Silver,Active,HR,2023-07-06,Inactive,Employee,Audit,SubSL_2,Canada,London,BI002,,2023-02-24 +26250,9124,Bronze,Inactive,IT,2023-09-01,Active,Manager,TAX,SubSL_2,UK,New York,TAX01,Leadership,2022-10-06 +23683,8981,Platinum,Inactive,IT,2022-12-04,Inactive,Manager,RMS,SubSL_3,Canada,Los Angeles,DS02,Business,2023-06-07 +10520,8662,Bronze,Active,HR,2023-06-12,Inactive,Supervisor,TAX,SubSL_3,Canada,New York,TAX01,Leadership,2023-09-08 +48276,9798,Platinum,Active,Marketing,2022-11-17,Active,Supervisor,RMS,SubSL_3,UK,Los Angeles,DS02,Business,2023-01-10 +50411,7463,Bronze,Active,Data Strategy,2023-07-14,Inactive,Employee,Consulting,SubSL_2,Canada,New York,BI002,Leadership,2023-02-03 +87975,4717,Bronze,Inactive,Marketing,2023-01-19,Inactive,Director,Consulting,SubSL_3,USA,Toronto,DS02,,2023-07-05 +82196,2835,Platinum,Inactive,Data Strategy,2022-10-13,Active,Employee,Consulting,SubSL_1,USA,Los Angeles,TAX01,Leadership,2023-08-17 +69782,9909,Gold,Active,IT,2023-01-08,Inactive,Director,Audit,SubSL_2,USA,London,AI001,Leadership,2023-07-03 +67243,3623,Gold,Active,HR,2023-01-31,Active,Director,RMS,SubSL_2,Canada,London,DS02,Leadership,2022-09-30 +67286,1642,Bronze,Active,HR,2023-06-12,Active,Employee,RMS,SubSL_1,UK,New York,DS02,Leadership,2022-11-29 +52561,1313,Platinum,Inactive,Data Strategy,2023-08-09,Active,Employee,Audit,SubSL_1,USA,New York,TAX01,Leadership,2023-03-09 +81096,5253,Silver,Active,IT,2023-05-31,Active,Employee,Consulting,SubSL_2,USA,New York,AI001,Leadership,2022-11-11 +42115,4026,Gold,Active,HR,2022-12-05,Inactive,Supervisor,Audit,SubSL_1,UK,London,TAX01,Business,2023-05-04 +91979,5542,Bronze,Inactive,IT,2022-09-26,Inactive,Director,TAX,SubSL_1,UK,London,AI001,Business,2022-11-01 +47726,9891,Gold,Active,Finance,2023-01-10,Active,Manager,TAX,SubSL_1,USA,New York,AI001,Technology,2023-05-30 +79641,5203,Platinum,Active,HR,2023-09-03,Inactive,Supervisor,RMS,SubSL_1,USA,Toronto,DS02,,2022-12-19 +91701,5552,Bronze,Active,Data Strategy,2023-07-08,Inactive,Director,RMS,SubSL_3,Canada,Toronto,AI001,Leadership,2023-05-31 +23453,3275,Platinum,Active,Finance,2023-04-17,Inactive,Manager,IT,SubSL_2,UK,Toronto,DS02,Technology,2023-06-22 +95650,2651,Silver,Inactive,IT,2022-11-15,Active,Manager,Audit,SubSL_1,Canada,Los Angeles,DS02,,2023-04-10 +83136,3142,Platinum,Inactive,Marketing,2023-02-23,Active,Director,Audit,SubSL_1,Canada,Los Angeles,DS02,Business,2023-03-19 +61825,4441,Bronze,Active,Finance,2022-10-20,Inactive,Employee,Audit,SubSL_2,UK,New York,BI002,,2023-08-15 +26846,2747,Platinum,Active,IT,2022-10-08,Inactive,Employee,Consulting,SubSL_1,USA,London,AI001,Technology,2023-07-13 +53720,8799,Platinum,Active,Data Strategy,2023-06-29,Inactive,Director,IT,SubSL_1,USA,New York,BI002,Technology,2023-06-24 +87087,5888,Gold,Inactive,Marketing,2023-07-11,Active,Supervisor,RMS,SubSL_2,Canada,Los Angeles,AI001,Leadership,2023-08-01 +48493,4436,Bronze,Inactive,Finance,2023-01-27,Inactive,Manager,IT,SubSL_2,Canada,London,TAX01,Leadership,2023-06-09 +59019,1881,Silver,Active,Finance,2023-04-26,Inactive,Manager,IT,SubSL_3,UK,Toronto,TAX01,Technology,2023-04-15 +61147,3164,Bronze,Active,Finance,2022-10-11,Active,Manager,Consulting,SubSL_2,Canada,New York,TAX01,Leadership,2023-07-21 +89504,8019,Gold,Active,Marketing,2023-02-06,Active,Supervisor,TAX,SubSL_1,USA,London,DS02,Leadership,2023-09-02 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+22144,2206,Bronze,Inactive,Marketing,2023-04-25,Inactive,Supervisor,Consulting,SubSL_2,UK,Toronto,TAX01,Leadership,2023-07-04 +92207,4106,Platinum,Active,Data Strategy,2023-03-04,Inactive,Director,Audit,SubSL_2,UK,New York,BI002,Business,2022-12-21 +27548,6728,Silver,Active,Finance,2022-10-09,Inactive,Employee,RMS,SubSL_3,Canada,Toronto,TAX01,Business,2023-03-28 diff --git a/referencefiles/workforce.csv b/referencefiles/workforce.csv new file mode 100644 index 0000000000000000000000000000000000000000..48ece344338186713136178ffc0dd11233e5cc54 --- /dev/null +++ b/referencefiles/workforce.csv @@ -0,0 +1,1030 @@ +Age,Attrition,BusinessTravel,DailyRate,Department,DistanceFromHome,Education,EducationField,EmployeeCount,GUI,EnvironmentSatisfaction,Gender,HourlyRate,JobInvolvement,JobLevel,JobRole,JobSatisfaction,MaritalStatus,MonthlyIncome,MonthlyRate,NumCompaniesWorked,Over18,OverTime,PercentSalaryHike,PerformanceRating,RelationshipSatisfaction,StandardHours,StockOptionLevel,TotalWorkingYears,TrainingTimesLastYear,WorkLifeBalance,YearsAtCompany,YearsInCurrentRole,YearsSinceLastPromotion,YearsWithCurrManager +50.0,No,Travel_Rarely,1126.0,Research & Development,1.0,2,Medical,1,997,4,Male,66,3,4,Research Director,4,Divorced,17399,6615,9,Y,No,22,4,3,80,1,32,1,2,5,4,1,3 +36.0,No,Travel_Rarely,216.0,Research & Development,6.0,2,Medical,1,178,2,Male,84,3,2,Manufacturing Director,2,Divorced,4941,2819,6,Y,No,20,4,4,80,2,7,0,3,3,2,0,1 +21.0,Yes,Travel_Rarely,337.0,Sales,7.0,1,Marketing,1,1780,2,Male,31,3,1,Sales Representative,2,Single,2679,4567,1,Y,No,13,3,2,80,0,1,3,3,1,0,1,0 +50.0,No,Travel_Frequently,1246.0,Human Resources,,3,Medical,1,644,1,Male,99,3,5,Manager,2,Married,18200,7999,1,Y,No,11,3,3,80,1,32,2,3,32,5,10,7 +52.0,No,Travel_Rarely,994.0,Research & Development,7.0,4,Life Sciences,1,1118,2,Male,87,3,3,Healthcare Representative,2,Single,10445,15322,7,Y,No,19,3,4,80,0,18,4,3,8,6,4,0 +33.0,Yes,Travel_Rarely,1277.0,Research & Development,15.0,1,Medical,1,582,2,Male,56,3,3,Manager,3,Married,13610,24619,7,Y,Yes,12,3,4,80,0,15,2,4,7,6,7,7 +47.0,No,Travel_Rarely,1001.0,Research & Development,4.0,3,Life Sciences,1,1827,3,Female,92,2,3,Manufacturing Director,2,Divorced,10333,19271,8,Y,Yes,12,3,3,80,1,28,4,3,22,11,14,10 +22.0,No,Travel_Rarely,1230.0,Research & Development,1.0,2,Life Sciences,1,872,4,Male,33,2,2,Manufacturing Director,4,Married,4775,19146,6,Y,No,22,4,1,80,2,4,2,1,2,2,2,2 +,Yes,Travel_Rarely,890.0,Research & Development,2.0,4,Medical,1,828,3,Male,46,3,1,Research Scientist,3,Single,4382,16374,6,Y,No,17,3,4,80,0,5,3,2,2,2,2,1 +33.0,No,Non-Travel,530.0,Sales,16.0,3,Life Sciences,1,1681,3,Female,36,3,2,Sales Executive,4,Divorced,5368,16130,1,Y,Yes,25,4,3,80,1,7,2,3,6,5,1,2 +40.0,No,Travel_Rarely,630.0,Sales,4.0,4,Marketing,1,215,3,Male,67,2,3,Sales Executive,4,,10855,8552,7,Y,No,11,3,1,80,1,15,2,2,12,11,2,11 +27.0,No,Travel_Frequently,793.0,Sales,2.0,1,Life Sciences,1,1371,4,Male,43,1,2,Sales Executive,4,Single,5071,20392,3,Y,No,20,4,2,80,0,8,3,3,6,2,0,0 +40.0,No,Travel_Rarely,543.0,Research & Development,1.0,4,Life Sciences,1,2012,1,Male,83,3,1,Laboratory Technician,4,Married,2406,4060,8,Y,No,19,3,3,80,2,8,3,2,1,0,0,0 +55.0,No,Travel_Frequently,1091.0,Research & Development,2.0,1,Life Sciences,1,1096,4,Male,65,3,3,Manufacturing Director,2,Married,10976,15813,3,Y,No,18,3,2,80,1,23,4,3,3,2,1,2 +33.0,Yes,Travel_Rarely,1017.0,Research & Development,25.0,3,Medical,1,1108,1,Male,55,2,1,Research Scientist,2,Single,2313,2993,4,Y,Yes,20,4,2,80,0,5,0,3,2,2,2,2 +37.0,Yes,Travel_Rarely,625.0,Sales,1.0,4,Life Sciences,1,970,1,Male,46,2,3,Sales Executive,3,Married,10609,14922,5,Y,No,11,3,3,80,0,17,2,1,14,1,11,7 +34.0,No,Travel_Rarely,511.0,Sales,,2,Life Sciences,1,1779,4,Female,32,1,2,Sales Executive,4,Single,6029,25353,5,Y,No,12,3,1,80,0,6,3,3,2,2,2,2 +46.0,No,Travel_Rarely,168.0,Sales,4.0,2,Marketing,1,1280,4,Female,33,2,5,Manager,2,Married,18789,9946,2,Y,No,14,3,3,80,1,26,2,3,11,4,0,8 +38.0,No,Travel_Rarely,1245.0,Sales,14.0,3,Life Sciences,1,1582,3,Male,80,3,2,Sales Executive,2,Married,9924,12355,0,Y,No,11,3,4,80,1,10,3,3,9,8,7,7 +30.0,No,Travel_Rarely,1138.0,Research & Development,6.0,3,Technical Degree,1,1311,1,Female,48,2,2,Laboratory Technician,4,Married,4627,23631,0,Y,No,12,3,1,80,1,10,6,3,9,2,6,7 +34.0,No,Travel_Rarely,829.0,Human Resources,,2,Human Resources,1,847,3,Male,88,3,1,Human Resources,4,Married,3737,2243,0,Y,No,19,3,3,80,1,4,1,1,3,2,0,2 +34.0,No,Travel_Rarely,1130.0,Research & Development,,3,Life Sciences,1,1658,4,Female,66,3,2,Research Scientist,2,Divorced,5433,19332,1,Y,No,12,3,3,80,1,11,2,3,11,8,7,9 +36.0,No,Non-Travel,301.0,Sales,15.0,4,Marketing,1,2036,4,Male,88,1,2,Sales Executive,4,Divorced,5406,10436,1,Y,No,24,4,1,80,1,15,4,2,15,12,11,11 +,No,Travel_Rarely,1146.0,Human Resources,26.0,4,Life Sciences,1,2040,3,Female,31,3,3,Human Resources,4,Single,8837,16642,1,Y,Yes,16,3,3,80,0,9,2,3,9,0,1,7 +,No,Travel_Rarely,1276.0,Research & Development,16.0,3,Life Sciences,1,586,4,Male,72,3,3,Healthcare Representative,3,Married,7632,14295,4,Y,Yes,12,3,3,80,0,10,2,3,8,7,0,0 +40.0,No,Travel_Rarely,611.0,Sales,7.0,4,Medical,1,1740,2,Male,88,3,5,Manager,2,Single,19833,4349,1,Y,No,14,3,2,80,0,21,3,2,21,8,12,8 +24.0,No,Travel_Rarely,1353.0,Sales,,2,Other,1,128,1,Female,33,3,2,Sales Executive,3,Married,4999,17519,0,Y,No,21,4,1,80,1,4,2,2,3,2,0,2 +53.0,No,Travel_Rarely,1376.0,Sales,2.0,2,Medical,1,981,3,Male,45,3,4,Manager,3,Divorced,14852,13938,6,Y,No,13,3,3,80,1,22,3,4,17,13,15,2 +32.0,No,Travel_Rarely,977.0,Research & Development,2.0,3,Medical,1,1671,4,Male,45,3,2,Research Scientist,2,Divorced,5470,25518,0,Y,No,13,3,3,80,2,10,4,2,9,5,1,6 +,Yes,Travel_Frequently,289.0,Research & Development,2.0,2,Medical,1,1504,3,Male,38,2,1,Laboratory Technician,1,Single,2561,5355,7,Y,No,11,3,3,80,0,8,2,2,0,0,0,0 +55.0,No,Travel_Rarely,1229.0,Research & Development,4.0,4,Life Sciences,1,1501,4,Male,30,3,2,Healthcare Representative,3,Married,4035,16143,0,Y,Yes,16,3,2,80,0,4,2,3,3,2,1,2 +30.0,No,Travel_Rarely,317.0,Research & Development,2.0,3,Life Sciences,1,548,3,Female,43,1,2,Manufacturing Director,4,Single,6091,24793,2,Y,No,20,4,3,80,0,11,2,3,5,4,0,2 +,Yes,Travel_Frequently,887.0,Research & Development,,2,Medical,1,848,3,Female,88,2,1,Research Scientist,3,Married,2366,20898,1,Y,Yes,14,3,1,80,1,8,2,3,8,7,1,7 +23.0,Yes,Travel_Rarely,1243.0,Research & Development,6.0,3,Life Sciences,1,811,3,Male,63,4,1,Laboratory Technician,1,Married,1601,3445,1,Y,Yes,21,4,3,80,2,1,2,3,0,0,0,0 +51.0,No,Travel_Rarely,1169.0,Research & Development,7.0,4,Medical,1,211,2,Male,34,2,2,Manufacturing Director,3,Married,6132,13983,2,Y,No,17,3,3,80,0,10,2,3,1,0,0,0 +42.0,No,Travel_Rarely,932.0,Research & Development,1.0,2,Life Sciences,1,827,4,Female,43,2,2,Manufacturing Director,4,Married,6062,4051,9,Y,Yes,13,3,4,80,1,8,4,3,4,3,0,2 +,No,Travel_Rarely,1343.0,Research & Development,27.0,1,Medical,1,856,3,Female,53,2,1,Research Scientist,1,Single,2559,17852,1,Y,No,11,3,4,80,0,6,3,2,6,5,1,1 +,No,Travel_Rarely,,Sales,1.0,3,Marketing,1,600,2,Male,85,3,2,Sales Executive,3,Married,4717,18659,9,Y,No,11,3,3,80,0,15,2,3,11,9,6,9 +20.0,Yes,Travel_Rarely,1362.0,Research & Development,10.0,1,Medical,1,701,4,Male,32,3,1,Research Scientist,3,Single,1009,26999,1,Y,Yes,11,3,4,80,0,1,5,3,1,0,1,1 +,No,Travel_Rarely,736.0,Sales,26.0,3,Life Sciences,1,1387,3,Male,48,2,2,Sales Executive,1,Married,4724,24232,1,Y,No,11,3,3,80,1,5,0,3,5,3,0,4 +29.0,No,Travel_Rarely,942.0,Research & Development,15.0,1,Life Sciences,1,1202,2,Female,69,1,1,Research Scientist,4,Married,2168,26933,0,Y,Yes,18,3,1,80,1,6,2,2,5,4,1,3 +43.0,No,Travel_Rarely,982.0,Research & Development,12.0,3,Life Sciences,1,520,1,Male,59,2,4,Research Director,2,Divorced,14336,4345,1,Y,No,11,3,3,80,1,25,3,3,25,10,3,9 +40.0,No,Travel_Frequently,902.0,Research & Development,26.0,2,Medical,1,1180,3,Female,92,2,2,Research Scientist,4,Married,4422,21203,3,Y,Yes,13,3,4,80,1,16,3,1,1,1,0,0 +29.0,No,Travel_Rarely,1401.0,Research & Development,6.0,1,Medical,1,1192,2,Female,54,3,1,Laboratory Technician,4,Married,3131,26342,1,Y,No,13,3,1,80,1,10,5,3,10,8,0,8 +46.0,No,Travel_Rarely,1319.0,Sales,,3,Technical Degree,1,1863,1,Female,45,4,4,Sales Executive,1,Divorced,13225,7739,2,Y,No,12,3,4,80,1,25,5,3,19,17,2,8 +44.0,Yes,Travel_Frequently,429.0,Research & Development,1.0,2,Medical,1,1792,3,Male,99,3,1,Research Scientist,2,Divorced,2342,11092,1,Y,Yes,12,3,3,80,3,6,2,2,5,3,2,3 +47.0,No,Travel_Rarely,359.0,Research & Development,2.0,4,Medical,1,1443,1,Female,82,3,4,Research Director,3,Married,17169,26703,3,Y,No,19,3,2,80,2,26,2,4,20,17,5,6 +32.0,No,Travel_Frequently,430.0,Research & Development,24.0,4,Life Sciences,1,772,1,Male,80,3,2,Laboratory Technician,4,Married,5309,21146,1,Y,No,15,3,4,80,2,10,2,3,10,8,4,7 +38.0,No,Travel_Rarely,362.0,Research & Development,1.0,1,Life Sciences,1,662,3,Female,43,3,1,Research Scientist,1,Single,2619,14561,3,Y,No,17,3,4,80,0,8,3,2,0,0,0,0 +51.0,No,Travel_Rarely,770.0,Human Resources,,3,Life Sciences,1,1352,3,Male,84,3,4,Manager,2,Divorced,14026,17588,1,Y,Yes,11,3,2,80,1,33,2,3,33,9,0,10 +58.0,No,Non-Travel,390.0,Research & Development,1.0,4,Life Sciences,1,422,4,Male,32,1,2,Healthcare Representative,3,Divorced,5660,17056,2,Y,Yes,13,3,4,80,1,12,2,3,5,3,1,2 +,No,Travel_Rarely,195.0,Sales,1.0,3,Medical,1,620,1,Female,80,3,2,Sales Executive,3,Single,4859,6698,1,Y,No,16,3,4,80,0,5,3,3,5,4,0,3 +45.0,No,Travel_Rarely,1448.0,Research & Development,29.0,3,Technical Degree,1,1465,2,Male,55,3,3,Manufacturing Director,4,Married,9380,14720,4,Y,Yes,18,3,4,80,2,10,4,4,3,1,1,2 +56.0,No,Travel_Rarely,832.0,Research & Development,9.0,3,Medical,1,762,3,Male,81,3,4,Healthcare Representative,4,Married,11103,20420,7,Y,No,11,3,3,80,0,30,1,2,10,7,1,1 +37.0,No,Travel_Rarely,124.0,Research & Development,,3,Other,1,1062,4,Female,35,3,2,Healthcare Representative,2,Single,4107,13848,3,Y,No,15,3,1,80,0,8,3,2,4,3,0,1 +37.0,No,Travel_Frequently,1278.0,Sales,1.0,4,Medical,1,1700,3,Male,31,1,2,Sales Executive,4,Divorced,9525,7677,1,Y,No,14,3,3,80,2,6,2,2,6,3,1,3 +39.0,No,Travel_Rarely,903.0,Sales,2.0,5,Life Sciences,1,985,1,Male,41,4,3,Sales Executive,3,Single,7880,2560,0,Y,No,18,3,4,80,0,9,3,3,8,7,0,7 +,No,Travel_Rarely,819.0,Research & Development,2.0,3,Life Sciences,1,1182,3,Male,44,2,3,Manufacturing Director,2,Divorced,10274,19588,2,Y,No,18,3,2,80,1,15,2,4,7,7,6,4 +54.0,No,Travel_Rarely,1082.0,Sales,2.0,4,Life Sciences,1,1070,3,Female,41,2,3,Sales Executive,3,Married,10686,8392,6,Y,No,11,3,2,80,1,13,4,3,9,4,7,0 +32.0,No,Non-Travel,1109.0,Research & Development,29.0,4,Medical,1,1046,4,Female,69,3,1,Laboratory Technician,3,Single,4025,11135,9,Y,No,12,3,2,80,0,10,2,3,8,7,7,7 +48.0,No,Travel_Rarely,530.0,Sales,29.0,1,Medical,1,473,1,Female,91,3,3,Manager,3,Married,12504,23978,3,Y,No,21,4,2,80,1,15,3,1,0,0,0,0 +33.0,No,Travel_Frequently,827.0,Research & Development,1.0,4,Other,1,998,3,Female,84,4,2,Healthcare Representative,2,Married,5488,20161,1,Y,Yes,13,3,1,80,1,6,2,3,6,5,1,2 +31.0,Yes,Travel_Rarely,249.0,Sales,6.0,4,Life Sciences,1,163,2,Male,76,1,2,Sales Executive,3,Married,6172,20739,4,Y,Yes,18,3,2,80,0,12,3,2,7,7,7,7 +46.0,No,Travel_Rarely,,Sales,1.0,2,Marketing,1,244,2,Female,92,3,3,Sales Executive,1,Divorced,10453,2137,1,Y,No,25,4,3,80,3,24,2,3,24,13,15,7 +38.0,No,Travel_Rarely,688.0,Research & Development,23.0,4,Life Sciences,1,393,4,Male,82,3,2,Healthcare Representative,4,Divorced,5745,18899,9,Y,No,14,3,2,80,1,10,2,3,2,2,1,2 +38.0,No,Travel_Rarely,1321.0,Sales,1.0,4,Life Sciences,1,1995,4,Male,86,3,2,Sales Executive,2,Married,4440,7636,0,Y,No,15,3,1,80,2,16,3,3,15,13,5,8 +43.0,No,Travel_Rarely,1179.0,Sales,2.0,3,Medical,1,1706,4,Male,73,3,2,Sales Executive,4,Married,7847,6069,1,Y,Yes,17,3,1,80,1,10,3,3,10,9,8,8 +37.0,No,Travel_Frequently,889.0,Research & Development,9.0,3,Medical,1,403,2,Male,53,3,1,Research Scientist,4,Married,2326,11411,1,Y,Yes,12,3,3,80,3,4,3,2,4,2,1,2 +39.0,Yes,Travel_Rarely,1162.0,Sales,,2,Medical,1,445,4,Female,41,3,2,Sales Executive,3,Married,5238,17778,4,Y,Yes,18,3,1,80,0,12,3,2,1,0,0,0 +,No,Travel_Rarely,1169.0,Human Resources,8.0,2,Medical,1,869,2,Male,63,2,1,Human Resources,4,Divorced,4936,23965,1,Y,No,13,3,4,80,1,6,6,3,5,1,0,4 +,No,Travel_Frequently,1199.0,Research & Development,18.0,4,Life Sciences,1,2049,3,Male,80,3,2,Healthcare Representative,3,Married,5689,24594,1,Y,Yes,14,3,4,80,2,10,2,4,10,2,0,2 +30.0,No,Travel_Rarely,288.0,Research & Development,2.0,3,Life Sciences,1,117,3,Male,99,2,2,Healthcare Representative,4,Married,4152,15830,1,Y,No,19,3,1,80,3,11,3,3,11,10,10,8 +39.0,No,Travel_Rarely,412.0,Research & Development,13.0,4,Medical,1,1307,3,Female,94,2,4,Manager,2,Divorced,17123,17334,6,Y,Yes,13,3,4,80,2,21,4,3,19,9,15,2 +43.0,No,Travel_Rarely,,Research & Development,6.0,3,Medical,1,1866,1,Female,81,2,5,Manager,3,Married,19392,22539,7,Y,No,13,3,4,80,0,21,2,3,16,12,6,14 +27.0,No,Travel_Rarely,975.0,Research & Development,7.0,3,Medical,1,764,4,Female,55,2,2,Healthcare Representative,1,Single,6811,23398,8,Y,No,19,3,1,80,0,9,2,1,7,6,0,7 +42.0,No,Travel_Rarely,462.0,Sales,14.0,2,Medical,1,936,3,Female,68,2,2,Sales Executive,3,Single,6244,7824,7,Y,No,17,3,1,80,0,10,6,3,5,4,0,3 +31.0,No,Travel_Rarely,471.0,Research & Development,4.0,3,Medical,1,1916,1,Female,62,4,1,Laboratory Technician,3,Divorced,3978,16031,8,Y,No,12,3,2,80,1,4,0,2,2,2,2,2 +39.0,Yes,Travel_Rarely,1122.0,Research & Development,6.0,3,Medical,1,932,4,Male,70,3,1,Laboratory Technician,1,Married,2404,4303,7,Y,Yes,21,4,4,80,0,8,2,1,2,2,2,2 +29.0,No,Travel_Rarely,694.0,Research & Development,1.0,3,Life Sciences,1,1264,4,Female,87,2,4,Research Director,4,Divorced,16124,3423,3,Y,No,14,3,2,80,2,9,2,2,7,7,1,7 +49.0,No,Travel_Frequently,636.0,Research & Development,10.0,4,Life Sciences,1,396,3,Female,35,3,5,Research Director,1,Single,18665,25594,9,Y,Yes,11,3,4,80,0,22,4,3,3,2,1,2 +38.0,No,Travel_Rarely,1404.0,Sales,1.0,3,Life Sciences,1,1961,1,Male,59,2,1,Sales Representative,1,Single,2858,11473,4,Y,No,14,3,1,80,0,20,3,2,1,0,0,0 +,No,Travel_Rarely,1395.0,Research & Development,9.0,4,Medical,1,2008,2,Male,48,3,2,Research Scientist,3,Single,5098,18698,1,Y,No,19,3,2,80,0,10,5,3,10,7,0,8 +42.0,No,Travel_Rarely,810.0,Research & Development,23.0,5,Life Sciences,1,468,1,Female,44,3,4,Research Director,4,Single,15992,15901,2,Y,No,14,3,2,80,0,16,2,3,1,0,0,0 +31.0,Yes,Travel_Frequently,561.0,Research & Development,,3,Life Sciences,1,1537,4,Female,33,3,1,Research Scientist,3,Single,4084,4156,1,Y,No,12,3,1,80,0,7,2,1,7,2,7,7 +34.0,No,Travel_Rarely,,Sales,13.0,4,Medical,1,1951,4,Male,39,3,3,Sales Executive,3,Divorced,8628,22914,1,Y,No,18,3,3,80,1,9,2,2,8,7,1,1 +36.0,No,Travel_Rarely,1425.0,Research & Development,14.0,1,Life Sciences,1,924,3,Male,68,3,2,Healthcare Representative,4,Married,6586,4821,0,Y,Yes,17,3,1,80,1,17,2,2,16,8,4,11 +27.0,No,Travel_Frequently,829.0,Sales,8.0,1,Marketing,1,800,3,Male,84,3,2,Sales Executive,4,Married,4342,24008,0,Y,No,19,3,2,80,1,5,3,3,4,2,1,1 +40.0,No,Non-Travel,1094.0,Sales,28.0,3,Other,1,615,3,Male,58,1,3,Sales Executive,1,Divorced,10932,11373,3,Y,No,15,3,3,80,1,20,2,3,1,0,0,1 +34.0,No,Travel_Rarely,971.0,Sales,1.0,3,Technical Degree,1,1535,4,Male,64,2,3,Sales Executive,3,Married,7083,12288,1,Y,Yes,14,3,4,80,0,10,3,3,10,9,8,6 +43.0,No,Travel_Rarely,1001.0,Research & Development,7.0,3,Life Sciences,1,451,3,Female,43,3,3,Healthcare Representative,1,,9985,9262,8,Y,No,16,3,1,80,1,10,1,2,1,0,0,0 +31.0,No,Travel_Rarely,326.0,Sales,8.0,2,Life Sciences,1,1453,1,Male,31,3,3,Sales Executive,4,Divorced,10793,8386,1,Y,No,18,3,1,80,1,13,5,3,13,7,9,9 +41.0,No,Travel_Rarely,642.0,Research & Development,1.0,3,Life Sciences,1,1999,4,Male,76,3,1,Research Scientist,4,Married,2782,21412,3,Y,No,22,4,1,80,1,12,3,3,5,3,1,0 +31.0,No,Travel_Frequently,1125.0,Research & Development,1.0,3,Life Sciences,1,1956,4,Male,48,1,2,Research Scientist,1,Married,5003,5771,1,Y,No,21,4,2,80,0,10,6,3,10,8,8,7 +45.0,No,Travel_Frequently,1297.0,Research & Development,1.0,4,Medical,1,1922,2,Male,44,3,2,Healthcare Representative,3,Single,5399,14511,4,Y,No,12,3,3,80,0,12,3,3,4,2,0,3 +33.0,No,Travel_Frequently,508.0,Sales,10.0,3,Marketing,1,446,2,Male,46,2,2,Sales Executive,4,Single,4682,4317,3,Y,No,14,3,3,80,0,9,6,2,7,7,0,1 +27.0,No,Travel_Rarely,1220.0,Research & Development,,3,Life Sciences,1,434,3,Female,85,3,1,Research Scientist,2,Single,2478,20938,1,Y,Yes,12,3,2,80,0,4,2,2,4,3,1,2 +36.0,No,Travel_Frequently,884.0,Research & Development,23.0,2,Medical,1,2061,3,Male,41,4,2,Laboratory Technician,4,Married,2571,12290,4,Y,No,17,3,3,80,1,17,3,3,5,2,0,3 +33.0,No,Travel_Rarely,267.0,Research & Development,21.0,3,Medical,1,1698,2,Male,79,4,1,Laboratory Technician,2,Married,2028,13637,1,Y,No,18,3,4,80,3,14,6,3,14,11,2,13 +31.0,No,Travel_Rarely,670.0,Research & Development,26.0,1,Life Sciences,1,16,1,Male,31,3,1,Research Scientist,3,Divorced,2911,15170,1,Y,No,17,3,4,80,1,5,1,2,5,2,4,3 +19.0,Yes,Travel_Frequently,602.0,Sales,1.0,1,Technical Degree,1,235,3,Female,100,1,1,Sales Representative,1,Single,2325,20989,0,Y,No,21,4,1,80,0,1,5,4,0,0,0,0 +32.0,No,Travel_Frequently,1311.0,Research & Development,7.0,3,Life Sciences,1,359,2,Male,100,4,1,Laboratory Technician,2,Married,2794,26062,1,Y,No,20,4,3,80,0,5,3,1,5,1,0,3 +36.0,No,Non-Travel,217.0,Research & Development,18.0,4,Life Sciences,1,1133,1,Male,78,3,2,Manufacturing Director,4,Single,7779,23238,2,Y,No,20,4,1,80,0,18,0,3,11,9,0,9 +37.0,No,Travel_Rarely,,Human Resources,8.0,2,Other,1,1794,3,Male,89,3,2,Human Resources,2,Divorced,4071,12832,2,Y,No,13,3,3,80,0,19,4,2,10,0,4,7 +,No,Travel_Rarely,1144.0,Sales,10.0,1,Medical,1,1056,4,Male,74,3,1,Sales Representative,2,Married,1052,23384,1,Y,No,22,4,2,80,0,1,5,3,1,0,0,0 +,No,Travel_Rarely,959.0,Sales,28.0,3,Life Sciences,1,183,1,Male,41,2,2,Sales Executive,3,Married,8639,24835,2,Y,No,18,3,4,80,0,6,3,3,2,2,2,2 +29.0,Yes,Travel_Rarely,805.0,Research & Development,1.0,2,Life Sciences,1,816,2,Female,36,2,1,Laboratory Technician,1,,2319,6689,1,Y,Yes,11,3,4,80,1,1,1,3,1,0,0,0 +29.0,No,Travel_Rarely,1107.0,Research & Development,28.0,4,Life Sciences,1,1120,3,Female,93,3,1,Research Scientist,4,Divorced,2514,26968,4,Y,No,22,4,1,80,1,11,1,3,7,5,1,7 +41.0,No,Non-Travel,247.0,Research & Development,7.0,1,Life Sciences,1,1035,2,Female,55,1,5,Research Director,3,,19973,20284,1,Y,No,22,4,2,80,2,21,3,3,21,16,5,10 +30.0,No,Travel_Rarely,1240.0,Human Resources,9.0,3,Human Resources,1,184,3,Male,48,3,2,Human Resources,4,Married,6347,13982,0,Y,Yes,19,3,4,80,0,12,2,1,11,9,4,7 +39.0,No,Travel_Rarely,1253.0,Research & Development,10.0,1,Medical,1,1800,3,Male,65,3,3,Research Director,3,Single,13464,7914,7,Y,No,21,4,3,80,0,9,3,3,4,3,2,2 +22.0,Yes,Travel_Rarely,1294.0,Research & Development,8.0,1,Medical,1,1783,3,Female,79,3,1,Laboratory Technician,1,Married,2398,15999,1,Y,Yes,17,3,3,80,0,1,6,3,1,0,0,0 +31.0,No,Non-Travel,979.0,Research & Development,1.0,4,Medical,1,308,3,Male,90,1,2,Manufacturing Director,3,Married,4345,4381,0,Y,No,12,3,4,80,1,6,2,3,5,4,1,4 +45.0,No,Travel_Rarely,1234.0,Sales,11.0,2,Life Sciences,1,1045,4,Female,90,3,4,Manager,4,Married,17650,5404,3,Y,No,13,3,2,80,1,26,4,4,9,3,1,1 +42.0,No,Travel_Frequently,532.0,Research & Development,29.0,2,Life Sciences,1,547,1,Female,92,3,2,Research Scientist,3,Divorced,4556,12932,2,Y,No,11,3,2,80,1,19,3,3,5,4,0,2 +31.0,No,Travel_Frequently,798.0,Research & Development,7.0,2,Life Sciences,1,442,3,Female,48,2,3,Manufacturing Director,3,Married,8943,14034,1,Y,No,24,4,1,80,1,10,2,3,10,9,8,9 +51.0,No,Travel_Rarely,,Research & Development,2.0,3,Medical,1,408,4,Male,84,1,2,Manufacturing Director,2,Divorced,5482,16321,5,Y,No,18,3,4,80,1,13,3,3,4,1,1,2 +34.0,No,Travel_Frequently,669.0,Research & Development,1.0,3,Medical,1,1184,4,Male,97,2,2,Healthcare Representative,1,Single,5343,25755,0,Y,No,20,4,3,80,0,14,3,3,13,9,4,9 +33.0,No,Non-Travel,722.0,Sales,17.0,3,Life Sciences,1,992,4,Male,38,3,4,Manager,3,Single,17444,20489,1,Y,No,11,3,4,80,0,10,2,3,10,8,6,0 +,No,Travel_Rarely,1224.0,Sales,7.0,4,Life Sciences,1,1962,3,Female,55,3,2,Sales Executive,4,Married,5204,13586,1,Y,Yes,11,3,4,80,0,10,2,3,10,8,0,9 +40.0,No,Travel_Rarely,444.0,Sales,2.0,2,Marketing,1,1986,2,Female,92,3,2,Sales Executive,2,Married,5677,4258,3,Y,No,14,3,3,80,1,15,4,3,11,8,5,10 +33.0,No,Travel_Rarely,536.0,Sales,10.0,5,Marketing,1,1268,4,Male,82,4,3,Sales Executive,3,Divorced,8380,21708,0,Y,Yes,14,3,4,80,2,10,3,3,9,8,0,8 +34.0,No,Travel_Rarely,1400.0,Sales,9.0,1,Life Sciences,1,1163,2,Female,70,3,2,Sales Executive,3,Married,5714,5829,1,Y,No,20,4,1,80,0,6,3,2,6,5,1,3 +34.0,No,Travel_Rarely,1397.0,Research & Development,1.0,5,Life Sciences,1,683,2,Male,42,3,1,Research Scientist,4,Married,2691,7660,1,Y,No,12,3,4,80,1,10,4,2,10,9,8,8 +30.0,No,Travel_Rarely,153.0,Research & Development,8.0,2,Life Sciences,1,1015,2,Female,73,4,3,Research Director,1,Married,11416,17802,0,Y,Yes,12,3,3,80,3,9,4,2,8,7,1,7 +33.0,No,Travel_Frequently,1392.0,Research & Development,,4,Life Sciences,1,5,4,Female,56,3,1,Research Scientist,3,Married,2909,23159,1,Y,Yes,11,3,3,80,0,8,3,3,8,7,3,0 +45.0,No,Non-Travel,248.0,Research & Development,23.0,2,Life Sciences,1,1002,4,Male,42,3,2,Laboratory Technician,1,Married,3633,14039,1,Y,Yes,15,3,3,80,1,9,2,3,9,8,0,8 +37.0,No,Non-Travel,142.0,Sales,9.0,4,Medical,1,626,1,Male,69,3,3,Sales Executive,2,Divorced,8834,24666,1,Y,No,13,3,4,80,1,9,6,3,9,5,7,7 +31.0,No,Travel_Rarely,691.0,Sales,7.0,3,Marketing,1,438,4,Male,73,3,2,Sales Executive,4,Divorced,7547,7143,4,Y,No,12,3,4,80,3,13,3,3,7,7,1,7 +32.0,No,Travel_Frequently,1005.0,Research & Development,2.0,2,Life Sciences,1,8,4,Male,79,3,1,Laboratory Technician,4,Single,3068,11864,0,Y,No,13,3,3,80,0,8,2,2,7,7,3,6 +,No,Travel_Rarely,640.0,Research & Development,1.0,3,Technical Degree,1,1301,4,Male,84,3,1,Research Scientist,1,Single,2080,4732,2,Y,No,11,3,2,80,0,5,2,2,3,2,1,2 +,No,Travel_Rarely,683.0,Research & Development,2.0,1,Medical,1,1407,1,Male,36,2,1,Research Scientist,4,Single,3904,4050,0,Y,No,12,3,4,80,0,5,2,3,4,3,1,1 +30.0,Yes,Travel_Rarely,138.0,Research & Development,22.0,3,Life Sciences,1,1004,1,Female,48,3,1,Research Scientist,3,Married,2132,11539,4,Y,Yes,11,3,2,80,0,7,2,3,5,2,0,1 +33.0,No,Travel_Frequently,1141.0,Sales,1.0,3,Life Sciences,1,52,3,Female,42,4,2,Sales Executive,1,Married,5376,3193,2,Y,No,19,3,1,80,2,10,3,3,5,3,1,3 +38.0,No,Travel_Rarely,168.0,Research & Development,1.0,3,Life Sciences,1,743,3,Female,81,3,3,Manufacturing Director,3,Single,7861,15397,4,Y,Yes,14,3,4,80,0,10,4,4,1,0,0,0 +41.0,No,Travel_Rarely,1411.0,Research & Development,19.0,2,Life Sciences,1,334,3,Male,36,3,2,Research Scientist,1,Divorced,3072,19877,2,Y,No,16,3,1,80,2,17,2,2,1,0,0,0 +51.0,Yes,Travel_Frequently,1150.0,Research & Development,8.0,4,Life Sciences,1,179,1,Male,53,1,3,Manufacturing Director,4,Single,10650,25150,2,Y,No,15,3,4,80,0,18,2,3,4,2,0,3 +38.0,No,Travel_Frequently,471.0,Research & Development,12.0,3,Life Sciences,1,837,1,Male,45,2,2,Healthcare Representative,1,Divorced,6288,4284,2,Y,No,15,3,3,80,1,13,3,2,4,3,1,2 +27.0,No,Travel_Rarely,728.0,Sales,23.0,1,Medical,1,1864,2,Female,36,2,2,Sales Representative,3,Married,3540,7018,1,Y,No,21,4,4,80,1,9,5,3,9,8,5,8 +53.0,No,Travel_Rarely,102.0,Research & Development,23.0,4,Life Sciences,1,901,4,Female,72,3,4,Research Director,4,Single,14275,20206,6,Y,No,18,3,3,80,0,33,0,3,12,9,3,8 +30.0,No,Travel_Rarely,1358.0,Sales,16.0,1,Life Sciences,1,1479,4,Male,96,3,2,Sales Executive,3,Married,5301,2939,8,Y,No,15,3,3,80,2,4,2,2,2,1,2,2 +30.0,Yes,Travel_Rarely,945.0,Sales,9.0,3,Medical,1,1876,2,Male,89,3,1,Sales Representative,4,Single,1081,16019,1,Y,No,13,3,3,80,0,1,3,2,1,0,0,0 +30.0,No,Travel_Rarely,921.0,Research & Development,1.0,3,Life Sciences,1,806,4,Male,38,1,1,Laboratory Technician,3,Married,3833,24375,3,Y,No,21,4,3,80,2,7,2,3,2,2,0,2 +58.0,No,Travel_Rarely,1055.0,Research & Development,1.0,3,Medical,1,1423,4,Female,76,3,5,Research Director,1,Married,19701,22456,3,Y,Yes,21,4,3,80,1,32,3,3,9,8,1,5 +34.0,No,Travel_Rarely,216.0,Sales,1.0,4,Marketing,1,1047,2,Male,75,4,2,Sales Executive,4,Divorced,9725,12278,0,Y,No,11,3,4,80,1,16,2,2,15,1,0,9 +,No,Travel_Frequently,1096.0,Research & Development,6.0,3,Other,1,1918,3,Male,61,4,1,Laboratory Technician,4,Married,2544,7102,0,Y,No,18,3,1,80,1,8,3,3,7,7,7,7 +51.0,No,Travel_Rarely,1178.0,Sales,14.0,2,Life Sciences,1,500,3,Female,87,3,2,Sales Executive,4,Married,4936,14862,4,Y,No,11,3,3,80,1,18,2,2,7,7,0,7 +39.0,No,Travel_Rarely,117.0,Research & Development,10.0,1,Medical,1,429,3,Male,99,3,4,Manager,1,Married,17068,5355,1,Y,Yes,14,3,4,80,0,21,3,3,21,9,11,10 +36.0,No,Non-Travel,635.0,Sales,10.0,4,Medical,1,592,2,Male,32,3,3,Sales Executive,4,Single,9980,15318,1,Y,No,14,3,4,80,0,10,3,2,10,3,9,7 +32.0,No,Travel_Rarely,588.0,Sales,8.0,2,Technical Degree,1,436,3,Female,65,2,2,Sales Executive,2,Married,5228,24624,1,Y,Yes,11,3,4,80,0,13,2,3,13,12,11,9 +56.0,No,Travel_Frequently,1240.0,Research & Development,9.0,3,Medical,1,1071,1,Female,63,3,1,Research Scientist,3,Married,2942,12154,2,Y,No,19,3,2,80,1,18,4,3,5,4,0,3 +57.0,No,Travel_Rarely,405.0,Research & Development,1.0,2,Life Sciences,1,1483,2,Male,93,4,2,Research Scientist,3,,4900,2721,0,Y,No,24,4,1,80,1,13,2,2,12,9,2,8 +57.0,No,Travel_Rarely,210.0,Sales,29.0,3,Marketing,1,568,1,Male,56,2,4,Manager,4,Divorced,14118,22102,3,Y,No,12,3,3,80,1,32,3,2,1,0,0,0 +40.0,No,Travel_Rarely,804.0,Research & Development,2.0,1,Medical,1,763,4,Female,86,2,1,Research Scientist,4,Single,2342,22929,0,Y,Yes,20,4,4,80,0,5,2,2,4,2,2,3 +23.0,Yes,Travel_Frequently,638.0,Sales,9.0,3,Marketing,1,2023,4,Male,33,3,1,Sales Representative,1,Married,1790,26956,1,Y,No,19,3,1,80,1,1,3,2,1,0,1,0 +53.0,No,Travel_Rarely,1395.0,Research & Development,24.0,4,Medical,1,1689,2,Male,48,4,3,Healthcare Representative,4,Married,7005,3458,3,Y,No,15,3,3,80,0,11,2,3,4,3,1,2 +38.0,No,Travel_Frequently,148.0,Research & Development,2.0,3,Medical,1,1675,4,Female,42,2,1,Laboratory Technician,2,Single,2440,23826,1,Y,No,22,4,2,80,0,4,3,3,4,3,3,3 +36.0,No,Travel_Rarely,1041.0,Human Resources,13.0,3,Human Resources,1,829,3,Male,36,3,1,Human Resources,2,Married,2143,25527,4,Y,No,13,3,2,80,1,8,2,3,5,2,0,4 +29.0,No,Travel_Frequently,1413.0,Sales,1.0,1,Medical,1,312,2,Female,42,3,3,Sales Executive,4,Married,7918,6599,1,Y,No,14,3,4,80,1,11,5,3,11,10,4,1 +38.0,No,Travel_Rarely,201.0,Research & Development,10.0,3,Medical,1,2015,2,Female,99,1,3,Research Director,3,Married,13206,3376,3,Y,No,12,3,1,80,1,20,3,3,18,16,1,11 +47.0,No,Travel_Rarely,1180.0,Research & Development,25.0,3,Medical,1,1993,1,Male,84,3,3,Healthcare Representative,3,Single,8633,13084,2,Y,No,23,4,2,80,0,25,3,3,17,14,12,11 +32.0,Yes,Travel_Rarely,1089.0,Research & Development,7.0,2,Life Sciences,1,1309,4,Male,79,3,2,Laboratory Technician,3,Married,4883,22845,1,Y,No,18,3,1,80,1,10,3,3,10,4,1,1 +,No,Travel_Rarely,819.0,Research & Development,18.0,5,Life Sciences,1,1621,2,Male,48,4,2,Research Scientist,1,Married,5208,26312,1,Y,No,11,3,4,80,0,16,2,3,16,15,1,10 +36.0,No,Travel_Frequently,1195.0,Research & Development,11.0,3,Life Sciences,1,85,2,Male,95,2,2,Manufacturing Director,2,Single,6499,22656,1,Y,No,13,3,3,80,0,6,3,3,6,5,0,3 +49.0,Yes,Travel_Frequently,1475.0,Research & Development,28.0,2,Life Sciences,1,1420,1,Male,97,2,2,Laboratory Technician,1,Single,4284,22710,3,Y,No,20,4,1,80,0,20,2,3,4,3,1,3 +34.0,No,Travel_Rarely,121.0,Research & Development,2.0,4,Medical,1,804,3,Female,86,2,1,Research Scientist,1,Single,4381,7530,1,Y,No,11,3,3,80,0,6,3,3,6,5,1,3 +39.0,No,Travel_Rarely,524.0,Research & Development,18.0,2,Life Sciences,1,1322,1,Male,32,3,2,Manufacturing Director,3,Single,4534,13352,0,Y,No,11,3,1,80,0,9,6,3,8,7,1,7 +30.0,No,Non-Travel,829.0,Research & Development,1.0,1,Life Sciences,1,292,3,Male,88,2,3,Manufacturing Director,3,Single,8474,20925,1,Y,No,22,4,3,80,0,12,2,3,11,8,5,8 +51.0,No,Travel_Frequently,541.0,Sales,2.0,3,Marketing,1,1391,2,Male,52,3,3,Sales Executive,2,Married,10596,15395,2,Y,No,11,3,2,80,0,14,5,3,4,2,3,2 +,No,Travel_Rarely,735.0,Research & Development,6.0,1,Life Sciences,1,1291,3,Male,66,3,1,Research Scientist,3,Married,3506,6020,0,Y,Yes,14,3,4,80,0,4,3,3,3,2,2,2 +60.0,No,Travel_Rarely,1179.0,Sales,16.0,4,Marketing,1,732,1,Male,84,3,2,Sales Executive,1,Single,5405,11924,8,Y,No,14,3,4,80,0,10,1,3,2,2,2,2 +50.0,Yes,Travel_Frequently,878.0,Sales,1.0,4,Life Sciences,1,2044,2,Male,94,3,2,Sales Executive,3,Divorced,6728,14255,7,Y,No,12,3,4,80,2,12,3,3,6,3,0,1 +45.0,No,,950.0,Research & Development,28.0,3,Technical Degree,1,1546,4,Male,97,3,1,Research Scientist,4,Married,2132,4585,4,Y,No,20,4,4,80,1,8,3,3,5,4,0,3 +56.0,No,Travel_Rarely,1400.0,Research & Development,7.0,3,Life Sciences,1,112,4,Male,49,1,3,Manufacturing Director,4,Single,7260,21698,4,Y,No,11,3,1,80,0,37,3,2,6,4,0,2 +46.0,No,Travel_Rarely,706.0,Research & Development,2.0,2,Life Sciences,1,1857,4,Male,82,3,3,Manufacturing Director,4,Divorced,8578,19989,3,Y,No,14,3,3,80,1,12,4,2,9,8,4,7 +42.0,No,Travel_Rarely,855.0,Research & Development,12.0,3,Medical,1,1768,2,Male,57,3,1,Laboratory Technician,2,Divorced,2766,8952,8,Y,No,22,4,2,80,3,7,6,2,5,3,0,4 +60.0,No,Travel_Rarely,,Research & Development,1.0,4,Medical,1,1697,3,Male,92,1,3,Healthcare Representative,4,Divorced,10883,20467,3,Y,No,20,4,3,80,1,19,2,4,1,0,0,0 +,No,Travel_Rarely,141.0,Sales,,1,Other,1,879,3,Male,98,3,2,Sales Executive,1,Married,4194,14363,1,Y,Yes,18,3,4,80,0,5,3,3,5,3,0,3 +,No,Non-Travel,280.0,Human Resources,1.0,2,Life Sciences,1,1858,3,Male,43,3,1,Human Resources,4,Divorced,2706,10494,1,Y,No,15,3,2,80,1,3,2,3,3,2,2,2 +53.0,Yes,Travel_Rarely,607.0,Research & Development,2.0,5,Technical Degree,1,1572,3,Female,78,2,3,Manufacturing Director,4,Married,10169,14618,0,Y,No,16,3,2,80,1,34,4,3,33,7,1,9 +39.0,No,Travel_Rarely,867.0,Research & Development,9.0,2,Medical,1,1936,1,Male,87,3,2,Manufacturing Director,1,Married,5151,12315,1,Y,No,25,4,4,80,1,10,3,3,10,0,7,9 +48.0,No,Travel_Rarely,1224.0,Research & Development,10.0,3,Life Sciences,1,1867,4,Male,91,2,5,Research Director,2,Married,19665,13583,4,Y,No,12,3,4,80,0,29,3,3,22,10,12,9 +37.0,No,Travel_Rarely,228.0,Sales,6.0,4,Medical,1,378,3,Male,98,3,2,Sales Executive,4,Married,6502,22825,4,Y,No,14,3,2,80,1,7,5,4,5,4,0,1 +41.0,No,Travel_Frequently,1200.0,Research & Development,22.0,3,Life Sciences,1,1392,4,Female,75,3,2,Research Scientist,4,Divorced,5467,13953,3,Y,Yes,14,3,1,80,2,12,4,2,6,2,3,3 +21.0,No,Non-Travel,895.0,Sales,9.0,2,Medical,1,484,1,Male,39,3,1,Sales Representative,4,Single,2610,2851,1,Y,No,24,4,3,80,0,3,3,2,3,2,2,2 +32.0,No,Travel_Rarely,117.0,Sales,13.0,4,Life Sciences,1,859,2,Male,73,3,2,Sales Executive,4,Divorced,4403,9250,2,Y,No,11,3,3,80,1,8,3,2,5,2,0,3 +37.0,Yes,Travel_Rarely,1373.0,Research & Development,2.0,2,Other,1,4,4,Male,92,2,1,Laboratory Technician,3,Single,2090,2396,6,Y,Yes,15,3,2,80,0,7,3,3,0,0,0,0 +59.0,No,Travel_Rarely,1324.0,Research & Development,,3,Medical,1,10,3,Female,81,4,1,Laboratory Technician,1,Married,2670,9964,4,Y,Yes,20,4,1,80,3,12,3,2,1,0,0,0 +45.0,No,Travel_Frequently,1249.0,Research & Development,7.0,3,Life Sciences,1,425,1,Male,97,3,3,Laboratory Technician,1,Divorced,5210,20308,1,Y,No,18,3,1,80,1,24,2,3,24,9,9,11 +,Yes,Travel_Frequently,130.0,Research & Development,25.0,4,Life Sciences,1,881,4,Female,96,3,1,Research Scientist,2,Divorced,2022,16612,1,Y,Yes,19,3,1,80,1,10,3,2,10,2,7,8 +36.0,No,Travel_Frequently,469.0,Research & Development,,3,Technical Degree,1,1257,3,Male,46,3,1,Research Scientist,2,Married,3692,9256,1,Y,No,12,3,3,80,0,12,2,2,11,10,0,7 +41.0,No,Travel_Rarely,930.0,Sales,,3,Life Sciences,1,2037,3,Male,57,2,2,Sales Executive,2,Divorced,8938,12227,2,Y,No,11,3,3,80,1,14,5,3,5,4,0,4 +41.0,No,Travel_Rarely,896.0,Sales,6.0,3,Life Sciences,1,298,4,Female,75,3,3,Manager,4,Single,13591,14674,3,Y,Yes,18,3,3,80,0,16,3,3,1,0,0,0 +42.0,No,Travel_Rarely,603.0,Research & Development,7.0,4,Medical,1,1292,2,Female,78,4,2,Research Scientist,2,Married,2372,5628,6,Y,Yes,16,3,4,80,0,18,2,3,1,0,0,0 +42.0,No,Travel_Rarely,691.0,Sales,8.0,4,Marketing,1,35,3,Male,48,3,2,Sales Executive,2,Married,6825,21173,0,Y,No,11,3,4,80,1,10,2,3,9,7,4,2 +24.0,No,Non-Travel,830.0,Sales,13.0,2,Life Sciences,1,1495,4,Female,78,3,1,Sales Representative,2,Married,2033,7103,1,Y,No,13,3,3,80,1,1,2,3,1,0,0,0 +33.0,Yes,Travel_Rarely,603.0,Sales,9.0,4,Marketing,1,1157,1,Female,77,3,2,Sales Executive,1,Single,8224,18385,0,Y,Yes,17,3,1,80,0,6,3,3,5,2,0,3 +43.0,No,Travel_Frequently,422.0,Research & Development,1.0,3,Life Sciences,1,902,4,Female,33,3,2,Healthcare Representative,4,Married,5562,21782,4,Y,No,13,3,2,80,1,12,2,2,5,2,2,2 +,No,Travel_Rarely,583.0,Sales,4.0,1,Marketing,1,885,3,Male,87,2,2,Sales Executive,1,Married,4256,18154,1,Y,No,12,3,1,80,0,5,1,4,5,2,0,3 +38.0,No,Travel_Frequently,1391.0,Research & Development,10.0,1,Medical,1,1006,3,Male,66,3,1,Research Scientist,3,Married,2684,12127,0,Y,No,17,3,2,80,1,3,0,2,2,1,0,2 +33.0,No,Travel_Rarely,516.0,Research & Development,8.0,5,Life Sciences,1,1515,4,Male,69,3,2,Healthcare Representative,3,Single,6388,22049,2,Y,Yes,17,3,1,80,0,14,6,3,0,0,0,0 +53.0,No,Travel_Rarely,661.0,Sales,7.0,2,Marketing,1,862,1,Female,78,2,3,Sales Executive,4,Married,10934,20715,7,Y,Yes,18,3,4,80,1,35,3,3,5,2,0,4 +43.0,No,Travel_Frequently,1082.0,Research & Development,27.0,3,Life Sciences,1,1126,3,Female,83,3,3,Manufacturing Director,1,Married,10820,11535,8,Y,No,11,3,3,80,1,18,1,3,8,7,0,1 +42.0,No,Travel_Rarely,269.0,Research & Development,2.0,3,Medical,1,351,4,Female,56,2,1,Laboratory Technician,1,Divorced,2593,8007,0,Y,Yes,11,3,3,80,1,10,4,3,9,6,7,8 +53.0,No,Travel_Rarely,1282.0,Research & Development,,3,Other,1,32,3,Female,58,3,5,Manager,3,Divorced,19094,10735,4,Y,No,11,3,4,80,1,26,3,2,14,13,4,8 +29.0,Yes,Travel_Rarely,318.0,Research & Development,8.0,4,Other,1,454,2,Male,77,1,1,Laboratory Technician,1,Married,2119,4759,1,Y,Yes,11,3,4,80,0,7,4,2,7,7,0,7 +29.0,No,Travel_Rarely,657.0,Research & Development,27.0,3,Medical,1,793,2,Female,66,3,2,Healthcare Representative,3,Married,4335,25549,4,Y,No,12,3,1,80,1,11,3,2,8,7,1,1 +37.0,No,Travel_Rarely,408.0,Research & Development,19.0,2,Life Sciences,1,61,2,Male,73,3,1,Research Scientist,2,Married,3022,10227,4,Y,No,21,4,1,80,0,8,1,3,1,0,0,0 +50.0,No,Travel_Frequently,1115.0,Research & Development,1.0,3,Life Sciences,1,141,1,Female,73,3,5,Research Director,2,Married,18172,9755,3,Y,Yes,19,3,1,80,0,28,1,2,8,3,0,7 +29.0,No,Non-Travel,746.0,Sales,2.0,3,Life Sciences,1,469,4,Male,61,3,2,Sales Executive,3,Married,4649,16928,1,Y,No,14,3,1,80,1,4,3,2,4,3,0,2 +33.0,No,Travel_Frequently,515.0,Research & Development,1.0,2,Life Sciences,1,73,1,Female,98,3,3,Research Director,4,Single,13458,15146,1,Y,Yes,12,3,3,80,0,15,1,3,15,14,8,12 +55.0,No,Non-Travel,444.0,Research & Development,2.0,1,Medical,1,1074,3,Male,40,2,4,Manager,1,Single,16756,17323,7,Y,No,15,3,2,80,0,31,3,4,9,7,6,2 +51.0,No,Travel_Rarely,1469.0,Research & Development,8.0,4,Life Sciences,1,296,2,Male,81,2,3,Research Director,2,Married,12490,15736,5,Y,No,16,3,4,80,2,16,5,1,10,9,4,7 +30.0,No,Travel_Frequently,1312.0,Research & Development,23.0,3,Life Sciences,1,159,1,Male,96,1,1,Research Scientist,3,Divorced,2613,22310,1,Y,No,25,4,3,80,3,10,2,2,10,7,0,9 +49.0,No,Travel_Rarely,1098.0,Research & Development,4.0,2,Medical,1,1256,1,Male,85,2,5,Manager,3,Married,18711,12124,2,Y,No,13,3,3,80,1,23,2,4,1,0,0,0 +47.0,No,Travel_Frequently,1379.0,Research & Development,16.0,4,Medical,1,987,3,Male,64,4,2,Manufacturing Director,3,Divorced,5067,6759,1,Y,Yes,19,3,3,80,0,20,3,4,19,10,2,7 +31.0,No,Travel_Rarely,1082.0,Research & Development,1.0,4,Medical,1,95,3,Male,87,3,1,Research Scientist,2,Single,2501,18775,1,Y,No,17,3,2,80,0,1,4,3,1,1,1,0 +47.0,No,Travel_Rarely,207.0,Research & Development,9.0,4,Life Sciences,1,1856,2,Female,64,3,1,Laboratory Technician,3,Single,2105,5411,4,Y,No,12,3,3,80,0,7,2,3,2,2,2,0 +58.0,No,Travel_Rarely,848.0,Research & Development,23.0,4,Life Sciences,1,1308,1,Male,88,3,1,Research Scientist,3,Divorced,2372,26076,1,Y,No,12,3,4,80,2,2,3,3,2,2,2,2 +41.0,Yes,Travel_Rarely,1360.0,Research & Development,12.0,3,Technical Degree,1,58,2,Female,49,3,5,Research Director,3,Married,19545,16280,1,Y,No,12,3,4,80,0,23,0,3,22,15,15,8 +29.0,No,Travel_Rarely,468.0,Research & Development,28.0,4,Medical,1,2054,4,Female,73,2,1,Research Scientist,1,Single,3785,8489,1,Y,No,14,3,2,80,0,5,3,1,5,4,0,4 +50.0,No,Travel_Rarely,1207.0,Research & Development,28.0,1,Medical,1,716,4,Male,74,4,1,Laboratory Technician,3,Married,3221,3297,1,Y,Yes,11,3,3,80,3,20,3,3,20,8,3,8 +32.0,No,Travel_Rarely,267.0,Research & Development,29.0,4,Life Sciences,1,2010,3,Female,49,2,1,Laboratory Technician,2,Single,2837,15919,1,Y,No,13,3,3,80,0,6,3,3,6,2,4,1 +44.0,No,Travel_Rarely,1313.0,Research & Development,7.0,3,Medical,1,1608,2,Female,31,3,5,Research Director,4,Divorced,19049,3549,0,Y,Yes,14,3,4,80,1,23,4,2,22,7,1,10 +38.0,No,Travel_Rarely,433.0,Human Resources,1.0,3,Human Resources,1,1152,3,Male,37,4,1,Human Resources,3,Married,2844,6004,1,Y,No,13,3,4,80,1,7,2,4,7,6,5,0 +,Yes,Travel_Frequently,342.0,Research & Development,2.0,3,Life Sciences,1,1053,1,Male,57,3,1,Research Scientist,1,Married,2042,15346,6,Y,Yes,14,3,2,80,1,6,2,3,3,2,1,2 +40.0,No,Travel_Frequently,580.0,Sales,,4,Life Sciences,1,729,4,Male,48,2,3,Sales Executive,1,Married,10475,23772,5,Y,Yes,21,4,3,80,1,20,2,3,18,13,1,12 +45.0,No,Travel_Rarely,252.0,Research & Development,2.0,3,Life Sciences,1,834,2,Female,95,2,1,Research Scientist,3,Single,2274,6153,1,Y,No,14,3,4,80,0,1,3,3,1,0,0,0 +46.0,No,Travel_Frequently,1034.0,Research & Development,18.0,1,Medical,1,624,1,Female,86,3,3,Healthcare Representative,3,Married,10527,8984,5,Y,No,11,3,4,80,0,28,3,2,2,2,1,2 +,Yes,Non-Travel,1366.0,Research & Development,24.0,2,Technical Degree,1,1082,2,Male,72,2,3,Healthcare Representative,1,Single,8722,12355,1,Y,No,12,3,1,80,0,10,2,2,10,7,1,9 +34.0,No,Travel_Rarely,181.0,Research & Development,2.0,4,Medical,1,1755,4,Male,97,4,1,Research Scientist,4,Married,2932,5586,0,Y,Yes,14,3,1,80,3,6,3,3,5,0,1,2 +55.0,No,Travel_Frequently,135.0,Research & Development,18.0,4,Medical,1,1034,3,Male,62,3,2,Healthcare Representative,2,Married,6385,12992,3,Y,Yes,14,3,4,80,2,17,3,3,8,7,6,7 +19.0,No,Travel_Rarely,265.0,Research & Development,25.0,3,Life Sciences,1,1269,2,Female,57,4,1,Research Scientist,4,Single,2994,21221,1,Y,Yes,12,3,4,80,0,1,2,3,1,0,0,1 +32.0,No,Travel_Rarely,427.0,Research & Development,1.0,3,Medical,1,78,1,Male,33,3,2,Manufacturing Director,4,Married,6162,10877,1,Y,Yes,22,4,2,80,1,9,3,3,9,8,7,8 +40.0,No,Non-Travel,663.0,Research & Development,9.0,4,Other,1,1449,3,Male,81,3,2,Laboratory Technician,3,Divorced,3975,23099,3,Y,No,11,3,3,80,2,11,2,4,8,7,0,7 +30.0,No,Travel_Rarely,1334.0,Sales,4.0,2,Medical,1,121,3,Female,63,2,2,Sales Executive,2,Divorced,5209,19760,1,Y,Yes,12,3,2,80,3,11,4,2,11,8,2,7 +22.0,Yes,Travel_Rarely,617.0,Research & Development,,1,Life Sciences,1,926,2,Female,34,3,2,Manufacturing Director,3,Married,4171,10022,0,Y,Yes,19,3,1,80,1,4,3,4,3,2,0,2 +48.0,No,Travel_Rarely,1469.0,Research & Development,20.0,4,Medical,1,945,4,Male,51,3,1,Research Scientist,3,Married,2259,5543,4,Y,No,17,3,1,80,2,13,2,2,0,0,0,0 +45.0,No,Non-Travel,1195.0,Research & Development,2.0,2,Medical,1,264,1,Male,65,2,4,Manager,4,Married,16792,20462,9,Y,No,23,4,4,80,1,22,1,3,20,8,11,8 +53.0,No,Travel_Rarely,1070.0,Research & Development,,4,Medical,1,386,3,Male,45,3,4,Research Director,3,Married,17584,21016,3,Y,Yes,16,3,4,80,3,21,5,2,5,3,1,3 +36.0,No,Travel_Frequently,541.0,Sales,,4,Medical,1,481,1,Male,48,2,3,Sales Executive,4,Married,9699,7246,4,Y,No,11,3,1,80,1,16,2,3,13,9,1,12 +29.0,No,Travel_Frequently,806.0,Research & Development,1.0,4,Life Sciences,1,710,2,Male,76,1,1,Research Scientist,4,Divorced,2720,18959,1,Y,No,18,3,4,80,1,10,5,3,10,7,2,8 +46.0,No,Travel_Rarely,1003.0,Research & Development,8.0,4,Life Sciences,1,1080,4,Female,74,2,2,Research Scientist,1,Divorced,4615,21029,8,Y,Yes,23,4,1,80,3,19,2,3,16,13,1,7 +41.0,No,Travel_Rarely,549.0,Research & Development,7.0,2,Medical,1,1025,4,Female,42,3,2,Manufacturing Director,3,Single,5003,23371,6,Y,No,14,3,2,80,0,8,6,3,2,2,2,1 +41.0,Yes,Travel_Rarely,1356.0,Sales,20.0,2,Marketing,1,248,2,Female,70,3,1,Sales Representative,2,Single,3140,21728,1,Y,Yes,22,4,4,80,0,4,5,2,4,3,0,2 +52.0,No,Travel_Frequently,322.0,Research & Development,28.0,2,Medical,1,1401,4,Female,59,4,4,Manufacturing Director,3,Married,13247,9731,2,Y,Yes,11,3,2,80,1,24,3,2,5,3,0,2 +51.0,No,Travel_Frequently,1456.0,Research & Development,1.0,4,Medical,1,145,1,Female,30,2,3,Healthcare Representative,1,Single,7484,25796,3,Y,No,20,4,3,80,0,23,1,2,13,12,12,8 +,Yes,Travel_Rarely,1357.0,Research & Development,25.0,3,Life Sciences,1,55,1,Male,48,1,1,Laboratory Technician,3,Single,2293,10558,1,Y,No,12,3,3,80,0,1,2,2,1,0,0,1 +36.0,No,Travel_Rarely,1157.0,Sales,2.0,4,Life Sciences,1,1556,3,Male,70,3,1,Sales Representative,4,Single,2644,17001,3,Y,Yes,21,4,4,80,0,7,3,2,3,2,1,2 +38.0,Yes,Travel_Rarely,1180.0,Research & Development,29.0,1,Medical,1,282,2,Male,70,3,2,Healthcare Representative,1,Married,6673,11354,7,Y,Yes,19,3,2,80,0,17,2,3,1,0,0,0 +31.0,No,Travel_Frequently,715.0,Sales,2.0,4,Other,1,1613,4,Male,54,3,2,Sales Executive,1,Single,5332,21602,7,Y,No,13,3,4,80,0,10,3,3,5,2,0,3 +44.0,No,Travel_Rarely,1488.0,Sales,1.0,5,Marketing,1,68,2,Female,75,3,2,Sales Executive,1,Divorced,5454,4009,5,Y,Yes,21,4,3,80,1,9,2,2,4,3,1,3 +30.0,No,Travel_Rarely,,Sales,27.0,5,Marketing,1,747,3,Male,99,3,2,Sales Executive,4,Divorced,5304,25275,7,Y,No,23,4,4,80,1,10,2,2,8,7,7,7 +31.0,Yes,Travel_Frequently,1060.0,Sales,1.0,3,Life Sciences,1,1331,4,Female,54,3,1,Sales Representative,2,Single,2302,8319,1,Y,Yes,11,3,1,80,0,3,2,4,3,2,2,2 +27.0,Yes,Travel_Rarely,135.0,Research & Development,17.0,4,Life Sciences,1,1405,4,Female,51,3,1,Research Scientist,3,Single,2394,25681,1,Y,Yes,13,3,4,80,0,8,2,3,8,2,7,7 +,No,Travel_Rarely,1451.0,Research & Development,2.0,1,Life Sciences,1,1136,1,Male,67,2,1,Research Scientist,2,Married,3201,19911,0,Y,No,17,3,1,80,0,6,2,1,5,3,0,4 +24.0,No,,1206.0,Research & Development,17.0,1,Medical,1,1009,4,Female,41,2,2,Manufacturing Director,3,Divorced,4377,24117,1,Y,No,15,3,2,80,2,5,6,3,4,2,3,2 +50.0,No,Travel_Rarely,328.0,Research & Development,1.0,3,Medical,1,249,3,Male,86,2,1,Laboratory Technician,3,Married,3690,3425,2,Y,No,15,3,4,80,1,5,2,2,3,2,0,2 +39.0,No,Travel_Rarely,1329.0,Sales,4.0,4,Life Sciences,1,182,4,Female,47,2,2,Sales Executive,3,Married,5902,14590,4,Y,No,14,3,3,80,1,17,1,4,15,11,5,9 +30.0,No,Non-Travel,879.0,Research & Development,9.0,2,Medical,1,1298,3,Female,72,3,2,Manufacturing Director,3,Single,4695,12858,7,Y,Yes,18,3,3,80,0,10,3,3,8,4,1,7 +30.0,No,Travel_Rarely,852.0,Research & Development,1.0,1,Life Sciences,1,104,4,Male,55,2,2,Laboratory Technician,4,Married,5126,15998,1,Y,Yes,12,3,3,80,2,10,1,2,10,8,3,0 +29.0,No,,991.0,Sales,,3,Medical,1,1669,1,Male,43,2,2,Sales Executive,2,Divorced,4187,3356,1,Y,Yes,13,3,2,80,1,10,3,2,10,0,0,9 +59.0,No,Non-Travel,1420.0,Human Resources,2.0,4,Human Resources,1,140,3,Female,32,2,5,Manager,4,Married,18844,21922,9,Y,No,21,4,4,80,1,30,3,3,3,2,2,2 +36.0,No,Non-Travel,427.0,Research & Development,8.0,3,Life Sciences,1,742,1,Female,63,4,3,Research Director,1,Married,11713,20335,9,Y,No,14,3,1,80,1,10,2,3,8,7,0,5 +29.0,Yes,Travel_Rarely,,Research & Development,10.0,3,Life Sciences,1,994,4,Female,92,2,1,Research Scientist,1,Single,2404,11479,6,Y,Yes,20,4,3,80,0,3,5,3,0,0,0,0 +30.0,Yes,Travel_Frequently,448.0,Sales,12.0,4,Life Sciences,1,648,2,Male,74,2,1,Sales Representative,1,Married,2033,14470,1,Y,No,18,3,3,80,1,1,2,4,1,0,0,0 +50.0,No,Travel_Rarely,1452.0,Research & Development,11.0,3,Life Sciences,1,226,3,Female,53,3,5,Manager,2,Single,19926,17053,3,Y,No,15,3,2,80,0,21,5,3,5,4,4,4 +37.0,No,Travel_Rarely,1017.0,Research & Development,1.0,2,Medical,1,340,3,Female,83,2,1,Research Scientist,1,Married,3920,18697,2,Y,No,14,3,1,80,1,17,2,2,3,1,0,2 +38.0,No,Travel_Rarely,849.0,Research & Development,25.0,2,Life Sciences,1,421,1,Female,81,2,3,Research Director,2,Married,12061,26707,3,Y,No,17,3,3,80,1,19,2,3,10,8,0,1 +41.0,No,Non-Travel,267.0,Sales,10.0,2,Life Sciences,1,599,4,Male,56,3,2,Sales Executive,4,Single,6230,13430,7,Y,No,14,3,4,80,0,16,3,3,14,3,1,10 +29.0,No,Travel_Rarely,590.0,Research & Development,4.0,3,Technical Degree,1,1762,4,Female,91,2,1,Research Scientist,1,Divorced,2109,10007,1,Y,No,13,3,3,80,1,1,2,3,1,0,0,0 +45.0,No,Travel_Rarely,549.0,Research & Development,8.0,4,Other,1,452,4,Male,75,3,2,Research Scientist,4,Married,3697,9278,9,Y,No,14,3,1,80,2,12,3,3,10,9,9,8 +,No,Non-Travel,120.0,Sales,4.0,3,Medical,1,129,2,Male,43,3,2,Sales Executive,3,Married,4221,8863,1,Y,No,15,3,2,80,0,5,3,4,5,4,0,4 +29.0,No,Travel_Rarely,136.0,Research & Development,1.0,3,Life Sciences,1,1954,1,Male,89,3,2,Healthcare Representative,1,Married,5373,6225,0,Y,No,12,3,1,80,1,6,5,2,5,3,0,2 +42.0,No,Travel_Rarely,469.0,Research & Development,2.0,2,Medical,1,1109,4,Male,35,3,4,Manager,1,Married,17665,14399,0,Y,No,17,3,4,80,1,23,3,3,22,6,13,7 +48.0,No,Travel_Rarely,715.0,Research & Development,1.0,3,Life Sciences,1,1263,4,Male,76,2,5,Research Director,4,Single,18265,8733,6,Y,No,12,3,3,80,0,25,3,4,1,0,0,0 +20.0,Yes,Travel_Frequently,871.0,Research & Development,6.0,3,Life Sciences,1,137,4,Female,66,2,1,Laboratory Technician,4,Single,2926,19783,1,Y,Yes,18,3,2,80,0,1,5,3,1,0,1,0 +31.0,No,Travel_Rarely,1274.0,Research & Development,9.0,1,Life Sciences,1,581,3,Male,33,3,3,Manufacturing Director,2,Divorced,10648,14394,1,Y,No,25,4,4,80,1,13,6,4,13,8,0,8 +41.0,No,Non-Travel,552.0,Human Resources,4.0,3,Human Resources,1,1722,3,Male,60,1,2,Human Resources,2,Married,6430,20794,6,Y,No,19,3,2,80,1,10,4,3,3,2,1,2 +29.0,Yes,Travel_Rarely,350.0,Human Resources,13.0,3,Human Resources,1,1844,1,Male,56,2,1,Human Resources,1,Divorced,2335,3157,4,Y,Yes,15,3,4,80,3,4,3,3,2,2,2,0 +42.0,No,Travel_Rarely,647.0,Sales,4.0,4,Marketing,1,1171,2,Male,45,3,2,Sales Executive,1,Single,5155,2253,7,Y,No,13,3,4,80,0,9,3,4,6,4,1,5 +36.0,No,Travel_Rarely,1120.0,Sales,11.0,4,Marketing,1,2045,2,Female,100,2,2,Sales Executive,4,Married,6652,14369,4,Y,No,13,3,1,80,1,8,2,2,6,3,0,0 +,No,Travel_Rarely,1476.0,Research & Development,16.0,2,Medical,1,412,2,Male,68,4,2,Healthcare Representative,1,Single,5661,4824,0,Y,No,19,3,3,80,0,9,2,3,8,3,0,7 +32.0,Yes,Travel_Rarely,964.0,Sales,1.0,2,Life Sciences,1,1734,1,Male,34,1,2,Sales Executive,2,Single,6735,12147,6,Y,No,15,3,2,80,0,10,2,3,0,0,0,0 +36.0,No,Travel_Rarely,1351.0,Research & Development,26.0,4,Life Sciences,1,1682,1,Male,80,3,2,Healthcare Representative,3,Married,5347,7419,6,Y,No,14,3,2,80,2,10,2,2,3,2,0,2 +42.0,No,Travel_Rarely,201.0,Research & Development,1.0,4,Life Sciences,1,517,2,Female,95,3,1,Laboratory Technician,1,Divorced,2576,20490,3,Y,No,16,3,2,80,1,8,5,3,5,2,1,2 +43.0,No,Travel_Rarely,1034.0,Sales,16.0,3,Marketing,1,327,4,Female,80,3,4,Manager,4,Married,16064,7744,5,Y,Yes,22,4,3,80,1,22,3,3,17,13,1,9 +36.0,No,Travel_Rarely,530.0,Sales,2.0,4,Life Sciences,1,1710,3,Female,51,3,2,Sales Representative,4,Single,4502,7439,3,Y,No,15,3,3,80,0,17,2,2,13,7,6,7 +,No,Non-Travel,675.0,Research & Development,,2,Life Sciences,1,369,2,Male,85,4,2,Healthcare Representative,1,Divorced,4000,18384,1,Y,No,12,3,4,80,2,6,2,3,6,3,1,5 +36.0,No,Non-Travel,1105.0,Research & Development,24.0,4,Life Sciences,1,419,2,Female,47,3,2,Laboratory Technician,2,Married,5674,6927,7,Y,No,15,3,3,80,1,11,3,3,9,8,0,8 +36.0,No,Travel_Frequently,1467.0,Sales,11.0,2,Technical Degree,1,154,2,Female,92,3,3,Sales Executive,4,Married,9738,22952,0,Y,No,14,3,3,80,1,10,6,3,9,7,2,8 +38.0,No,Travel_Frequently,1189.0,Research & Development,1.0,3,Life Sciences,1,1668,4,Male,90,3,2,Research Scientist,4,Married,4735,9867,7,Y,No,15,3,4,80,2,19,4,4,13,11,2,9 +33.0,No,Travel_Rarely,1198.0,Research & Development,1.0,4,Other,1,939,3,Male,100,2,1,Research Scientist,1,Single,2799,3339,3,Y,Yes,11,3,2,80,0,6,1,3,3,2,0,2 +45.0,No,Travel_Frequently,1199.0,Research & Development,7.0,4,Life Sciences,1,341,1,Male,77,4,2,Manufacturing Director,3,Married,6434,5118,4,Y,No,17,3,4,80,1,9,1,3,3,2,0,2 +27.0,No,Travel_Rarely,511.0,Sales,2.0,2,Medical,1,1898,1,Female,89,4,2,Sales Executive,3,Single,6500,26997,0,Y,No,14,3,2,80,0,9,5,2,8,7,0,7 +34.0,Yes,Travel_Rarely,790.0,Sales,24.0,4,Medical,1,1489,1,Female,40,2,2,Sales Executive,2,Single,4599,7815,0,Y,Yes,23,4,3,80,0,16,2,4,15,9,10,10 +29.0,No,Travel_Rarely,1328.0,Research & Development,2.0,3,Life Sciences,1,94,3,Male,76,3,1,Research Scientist,2,Married,2703,4956,0,Y,No,23,4,4,80,1,6,3,3,5,4,0,4 +32.0,No,Travel_Rarely,1093.0,Sales,6.0,4,Medical,1,125,2,Male,87,3,2,Sales Executive,3,Single,5010,24301,1,Y,No,16,3,1,80,0,12,0,3,11,8,5,7 +46.0,No,Travel_Rarely,406.0,Sales,,1,Marketing,1,1124,1,Male,52,3,4,Manager,3,Married,17465,15596,3,Y,No,12,3,4,80,1,23,3,3,12,9,4,9 +39.0,Yes,Travel_Rarely,895.0,Sales,,3,Technical Degree,1,42,4,Male,56,3,2,Sales Representative,4,Married,2086,3335,3,Y,No,14,3,3,80,1,19,6,4,1,0,0,0 +44.0,No,Travel_Rarely,136.0,Research & Development,28.0,3,Life Sciences,1,1523,4,Male,32,3,4,Research Director,1,Married,16328,22074,3,Y,No,13,3,3,80,1,24,1,4,20,6,14,17 +40.0,No,Travel_Rarely,302.0,Research & Development,6.0,3,Life Sciences,1,601,2,Female,75,3,4,Manufacturing Director,3,Single,13237,20364,7,Y,No,15,3,3,80,0,22,3,3,20,6,5,13 +55.0,No,Travel_Rarely,1117.0,Sales,18.0,5,Life Sciences,1,597,1,Female,83,3,4,Manager,2,Single,16835,9873,3,Y,No,23,4,4,80,0,37,2,3,10,9,7,7 +41.0,No,Travel_Frequently,840.0,Research & Development,9.0,3,Medical,1,999,1,Male,64,3,5,Research Director,3,Divorced,19419,3735,2,Y,No,17,3,2,80,1,21,2,4,18,16,0,11 +43.0,Yes,Travel_Rarely,,Sales,9.0,3,Marketing,1,1188,1,Female,85,1,2,Sales Executive,3,Single,5346,9489,8,Y,No,13,3,2,80,0,7,2,2,4,3,1,3 +38.0,No,Travel_Rarely,437.0,Sales,16.0,3,Life Sciences,1,1583,2,Female,90,3,2,Sales Executive,2,Single,4198,16379,2,Y,No,12,3,2,80,0,8,5,4,3,2,1,2 +29.0,Yes,Travel_Rarely,428.0,Sales,9.0,3,Marketing,1,1752,2,Female,52,1,1,Sales Representative,2,Single,2760,14630,1,Y,No,13,3,3,80,0,2,3,3,2,2,2,2 +,No,Travel_Rarely,652.0,Research & Development,7.0,3,Other,1,1417,3,Male,100,4,1,Laboratory Technician,1,Single,3578,23577,0,Y,No,12,3,4,80,0,8,2,3,7,7,0,7 +45.0,No,Travel_Rarely,193.0,Research & Development,6.0,4,Other,1,101,4,Male,52,3,3,Research Director,1,Married,13245,15067,4,Y,Yes,14,3,2,80,0,17,3,4,0,0,0,0 +34.0,No,Travel_Rarely,1153.0,Research & Development,1.0,2,Medical,1,110,1,Male,94,3,2,Manufacturing Director,2,Married,4325,17736,1,Y,No,15,3,3,80,0,5,2,3,5,2,1,3 +38.0,No,Travel_Frequently,693.0,Research & Development,7.0,3,Life Sciences,1,1382,4,Male,57,4,1,Research Scientist,3,Divorced,2610,15748,1,Y,No,11,3,4,80,3,4,2,3,4,2,0,3 +55.0,No,Travel_Rarely,111.0,Sales,1.0,2,Life Sciences,1,106,1,Male,70,3,3,Sales Executive,4,Married,10239,18092,3,Y,No,14,3,4,80,1,24,4,3,1,0,1,0 +18.0,Yes,Travel_Frequently,1306.0,Sales,,3,Marketing,1,614,2,Male,69,3,1,Sales Representative,2,Single,1878,8059,1,Y,Yes,14,3,4,80,0,0,3,3,0,0,0,0 +40.0,No,Travel_Rarely,884.0,Research & Development,15.0,3,Life Sciences,1,1628,1,Female,80,2,3,Manufacturing Director,3,Married,10435,25800,1,Y,No,13,3,4,80,2,18,2,3,18,15,14,12 +,No,Travel_Rarely,1137.0,Research & Development,21.0,1,Life Sciences,1,942,4,Female,51,3,2,Healthcare Representative,4,Married,4014,19170,1,Y,Yes,25,4,4,80,1,10,2,1,10,6,0,7 +,No,Non-Travel,1476.0,Research & Development,1.0,3,Life Sciences,1,1315,3,Female,55,1,2,Laboratory Technician,4,Married,6674,16392,0,Y,No,11,3,1,80,3,10,6,3,9,8,7,5 +20.0,No,Travel_Rarely,727.0,Sales,9.0,1,Life Sciences,1,1680,4,Male,54,3,1,Sales Representative,1,Single,2728,21082,1,Y,No,11,3,1,80,0,2,3,3,2,2,0,2 +33.0,Yes,Travel_Rarely,587.0,Research & Development,10.0,1,Medical,1,584,1,Male,38,1,1,Laboratory Technician,4,Divorced,3408,6705,7,Y,No,13,3,1,80,3,8,2,3,4,3,1,3 +31.0,No,Travel_Rarely,1222.0,Research & Development,11.0,4,Life Sciences,1,895,4,Male,48,3,1,Research Scientist,4,Married,2356,14871,3,Y,Yes,19,3,2,80,1,8,2,3,6,4,0,2 +40.0,No,Travel_Rarely,1492.0,Research & Development,20.0,4,Technical Degree,1,1092,1,Male,61,3,3,Healthcare Representative,4,Married,10322,26542,4,Y,No,20,4,4,80,1,14,6,3,11,10,11,1 +50.0,No,Travel_Frequently,1421.0,Research & Development,2.0,3,Medical,1,1215,4,Female,30,3,4,Manager,1,Married,17856,9490,2,Y,No,22,4,3,80,1,32,3,3,2,2,2,2 +27.0,No,Travel_Frequently,591.0,Research & Development,2.0,3,Medical,1,1648,4,Male,87,3,1,Research Scientist,4,Single,2580,6297,2,Y,No,13,3,3,80,0,6,0,2,4,2,1,2 +,No,Travel_Rarely,1300.0,Research & Development,17.0,2,Medical,1,536,3,Male,79,3,2,Laboratory Technician,1,Divorced,4558,13535,1,Y,No,12,3,4,80,1,10,2,3,10,0,1,8 +36.0,No,Travel_Rarely,1383.0,Research & Development,10.0,3,Life Sciences,1,1790,4,Male,90,3,3,Healthcare Representative,1,Married,8321,25949,7,Y,Yes,13,3,4,80,1,15,1,3,12,8,5,7 +53.0,No,Travel_Rarely,447.0,Research & Development,2.0,3,Medical,1,1472,4,Male,39,4,4,Research Director,2,Single,16598,19764,4,Y,No,12,3,2,80,0,35,2,2,9,8,8,8 +42.0,No,Travel_Rarely,1128.0,Research & Development,13.0,3,Medical,1,1803,2,Male,95,4,2,Healthcare Representative,1,Married,5538,5696,5,Y,No,18,3,3,80,2,10,2,2,0,0,0,0 +37.0,No,Non-Travel,1040.0,Research & Development,2.0,2,Life Sciences,1,139,3,Male,100,2,2,Healthcare Representative,4,Divorced,5163,15850,5,Y,No,14,3,4,80,1,17,2,4,1,0,0,0 +43.0,No,Travel_Rarely,589.0,Research & Development,14.0,2,Life Sciences,1,843,2,Male,94,3,4,Research Director,1,Married,17159,5200,6,Y,No,24,4,3,80,1,22,3,3,4,1,1,0 +23.0,No,Travel_Rarely,373.0,Research & Development,1.0,2,Life Sciences,1,1270,4,Male,47,3,1,Research Scientist,3,Married,1223,16901,1,Y,No,22,4,4,80,1,1,2,3,1,0,0,1 +52.0,No,Travel_Rarely,258.0,Research & Development,8.0,4,Other,1,1409,3,Female,54,3,1,Laboratory Technician,1,Married,2950,17363,9,Y,No,13,3,3,80,0,12,2,1,5,4,0,4 +29.0,No,Travel_Rarely,1010.0,Research & Development,1.0,3,Life Sciences,1,1249,1,Female,97,3,1,Research Scientist,4,Divorced,3760,5598,1,Y,No,15,3,1,80,3,3,5,3,3,2,1,2 +50.0,No,Travel_Rarely,989.0,Research & Development,7.0,2,Medical,1,80,2,Female,43,2,5,Research Director,3,Divorced,18740,16701,5,Y,Yes,12,3,4,80,1,29,2,2,27,3,13,8 +42.0,No,Travel_Rarely,635.0,Sales,1.0,1,Life Sciences,1,387,2,Male,99,3,2,Sales Executive,3,Married,4907,24532,1,Y,No,25,4,3,80,0,20,3,3,20,16,11,6 +34.0,No,Travel_Rarely,628.0,Research & Development,8.0,3,Medical,1,2068,2,Male,82,4,2,Laboratory Technician,3,Married,4404,10228,2,Y,No,12,3,1,80,0,6,3,4,4,3,1,2 +32.0,No,,1401.0,Sales,4.0,2,Life Sciences,1,330,3,Female,56,3,1,Sales Representative,2,Married,3931,20990,2,Y,No,11,3,1,80,1,6,5,3,4,3,1,2 +38.0,No,Travel_Rarely,119.0,Sales,,3,Life Sciences,1,307,1,Male,76,3,3,Sales Executive,3,Divorced,10609,9647,0,Y,No,12,3,3,80,2,17,6,2,16,10,5,13 +30.0,No,Travel_Rarely,201.0,Research & Development,,3,Technical Degree,1,197,4,Female,84,3,1,Research Scientist,1,Divorced,3204,10415,5,Y,No,14,3,4,80,1,8,3,3,3,2,2,2 +56.0,No,Travel_Rarely,,Sales,11.0,5,Marketing,1,1935,4,Female,89,2,2,Sales Executive,1,Married,5380,20328,4,Y,No,16,3,3,80,1,6,3,3,0,0,0,0 +27.0,No,Travel_Rarely,1469.0,Research & Development,1.0,2,Medical,1,497,4,Male,82,3,1,Laboratory Technician,2,Divorced,3816,17881,1,Y,No,11,3,2,80,1,5,2,3,5,2,0,4 +36.0,No,Travel_Rarely,922.0,Research & Development,,2,Life Sciences,1,155,1,Female,39,3,1,Laboratory Technician,4,Divorced,2835,2561,5,Y,No,22,4,1,80,1,7,2,3,1,0,0,0 +40.0,No,,616.0,Research & Development,2.0,2,Life Sciences,1,1802,3,Female,99,3,1,Laboratory Technician,1,Married,3377,25605,4,Y,No,17,3,4,80,1,7,5,2,4,3,0,2 +37.0,Yes,Travel_Frequently,504.0,Research & Development,10.0,3,Medical,1,342,1,Male,61,3,3,Manufacturing Director,3,Divorced,10048,22573,6,Y,No,11,3,2,80,2,17,5,3,1,0,0,0 +33.0,No,Non-Travel,1313.0,Research & Development,1.0,2,Medical,1,1994,2,Male,59,2,1,Laboratory Technician,3,Divorced,2008,20439,1,Y,No,12,3,3,80,3,1,2,2,1,1,0,0 +36.0,No,Travel_Rarely,1299.0,Research & Development,27.0,3,Medical,1,13,3,Male,94,3,2,Healthcare Representative,3,Married,5237,16577,6,Y,No,13,3,2,80,2,17,3,2,7,7,7,7 +39.0,No,Travel_Frequently,443.0,Research & Development,8.0,1,Life Sciences,1,602,3,Female,48,3,1,Laboratory Technician,3,Married,3755,17872,1,Y,No,11,3,1,80,1,8,3,3,8,3,0,7 +36.0,No,Non-Travel,1229.0,Sales,8.0,4,Technical Degree,1,990,1,Male,84,3,2,Sales Executive,4,Divorced,5079,25952,4,Y,No,13,3,4,80,2,12,3,3,7,7,0,7 +,No,Travel_Rarely,,Research & Development,1.0,3,Life Sciences,1,350,1,Female,62,3,2,Manufacturing Director,3,Married,4898,7505,0,Y,No,12,3,4,80,2,5,3,3,4,2,1,2 +36.0,No,Travel_Rarely,676.0,Research & Development,1.0,3,Other,1,823,3,Female,35,3,2,Manufacturing Director,2,Married,5228,23361,0,Y,No,15,3,1,80,1,10,2,3,9,7,0,5 +37.0,No,Travel_Rarely,1305.0,Research & Development,10.0,4,Life Sciences,1,518,3,Male,49,3,2,Manufacturing Director,2,Single,4197,21123,2,Y,Yes,12,3,4,80,0,18,2,2,1,0,0,1 +51.0,No,Travel_Frequently,237.0,Sales,9.0,3,Life Sciences,1,1282,4,Male,83,3,5,Manager,2,Divorced,19847,19196,4,Y,Yes,24,4,1,80,1,31,5,2,29,10,11,10 +49.0,No,Travel_Rarely,301.0,Research & Development,22.0,4,Other,1,1655,1,Female,72,3,4,Research Director,2,Married,16413,3498,3,Y,No,16,3,2,80,2,27,2,3,4,2,1,2 +,No,Non-Travel,1225.0,Research & Development,2.0,4,Life Sciences,1,771,4,Female,61,3,2,Healthcare Representative,1,Divorced,5093,4761,2,Y,No,11,3,1,80,1,16,2,4,1,0,0,0 +43.0,Yes,Travel_Frequently,807.0,Research & Development,17.0,3,Technical Degree,1,1767,3,Male,38,2,1,Research Scientist,3,Married,2437,15587,9,Y,Yes,16,3,4,80,1,6,4,3,1,0,0,0 +33.0,No,Travel_Frequently,970.0,Sales,7.0,3,Life Sciences,1,1114,4,Female,30,3,2,Sales Executive,2,Married,4302,13401,0,Y,No,17,3,3,80,1,4,3,3,3,2,0,2 +,No,Travel_Rarely,775.0,Sales,29.0,2,Medical,1,618,1,Male,45,3,2,Sales Executive,3,Divorced,4306,4267,5,Y,No,12,3,1,80,2,8,5,3,0,0,0,0 +46.0,No,Travel_Rarely,566.0,Research & Development,7.0,2,Medical,1,1007,4,Male,75,3,3,Manufacturing Director,3,Divorced,10845,24208,6,Y,No,13,3,2,80,1,13,3,3,8,7,0,7 +56.0,Yes,Travel_Rarely,1162.0,Research & Development,24.0,2,Life Sciences,1,1907,1,Male,97,3,1,Laboratory Technician,4,Single,2587,10261,1,Y,No,16,3,4,80,0,5,3,3,4,2,1,0 +32.0,No,Travel_Frequently,689.0,Sales,9.0,2,Medical,1,195,4,Male,35,1,2,Sales Executive,4,Divorced,4668,22812,0,Y,No,17,3,4,80,3,9,2,4,8,7,0,7 +30.0,No,Travel_Frequently,160.0,Research & Development,,3,Medical,1,680,3,Female,71,3,1,Research Scientist,3,Divorced,2083,22653,1,Y,No,20,4,3,80,1,1,2,3,1,0,0,0 +30.0,Yes,Travel_Rarely,740.0,Sales,1.0,3,Life Sciences,1,1562,2,Male,64,2,2,Sales Executive,1,Married,9714,5323,1,Y,No,11,3,4,80,1,10,4,3,10,8,6,7 +27.0,No,Travel_Rarely,1055.0,Research & Development,2.0,4,Life Sciences,1,1027,1,Female,47,3,2,Manufacturing Director,4,Married,4227,4658,0,Y,No,18,3,2,80,1,4,2,3,3,2,2,2 +42.0,No,Travel_Rarely,1396.0,Research & Development,6.0,3,Medical,1,1911,3,Male,83,3,3,Research Director,1,Married,13348,14842,9,Y,No,13,3,2,80,1,18,3,4,13,7,5,7 +20.0,Yes,Travel_Rarely,1097.0,Research & Development,11.0,3,Medical,1,1016,4,Female,98,2,1,Research Scientist,1,Single,2600,18275,1,Y,Yes,15,3,1,80,0,1,2,3,1,0,0,0 +50.0,No,Travel_Rarely,316.0,Sales,8.0,4,Marketing,1,738,4,Male,54,3,1,Sales Representative,2,Married,3875,9983,7,Y,No,15,3,4,80,1,4,2,3,2,2,2,2 +19.0,Yes,Travel_Rarely,303.0,Research & Development,2.0,3,Life Sciences,1,243,2,Male,47,2,1,Laboratory Technician,4,Single,1102,9241,1,Y,No,22,4,3,80,0,1,3,2,1,0,1,0 +31.0,No,Travel_Rarely,1154.0,Sales,2.0,2,Life Sciences,1,1996,1,Male,54,3,1,Sales Representative,3,Married,3067,6393,0,Y,No,19,3,3,80,1,3,1,3,2,2,1,2 +29.0,No,Travel_Frequently,1404.0,Sales,20.0,3,Technical Degree,1,974,3,Female,84,3,1,Sales Representative,4,Married,2157,18203,1,Y,No,15,3,2,80,1,3,5,3,3,1,0,2 +42.0,No,Travel_Rarely,1142.0,Research & Development,8.0,3,Life Sciences,1,1860,4,Male,81,3,1,Laboratory Technician,3,Single,3968,13624,4,Y,No,13,3,4,80,0,8,3,3,0,0,0,0 +36.0,No,Travel_Rarely,1266.0,Sales,10.0,4,Technical Degree,1,1880,2,Female,63,2,2,Sales Executive,3,Married,5673,6060,1,Y,Yes,13,3,1,80,1,10,4,3,10,9,1,7 +42.0,Yes,Travel_Frequently,481.0,Sales,12.0,3,Life Sciences,1,1167,3,Male,44,3,4,Sales Executive,1,Single,13758,2447,0,Y,Yes,12,3,2,80,0,22,2,2,21,9,13,14 +46.0,No,Travel_Rarely,1402.0,Sales,2.0,3,Marketing,1,1204,3,Female,69,3,4,Manager,1,Married,17048,24097,8,Y,No,23,4,1,80,0,28,2,3,26,15,15,9 +39.0,No,Travel_Rarely,722.0,Sales,24.0,1,Marketing,1,2056,2,Female,60,2,4,Sales Executive,4,Married,12031,8828,0,Y,No,11,3,1,80,1,21,2,2,20,9,9,6 +30.0,No,Travel_Rarely,1358.0,Research & Development,24.0,1,Life Sciences,1,11,4,Male,67,3,1,Laboratory Technician,3,Divorced,2693,13335,1,Y,No,22,4,2,80,1,1,2,3,1,0,0,0 +36.0,No,Travel_Rarely,172.0,Research & Development,4.0,4,Life Sciences,1,1435,1,Male,37,2,2,Laboratory Technician,4,Single,5810,22604,1,Y,No,16,3,3,80,0,10,2,2,10,4,1,8 +41.0,Yes,Travel_Rarely,1085.0,Research & Development,2.0,4,Life Sciences,1,927,2,Female,57,1,1,Laboratory Technician,4,Divorced,2778,17725,4,Y,Yes,13,3,3,80,1,10,1,2,7,7,1,0 +22.0,No,Non-Travel,457.0,Research & Development,26.0,2,Other,1,1605,2,Female,85,2,1,Research Scientist,3,Married,2814,10293,1,Y,Yes,14,3,2,80,0,4,2,2,4,2,1,3 +21.0,Yes,Travel_Frequently,756.0,Sales,1.0,1,Technical Degree,1,478,1,Female,99,2,1,Sales Representative,2,Single,2174,9150,1,Y,Yes,11,3,3,80,0,3,3,3,3,2,1,2 +41.0,No,Travel_Rarely,509.0,Research & Development,7.0,2,Technical Degree,1,1085,2,Female,43,4,1,Research Scientist,3,Married,3376,18863,1,Y,No,13,3,3,80,0,10,3,3,10,6,0,8 +,No,Travel_Rarely,992.0,Research & Development,1.0,3,Medical,1,1564,4,Male,68,2,1,Laboratory Technician,1,Single,2450,21731,1,Y,No,19,3,2,80,0,3,3,3,3,0,1,2 +47.0,No,Travel_Rarely,1482.0,Research & Development,,5,Life Sciences,1,447,4,Male,42,3,5,Research Director,3,Married,18300,16375,4,Y,No,11,3,2,80,1,21,2,3,3,2,1,1 +45.0,No,Travel_Rarely,,Research & Development,20.0,3,Medical,1,1460,2,Male,95,1,3,Healthcare Representative,1,Divorced,10851,19863,2,Y,Yes,18,3,2,80,1,24,2,3,7,7,0,7 +29.0,No,Travel_Frequently,995.0,Research & Development,2.0,1,Life Sciences,1,1590,1,Male,87,3,2,Healthcare Representative,4,Divorced,8853,24483,1,Y,No,19,3,4,80,1,6,0,4,6,4,1,3 +,No,Travel_Rarely,1167.0,Sales,,3,Other,1,2060,4,Female,30,2,1,Sales Representative,3,Single,2966,21378,0,Y,No,18,3,4,80,0,5,2,3,4,2,0,0 +51.0,No,Travel_Rarely,833.0,Research & Development,1.0,3,Life Sciences,1,353,3,Male,96,3,1,Research Scientist,4,Married,2723,23231,1,Y,No,11,3,2,80,0,1,0,2,1,0,0,0 +34.0,No,Travel_Frequently,735.0,Research & Development,22.0,4,Other,1,1932,3,Male,86,2,2,Research Scientist,4,Married,5747,26496,1,Y,Yes,15,3,2,80,0,16,3,3,15,10,6,11 +,No,Travel_Rarely,755.0,Research & Development,9.0,4,Life Sciences,1,496,3,Male,97,2,2,Healthcare Representative,2,Single,6540,19394,9,Y,No,19,3,3,80,0,10,5,3,1,1,0,0 +40.0,Yes,Travel_Rarely,676.0,Research & Development,9.0,4,Life Sciences,1,1534,4,Male,86,3,1,Laboratory Technician,1,Single,2018,21831,3,Y,No,14,3,2,80,0,15,3,1,5,4,1,0 +42.0,No,Travel_Frequently,458.0,Research & Development,26.0,5,Medical,1,1242,1,Female,60,3,3,Research Director,1,Married,13191,23281,3,Y,Yes,17,3,3,80,0,20,6,3,1,0,0,0 +38.0,No,Travel_Rarely,364.0,Research & Development,,5,Technical Degree,1,193,4,Female,32,3,2,Research Scientist,3,Single,4317,2302,3,Y,Yes,20,4,2,80,0,19,2,3,3,2,2,2 +24.0,Yes,Travel_Rarely,693.0,Sales,,2,Life Sciences,1,720,1,Female,65,3,2,Sales Executive,3,Single,4577,24785,9,Y,No,14,3,1,80,0,4,3,3,2,2,2,0 +39.0,No,Travel_Rarely,1462.0,Sales,6.0,3,Medical,1,1588,4,Male,38,4,3,Sales Executive,3,Married,8237,4658,2,Y,No,11,3,1,80,1,11,3,3,7,6,7,6 +40.0,No,Travel_Rarely,329.0,Research & Development,1.0,4,Life Sciences,1,1361,2,Male,88,3,1,Laboratory Technician,2,Married,2387,6762,3,Y,No,22,4,3,80,1,7,3,3,4,2,0,3 +45.0,No,Travel_Rarely,538.0,Research & Development,1.0,4,Technical Degree,1,1553,1,Male,66,3,3,Healthcare Representative,2,Divorced,7441,20933,1,Y,No,12,3,1,80,3,10,4,3,10,8,7,7 +40.0,No,Travel_Rarely,1194.0,Research & Development,2.0,4,Medical,1,2051,3,Female,98,3,1,Research Scientist,3,Married,2001,12549,2,Y,No,14,3,2,80,3,20,2,3,5,3,0,2 +34.0,Yes,Travel_Frequently,988.0,Human Resources,23.0,3,Human Resources,1,590,2,Female,43,3,3,Human Resources,1,Divorced,9950,11533,9,Y,Yes,15,3,3,80,3,11,2,3,3,2,0,2 +32.0,No,Travel_Rarely,1018.0,Research & Development,,2,Life Sciences,1,727,3,Female,39,3,3,Research Director,4,Single,11159,19373,3,Y,No,15,3,4,80,0,10,6,3,7,7,7,7 +50.0,No,Travel_Rarely,813.0,Research & Development,17.0,5,Life Sciences,1,1656,4,Female,50,2,3,Research Director,1,Divorced,13269,21981,5,Y,No,15,3,3,80,3,19,3,3,14,11,1,11 +37.0,No,Travel_Frequently,319.0,Sales,4.0,4,Marketing,1,311,1,Male,41,3,1,Sales Representative,4,Divorced,2793,2539,4,Y,No,17,3,3,80,1,13,2,3,9,8,5,8 +29.0,Yes,Travel_Frequently,337.0,Research & Development,14.0,1,Other,1,1421,3,Female,84,3,3,Healthcare Representative,4,Single,7553,22930,0,Y,Yes,12,3,1,80,0,9,1,3,8,7,7,7 +,No,Travel_Frequently,944.0,Sales,1.0,3,Marketing,1,314,3,Female,92,3,3,Sales Executive,3,Single,8789,9096,1,Y,No,14,3,1,80,0,10,3,4,10,7,0,8 +31.0,No,Travel_Frequently,1125.0,Sales,7.0,4,Marketing,1,1833,1,Female,68,3,3,Sales Executive,1,Married,9637,8277,2,Y,No,14,3,4,80,2,9,3,3,3,2,2,2 +38.0,No,Travel_Rarely,1153.0,Research & Development,6.0,2,Other,1,1782,4,Female,40,2,1,Laboratory Technician,3,Married,3702,16376,1,Y,No,11,3,2,80,1,5,3,3,5,4,0,4 +27.0,No,Travel_Frequently,1242.0,Sales,20.0,3,Life Sciences,1,293,4,Female,90,3,2,Sales Executive,3,Single,9981,12916,1,Y,No,14,3,4,80,0,7,2,3,7,7,0,7 +46.0,No,Travel_Rarely,945.0,Human Resources,,2,Medical,1,103,2,Male,80,3,2,Human Resources,2,Divorced,5021,10425,8,Y,Yes,22,4,4,80,1,16,2,3,4,2,0,2 +41.0,No,Travel_Rarely,933.0,Research & Development,9.0,4,Life Sciences,1,200,3,Male,94,3,1,Laboratory Technician,1,Married,2238,6961,2,Y,No,21,4,4,80,1,7,2,3,5,0,1,4 +40.0,No,Travel_Rarely,1308.0,Research & Development,14.0,3,Medical,1,1128,3,Male,44,2,5,Research Director,3,Single,19626,17544,1,Y,No,14,3,1,80,0,21,2,4,20,7,4,9 +30.0,No,Travel_Rarely,1329.0,Sales,29.0,4,Life Sciences,1,1211,3,Male,61,3,2,Sales Executive,1,Divorced,4115,13192,8,Y,No,19,3,3,80,3,8,3,3,4,3,0,3 +30.0,No,Travel_Rarely,853.0,Research & Development,7.0,4,Life Sciences,1,1224,3,Male,49,3,2,Laboratory Technician,3,Divorced,3491,11309,1,Y,No,13,3,1,80,3,10,4,2,10,7,8,9 +34.0,No,Travel_Rarely,546.0,Research & Development,10.0,3,Life Sciences,1,934,2,Male,83,3,1,Laboratory Technician,2,Divorced,2008,6896,1,Y,No,14,3,2,80,2,1,3,3,1,0,1,0 +40.0,No,Travel_Rarely,118.0,Sales,14.0,2,Life Sciences,1,1598,4,Female,84,3,2,Sales Executive,1,Married,4639,11262,1,Y,No,15,3,3,80,1,5,2,3,5,4,1,2 +29.0,No,Travel_Rarely,1090.0,Sales,10.0,3,Marketing,1,766,4,Male,83,3,1,Sales Representative,2,Divorced,2297,17967,1,Y,No,14,3,4,80,2,2,2,3,2,2,2,2 +46.0,No,Travel_Rarely,1450.0,Research & Development,15.0,2,Life Sciences,1,1217,4,Male,52,3,5,Research Director,2,Married,19081,10849,5,Y,No,11,3,1,80,1,25,2,3,4,2,0,3 +41.0,No,Travel_Rarely,802.0,Sales,9.0,1,Life Sciences,1,176,3,Male,96,3,3,Sales Executive,3,Divorced,8189,21196,3,Y,Yes,13,3,3,80,1,12,2,3,9,7,0,7 +39.0,No,Non-Travel,1251.0,Sales,21.0,4,Life Sciences,1,1929,1,Female,32,1,2,Sales Executive,3,Married,5736,3987,6,Y,No,19,3,3,80,1,10,1,3,3,2,1,2 +29.0,No,Travel_Frequently,490.0,Research & Development,10.0,3,Life Sciences,1,1143,4,Female,61,3,1,Research Scientist,2,Divorced,3291,17940,0,Y,No,14,3,4,80,2,8,2,2,7,5,1,1 +52.0,No,Travel_Rarely,1490.0,Research & Development,4.0,2,Life Sciences,1,546,4,Female,30,3,4,Manager,4,Married,16555,10310,2,Y,No,13,3,4,80,0,31,2,1,5,2,1,4 +37.0,No,Travel_Rarely,1439.0,Research & Development,4.0,1,Life Sciences,1,1394,3,Male,54,3,1,Research Scientist,3,Married,2996,5182,7,Y,Yes,15,3,4,80,0,8,2,3,6,4,1,3 +29.0,No,Travel_Rarely,1176.0,Sales,,2,Medical,1,690,2,Female,62,3,2,Sales Executive,3,Married,5561,3487,1,Y,No,14,3,1,80,1,6,5,2,6,0,1,2 +44.0,No,Travel_Rarely,528.0,Human Resources,1.0,3,Life Sciences,1,1683,3,Female,44,3,1,Human Resources,4,Divorced,3195,4167,4,Y,Yes,18,3,1,80,3,8,2,3,2,2,2,2 +45.0,Yes,Travel_Frequently,306.0,Sales,26.0,4,Life Sciences,1,684,1,Female,100,3,2,Sales Executive,1,Married,4286,5630,2,Y,No,14,3,4,80,2,5,4,3,1,1,0,0 +,No,Travel_Rarely,,Sales,18.0,1,Life Sciences,1,1399,1,Male,93,4,2,Sales Executive,3,Married,6232,12477,2,Y,No,11,3,2,80,0,6,3,2,3,2,1,2 +47.0,No,Travel_Frequently,1309.0,Sales,4.0,1,Medical,1,467,2,Male,99,3,2,Sales Representative,3,Single,2976,25751,3,Y,No,19,3,1,80,0,5,3,3,0,0,0,0 +37.0,No,Travel_Rarely,1107.0,Research & Development,14.0,3,Life Sciences,1,515,4,Female,95,3,1,Laboratory Technician,1,Divorced,3034,26914,1,Y,No,12,3,3,80,1,18,2,2,18,7,12,17 +41.0,Yes,Travel_Rarely,1102.0,Sales,1.0,2,Life Sciences,1,1,2,Female,94,3,2,Sales Executive,4,Single,5993,19479,8,Y,Yes,11,3,1,80,0,8,0,1,6,4,0,5 +57.0,No,Travel_Rarely,593.0,Research & Development,1.0,4,Medical,1,482,4,Male,88,3,2,Healthcare Representative,3,Married,6755,2967,2,Y,No,11,3,3,80,0,15,2,3,3,2,1,2 +18.0,Yes,Non-Travel,247.0,Research & Development,8.0,1,Medical,1,1156,3,Male,80,3,1,Laboratory Technician,3,Single,1904,13556,1,Y,No,12,3,4,80,0,0,0,3,0,0,0,0 +32.0,No,Non-Travel,1146.0,Research & Development,15.0,4,Medical,1,1955,3,Female,34,3,2,Healthcare Representative,4,Divorced,6667,16542,5,Y,No,18,3,2,80,1,9,6,3,5,1,1,2 +,No,Travel_Rarely,703.0,Sales,28.0,2,Marketing,1,641,1,Male,66,3,2,Sales Executive,2,Married,6272,7428,1,Y,No,20,4,4,80,2,6,5,4,5,3,1,4 +33.0,Yes,Travel_Rarely,211.0,Sales,16.0,3,Life Sciences,1,1758,1,Female,74,3,3,Sales Executive,1,Single,8564,10092,2,Y,Yes,20,4,3,80,0,11,2,2,0,0,0,0 +,No,Travel_Rarely,1142.0,Research & Development,23.0,4,Medical,1,75,3,Female,30,3,1,Laboratory Technician,1,Married,4014,16002,3,Y,Yes,15,3,3,80,1,4,3,3,2,2,2,2 +32.0,No,Non-Travel,300.0,Research & Development,1.0,3,Life Sciences,1,882,4,Male,61,3,1,Laboratory Technician,4,Divorced,2314,9148,0,Y,No,12,3,2,80,1,4,2,3,3,0,0,2 +,Yes,Travel_Rarely,303.0,Sales,27.0,3,Life Sciences,1,1797,3,Male,84,3,2,Sales Executive,4,Single,5813,13492,1,Y,Yes,18,3,4,80,0,10,2,3,10,7,7,7 +39.0,Yes,Non-Travel,592.0,Research & Development,2.0,3,Life Sciences,1,1458,1,Female,54,2,1,Laboratory Technician,1,Single,3646,17181,2,Y,Yes,23,4,2,80,0,11,2,4,1,0,0,0 +58.0,Yes,Travel_Rarely,601.0,Research & Development,7.0,4,Medical,1,1360,3,Female,53,2,3,Manufacturing Director,1,Married,10008,12023,7,Y,Yes,14,3,4,80,0,31,0,2,10,9,5,9 +36.0,No,Travel_Frequently,1480.0,Research & Development,,2,Medical,1,238,4,Male,30,3,1,Laboratory Technician,2,Single,2088,15062,4,Y,No,12,3,3,80,0,13,3,2,8,7,7,2 +31.0,No,Travel_Rarely,828.0,Sales,2.0,1,Life Sciences,1,604,2,Male,77,3,2,Sales Executive,4,Single,6582,8346,4,Y,Yes,13,3,3,80,0,10,2,4,6,5,0,5 +,No,Travel_Rarely,841.0,Research & Development,6.0,3,Other,1,164,3,Female,46,2,1,Research Scientist,2,Married,2368,23300,1,Y,No,19,3,3,80,0,5,3,2,5,4,4,3 +39.0,Yes,Travel_Rarely,360.0,Research & Development,23.0,3,Medical,1,1310,3,Male,93,3,1,Research Scientist,1,Single,3904,22154,0,Y,No,13,3,1,80,0,6,2,3,5,2,0,3 +27.0,No,Travel_Rarely,608.0,Research & Development,1.0,2,Life Sciences,1,725,3,Female,68,3,3,Manufacturing Director,1,Married,7412,6009,1,Y,No,11,3,4,80,0,9,3,3,9,7,0,7 +44.0,Yes,Travel_Rarely,1097.0,Research & Development,10.0,4,Life Sciences,1,1200,3,Male,96,3,1,Research Scientist,3,Single,2936,10826,1,Y,Yes,11,3,3,80,0,6,4,3,6,4,0,2 +45.0,No,Travel_Rarely,974.0,Research & Development,1.0,4,Medical,1,996,4,Female,91,3,1,Laboratory Technician,4,Divorced,2270,11005,3,Y,No,14,3,4,80,2,8,2,3,5,3,0,2 +40.0,No,Travel_Frequently,530.0,Research & Development,1.0,4,Life Sciences,1,119,3,Male,78,2,4,Healthcare Representative,2,Married,13503,14115,1,Y,No,22,4,4,80,1,22,3,2,22,3,11,11 +47.0,No,Non-Travel,1162.0,Research & Development,1.0,1,Medical,1,2000,3,Female,98,3,3,Research Director,2,Married,11957,17231,0,Y,No,18,3,1,80,2,14,3,1,13,8,5,12 +34.0,No,Travel_Rarely,629.0,Research & Development,27.0,2,Medical,1,247,4,Female,95,3,1,Research Scientist,2,Single,2311,5711,2,Y,No,15,3,4,80,0,9,3,3,3,2,1,2 +44.0,No,Travel_Rarely,200.0,Research & Development,29.0,4,Other,1,1225,4,Male,32,3,2,Research Scientist,4,Single,4541,7744,1,Y,No,25,4,2,80,0,20,3,3,20,11,13,17 +36.0,No,Travel_Frequently,607.0,Sales,7.0,3,Marketing,1,1362,1,Female,83,4,2,Sales Executive,1,Married,4639,2261,2,Y,No,16,3,4,80,1,17,2,2,15,7,6,13 +27.0,No,Non-Travel,1277.0,Research & Development,8.0,5,Life Sciences,1,1094,1,Male,87,1,1,Laboratory Technician,3,Married,4621,5869,1,Y,No,19,3,4,80,3,3,4,3,3,2,1,2 +24.0,Yes,Travel_Rarely,1448.0,Sales,1.0,1,Technical Degree,1,554,1,Female,62,3,1,Sales Representative,2,Single,3202,21972,1,Y,Yes,16,3,2,80,0,6,4,3,5,3,1,4 +39.0,No,Travel_Frequently,505.0,Research & Development,2.0,4,Technical Degree,1,343,3,Female,64,3,3,Healthcare Representative,3,Single,10938,6420,0,Y,No,25,4,4,80,0,20,1,3,19,6,11,8 +36.0,Yes,Travel_Rarely,318.0,Research & Development,9.0,3,Medical,1,90,4,Male,79,2,1,Research Scientist,3,Married,3388,21777,0,Y,Yes,17,3,1,80,1,2,0,2,1,0,0,0 +34.0,No,Non-Travel,697.0,Research & Development,,4,Life Sciences,1,1115,3,Male,40,2,1,Research Scientist,4,Married,2979,22478,3,Y,No,17,3,4,80,3,6,2,3,0,0,0,0 +50.0,No,Travel_Frequently,809.0,Sales,12.0,3,Marketing,1,174,3,Female,77,3,3,Sales Executive,4,Single,9208,6645,4,Y,No,11,3,4,80,0,16,3,3,2,2,2,1 +41.0,No,Travel_Rarely,334.0,Sales,2.0,4,Life Sciences,1,410,4,Male,88,3,4,Manager,2,Single,16015,15896,1,Y,No,19,3,2,80,0,22,2,3,22,10,0,4 +31.0,Yes,Travel_Rarely,330.0,Research & Development,22.0,4,Medical,1,1389,4,Male,98,3,2,Manufacturing Director,3,Married,6179,21057,1,Y,Yes,15,3,4,80,2,10,3,2,10,2,6,7 +39.0,No,Travel_Frequently,672.0,Research & Development,7.0,2,Medical,1,444,3,Male,54,2,5,Manager,4,Married,19272,21141,1,Y,No,15,3,1,80,1,21,2,3,21,9,13,3 +44.0,No,Travel_Rarely,1037.0,Research & Development,1.0,3,Medical,1,2020,2,Male,42,3,1,Research Scientist,4,Single,2436,13422,6,Y,Yes,12,3,3,80,0,6,2,3,4,3,1,2 +33.0,No,Travel_Rarely,575.0,Research & Development,25.0,3,Life Sciences,1,1545,4,Male,44,2,2,Manufacturing Director,2,Single,4320,24152,1,Y,No,13,3,4,80,0,5,2,3,5,3,0,2 +33.0,No,Travel_Rarely,1216.0,Sales,8.0,4,Marketing,1,677,3,Male,39,3,2,Sales Executive,3,Divorced,7104,20431,0,Y,No,12,3,4,80,0,6,3,3,5,0,1,2 +,No,Travel_Rarely,1382.0,Sales,8.0,2,Other,1,2018,1,Female,85,3,2,Sales Executive,3,Divorced,4907,13684,0,Y,Yes,22,4,2,80,1,6,3,2,5,3,0,4 +37.0,No,Travel_Rarely,367.0,Research & Development,25.0,2,Medical,1,1161,3,Female,52,2,2,Healthcare Representative,4,Divorced,5731,17171,7,Y,No,13,3,3,80,2,9,2,3,6,2,1,3 +37.0,No,Travel_Rarely,921.0,Research & Development,10.0,3,Medical,1,486,3,Female,98,3,1,Laboratory Technician,1,Married,3452,17663,6,Y,No,20,4,2,80,1,17,3,3,5,4,0,3 +27.0,Yes,Travel_Rarely,1420.0,Sales,2.0,1,Marketing,1,667,3,Male,85,3,1,Sales Representative,1,Divorced,3041,16346,0,Y,No,11,3,2,80,1,5,3,3,4,3,0,2 +,No,Travel_Rarely,977.0,Research & Development,2.0,1,Other,1,1992,4,Male,57,3,1,Laboratory Technician,3,Divorced,3977,7298,6,Y,Yes,19,3,3,80,1,7,2,2,2,2,0,2 +30.0,No,Travel_Rarely,570.0,Sales,,3,Marketing,1,456,4,Female,30,2,2,Sales Executive,3,Divorced,6118,5431,1,Y,No,13,3,3,80,3,10,2,3,10,9,1,2 +29.0,Yes,Travel_Rarely,408.0,Research & Development,25.0,5,Technical Degree,1,565,3,Female,71,2,1,Research Scientist,2,Married,2546,18300,5,Y,No,16,3,2,80,0,6,2,4,2,2,1,1 +27.0,No,Non-Travel,1450.0,Research & Development,,3,Medical,1,224,3,Male,79,2,1,Research Scientist,3,Divorced,2566,25326,1,Y,Yes,15,3,4,80,1,1,2,2,1,1,0,1 +44.0,No,Travel_Rarely,477.0,Research & Development,7.0,4,Medical,1,36,1,Female,42,2,3,Healthcare Representative,4,Married,10248,2094,3,Y,No,14,3,4,80,1,24,4,3,22,6,5,17 +23.0,No,Travel_Rarely,885.0,Research & Development,4.0,3,Medical,1,705,1,Male,58,4,1,Research Scientist,1,Married,2819,8544,2,Y,No,16,3,1,80,1,5,3,4,3,2,0,2 +43.0,No,Non-Travel,1344.0,Research & Development,7.0,3,Medical,1,262,4,Male,37,4,1,Research Scientist,4,Divorced,2089,5228,4,Y,No,14,3,4,80,3,7,3,4,5,4,2,2 +29.0,Yes,Travel_Rarely,806.0,Research & Development,7.0,3,Technical Degree,1,1299,2,Female,39,3,1,Laboratory Technician,3,Divorced,3339,17285,3,Y,Yes,13,3,1,80,2,10,2,3,7,7,7,7 +27.0,No,Travel_Frequently,1131.0,Research & Development,15.0,3,Life Sciences,1,1870,4,Female,77,2,1,Research Scientist,1,Married,4774,23844,0,Y,No,19,3,4,80,1,8,2,2,7,6,7,3 +46.0,Yes,Travel_Rarely,1254.0,Sales,10.0,3,Life Sciences,1,1869,3,Female,64,3,3,Sales Executive,2,Married,7314,14011,5,Y,No,21,4,3,80,3,14,2,3,8,7,0,7 +32.0,No,Travel_Rarely,120.0,Research & Development,6.0,5,Life Sciences,1,231,3,Male,43,3,1,Research Scientist,3,Single,3038,12430,3,Y,No,20,4,1,80,0,8,2,3,5,4,1,4 +30.0,No,Travel_Rarely,1339.0,Sales,,3,Life Sciences,1,228,2,Female,41,3,3,Sales Executive,4,Married,9419,8053,2,Y,No,12,3,3,80,1,12,2,3,10,9,7,4 +37.0,No,Non-Travel,1252.0,Sales,19.0,2,Medical,1,904,1,Male,32,3,3,Sales Executive,2,Single,7642,4814,1,Y,Yes,13,3,4,80,0,10,2,3,10,0,0,9 +30.0,No,Non-Travel,111.0,Research & Development,9.0,3,Medical,1,239,3,Male,66,3,2,Laboratory Technician,1,Divorced,3072,11012,1,Y,No,11,3,3,80,2,12,4,3,12,9,6,10 +38.0,No,Travel_Rarely,243.0,Sales,7.0,4,Marketing,1,709,4,Female,46,2,2,Sales Executive,4,Single,4028,7791,0,Y,No,20,4,1,80,0,8,2,3,7,7,0,5 +33.0,No,Travel_Rarely,392.0,Sales,2.0,4,Medical,1,1670,4,Male,93,3,2,Sales Executive,4,Divorced,5505,3921,1,Y,No,14,3,3,80,2,6,5,3,6,2,0,4 +,No,Non-Travel,208.0,Research & Development,8.0,4,Life Sciences,1,1630,3,Female,52,3,2,Healthcare Representative,3,Married,4148,12250,1,Y,No,12,3,4,80,1,15,5,3,14,11,2,9 +,No,Travel_Rarely,583.0,Research & Development,4.0,2,Life Sciences,1,1275,3,Male,53,3,1,Research Scientist,4,Single,2875,9973,1,Y,Yes,20,4,2,80,0,8,2,2,8,5,2,2 +43.0,No,Travel_Frequently,1001.0,Research & Development,9.0,5,Medical,1,663,4,Male,72,3,2,Laboratory Technician,3,Divorced,5679,19627,3,Y,Yes,13,3,2,80,1,10,3,3,8,7,4,7 +32.0,No,Travel_Rarely,548.0,Research & Development,1.0,3,Life Sciences,1,96,2,Male,66,3,2,Research Scientist,2,Married,6220,7346,1,Y,No,17,3,2,80,2,10,3,3,10,4,0,9 +31.0,No,Travel_Rarely,741.0,Research & Development,2.0,4,Life Sciences,1,1721,2,Male,69,3,1,Laboratory Technician,3,Married,3477,18103,1,Y,No,14,3,4,80,1,6,2,4,5,2,0,3 +52.0,No,Travel_Rarely,1325.0,Research & Development,11.0,4,Life Sciences,1,813,4,Female,82,3,2,Laboratory Technician,3,Married,3149,21821,8,Y,No,20,4,2,80,1,9,3,3,5,2,1,4 +44.0,No,Travel_Rarely,1448.0,Sales,28.0,3,Medical,1,1039,4,Female,53,4,4,Sales Executive,4,Married,13320,11737,3,Y,Yes,18,3,3,80,1,23,2,3,12,11,11,11 +29.0,No,Travel_Rarely,1086.0,Research & Development,7.0,1,Medical,1,912,1,Female,62,2,1,Laboratory Technician,4,Divorced,2532,6054,6,Y,No,14,3,3,80,3,8,5,3,4,3,0,3 +,Yes,Travel_Rarely,1485.0,Research & Development,12.0,1,Life Sciences,1,1175,3,Female,79,3,1,Laboratory Technician,4,Married,2515,22955,1,Y,Yes,11,3,4,80,0,1,4,2,1,1,0,0 +33.0,Yes,Travel_Rarely,813.0,Research & Development,14.0,3,Medical,1,325,3,Male,58,3,1,Laboratory Technician,4,Married,2436,22149,5,Y,Yes,13,3,3,80,1,8,2,1,5,4,0,4 +30.0,Yes,Travel_Frequently,109.0,Research & Development,,3,Medical,1,1017,2,Female,60,3,1,Laboratory Technician,2,Single,2422,25725,0,Y,No,17,3,1,80,0,4,3,3,3,2,1,2 +30.0,Yes,Travel_Rarely,1005.0,Research & Development,,3,Technical Degree,1,297,4,Female,88,3,1,Research Scientist,1,Single,2657,8556,5,Y,Yes,11,3,3,80,0,8,5,3,5,2,0,4 +,No,Travel_Rarely,440.0,Research & Development,21.0,3,Medical,1,221,3,Male,42,3,1,Research Scientist,4,Married,2713,6672,1,Y,No,11,3,3,80,1,5,2,1,5,2,0,2 +31.0,Yes,Travel_Rarely,542.0,Sales,20.0,3,Life Sciences,1,175,2,Female,71,1,2,Sales Executive,3,Married,4559,24788,3,Y,Yes,11,3,3,80,1,4,2,3,2,2,2,2 +21.0,No,Travel_Rarely,,Sales,,1,Medical,1,2021,3,Male,58,3,1,Sales Representative,1,Single,2380,25479,1,Y,Yes,11,3,4,80,0,2,6,3,2,2,1,2 +37.0,No,Travel_Frequently,663.0,Research & Development,11.0,3,Other,1,306,2,Male,47,3,3,Research Director,4,Divorced,12185,10056,1,Y,Yes,14,3,3,80,3,10,1,3,10,8,0,7 +38.0,No,Travel_Rarely,1495.0,Research & Development,4.0,2,Medical,1,1687,4,Female,87,3,1,Laboratory Technician,3,Married,3306,26176,7,Y,No,19,3,4,80,1,7,5,2,0,0,0,0 +,No,Travel_Rarely,266.0,Research & Development,1.0,3,Medical,1,1303,4,Female,40,3,1,Research Scientist,2,Single,2096,18830,1,Y,No,18,3,4,80,0,2,3,2,2,2,2,1 +33.0,No,Travel_Rarely,931.0,Research & Development,14.0,3,Medical,1,252,4,Female,72,3,1,Research Scientist,2,Married,2756,4673,1,Y,No,13,3,4,80,1,8,5,3,8,7,1,6 +27.0,No,Travel_Rarely,1240.0,Research & Development,2.0,4,Life Sciences,1,54,4,Female,33,3,1,Laboratory Technician,1,Divorced,2341,19715,1,Y,No,13,3,4,80,1,1,6,3,1,0,0,0 +32.0,No,Travel_Rarely,498.0,Research & Development,,4,Medical,1,966,3,Female,93,3,2,Manufacturing Director,1,Married,6725,13554,1,Y,No,12,3,3,80,1,8,2,4,8,7,6,3 +,No,Travel_Rarely,1280.0,Research & Development,7.0,1,Medical,1,143,4,Male,64,2,1,Research Scientist,4,Married,2889,26897,1,Y,No,11,3,3,80,2,2,2,3,2,2,2,1 +36.0,No,Travel_Rarely,852.0,Research & Development,,4,Life Sciences,1,51,2,Female,82,2,1,Research Scientist,1,Married,3419,13072,9,Y,Yes,14,3,4,80,1,6,3,4,1,1,0,0 +55.0,Yes,Travel_Rarely,725.0,Research & Development,2.0,3,Medical,1,787,4,Male,78,3,5,Manager,1,Married,19859,21199,5,Y,Yes,13,3,4,80,1,24,2,3,5,2,1,4 +42.0,No,Non-Travel,355.0,Research & Development,10.0,4,Technical Degree,1,1854,3,Male,38,3,1,Research Scientist,3,Married,2936,6161,3,Y,No,22,4,2,80,2,10,1,2,6,3,3,3 +22.0,Yes,Travel_Rarely,391.0,Research & Development,7.0,1,Life Sciences,1,1878,4,Male,75,3,1,Research Scientist,2,Single,2472,26092,1,Y,Yes,23,4,1,80,0,1,2,3,1,0,0,0 +30.0,No,Travel_Rarely,911.0,Research & Development,1.0,2,Medical,1,1989,4,Male,76,3,1,Laboratory Technician,2,Married,3748,4077,1,Y,No,13,3,3,80,0,12,6,2,12,8,1,7 +,No,Travel_Rarely,538.0,Research & Development,25.0,2,Other,1,652,1,Male,54,2,2,Laboratory Technician,4,Single,3681,14004,4,Y,No,14,3,4,80,0,9,3,3,3,2,0,2 +52.0,No,Travel_Rarely,956.0,Research & Development,6.0,2,Technical Degree,1,630,4,Male,78,3,2,Research Scientist,1,Divorced,5577,22087,3,Y,Yes,12,3,2,80,2,18,3,3,10,9,6,9 +54.0,No,Travel_Frequently,966.0,Research & Development,1.0,4,Life Sciences,1,1245,4,Female,53,3,3,Manufacturing Director,3,Divorced,10502,9659,7,Y,No,17,3,1,80,1,33,2,1,5,4,1,4 +52.0,Yes,Travel_Rarely,1030.0,Sales,,3,Life Sciences,1,1319,2,Male,64,3,3,Sales Executive,2,Single,8446,21534,9,Y,Yes,19,3,3,80,0,10,2,2,8,7,7,7 +34.0,Yes,Travel_Rarely,699.0,Research & Development,6.0,1,Medical,1,31,2,Male,83,3,1,Research Scientist,1,Single,2960,17102,2,Y,No,11,3,3,80,0,8,2,3,4,2,1,3 +55.0,No,Travel_Rarely,189.0,Human Resources,26.0,4,Human Resources,1,1973,3,Male,71,4,5,Manager,2,Married,19636,25811,4,Y,Yes,18,3,1,80,1,35,0,3,10,9,1,4 +42.0,No,Travel_Rarely,1147.0,Human Resources,10.0,3,Human Resources,1,1408,3,Female,31,3,4,Manager,1,Married,16799,16616,0,Y,No,14,3,3,80,1,21,5,3,20,7,0,9 +,No,Travel_Frequently,664.0,Research & Development,1.0,3,Medical,1,88,2,Male,79,3,1,Research Scientist,1,Married,2194,5868,4,Y,No,13,3,4,80,1,5,2,2,3,2,1,2 +40.0,No,Travel_Rarely,107.0,Sales,10.0,3,Technical Degree,1,1239,2,Female,84,2,2,Sales Executive,2,Divorced,6852,11591,7,Y,No,12,3,2,80,1,7,2,4,5,1,1,3 +31.0,No,Travel_Frequently,163.0,Research & Development,24.0,1,Technical Degree,1,1736,4,Female,30,3,2,Manufacturing Director,4,Single,5238,6670,2,Y,No,20,4,4,80,0,9,3,2,5,4,1,4 +41.0,Yes,Travel_Frequently,143.0,Sales,4.0,3,Marketing,1,488,1,Male,56,3,2,Sales Executive,2,Single,9355,9558,1,Y,No,18,3,3,80,0,8,5,3,8,7,7,7 +,No,Travel_Rarely,991.0,Research & Development,6.0,3,Life Sciences,1,686,3,Female,71,3,1,Laboratory Technician,4,Married,2659,17759,1,Y,Yes,13,3,3,80,1,3,2,3,3,2,0,2 +32.0,No,Non-Travel,862.0,Sales,2.0,1,Life Sciences,1,1190,3,Female,76,3,1,Sales Representative,1,Divorced,2827,14947,1,Y,No,12,3,3,80,3,1,3,3,1,0,0,0 +38.0,No,Non-Travel,1336.0,Human Resources,2.0,3,Human Resources,1,1805,1,Male,100,3,1,Human Resources,2,Divorced,2592,7129,5,Y,No,13,3,4,80,3,13,3,3,11,10,3,8 +22.0,No,Travel_Rarely,253.0,Research & Development,11.0,3,Medical,1,511,1,Female,43,3,1,Research Scientist,2,Married,2244,24440,1,Y,No,13,3,4,80,1,2,1,3,2,1,1,2 +22.0,No,Travel_Rarely,217.0,Research & Development,8.0,1,Life Sciences,1,1019,2,Male,94,1,1,Laboratory Technician,1,Married,2451,6881,1,Y,No,15,3,1,80,1,4,3,2,4,3,1,1 +27.0,No,Travel_Rarely,1134.0,Research & Development,16.0,4,Technical Degree,1,1001,3,Female,37,3,1,Laboratory Technician,2,Married,2811,12086,9,Y,No,14,3,2,80,1,4,2,3,2,2,2,2 +38.0,No,Travel_Rarely,723.0,Sales,2.0,4,Marketing,1,1835,2,Female,77,1,2,Sales Representative,4,Married,5405,4244,2,Y,Yes,20,4,1,80,2,20,4,2,4,2,0,3 +29.0,No,Travel_Rarely,232.0,Research & Development,19.0,3,Technical Degree,1,611,4,Male,34,3,2,Manufacturing Director,4,Divorced,4262,22645,4,Y,No,12,3,2,80,2,8,2,4,3,2,1,2 +,Yes,Travel_Rarely,529.0,Research & Development,2.0,4,Life Sciences,1,364,1,Male,79,3,1,Laboratory Technician,3,Single,3485,14935,2,Y,No,11,3,3,80,0,5,5,1,0,0,0,0 +31.0,No,Travel_Rarely,746.0,Research & Development,8.0,4,Life Sciences,1,98,3,Female,61,3,2,Manufacturing Director,4,Single,4424,20682,1,Y,No,23,4,4,80,0,11,2,3,11,7,1,8 +55.0,No,Non-Travel,177.0,Research & Development,8.0,1,Medical,1,1278,4,Male,37,2,4,Healthcare Representative,2,Divorced,13577,25592,1,Y,Yes,15,3,4,80,1,34,3,3,33,9,15,0 +59.0,No,Travel_Rarely,818.0,Human Resources,6.0,2,Medical,1,321,2,Male,52,3,1,Human Resources,3,Married,2267,25657,8,Y,No,17,3,4,80,0,7,2,2,2,2,2,2 +48.0,No,Travel_Rarely,163.0,Sales,2.0,5,Marketing,1,595,2,Female,37,3,2,Sales Executive,4,Married,4051,19658,2,Y,No,14,3,1,80,1,14,2,3,9,7,6,7 +43.0,No,Travel_Frequently,313.0,Research & Development,21.0,3,Medical,1,525,4,Male,61,3,1,Laboratory Technician,4,Married,2258,15238,7,Y,No,20,4,1,80,1,8,1,3,3,2,1,2 +,No,Travel_Rarely,950.0,Research & Development,7.0,3,Other,1,845,3,Male,59,3,3,Manufacturing Director,3,Single,10221,18869,3,Y,No,21,4,2,80,0,17,3,4,8,5,1,6 +33.0,No,Travel_Rarely,134.0,Research & Development,2.0,3,Life Sciences,1,242,3,Male,90,3,1,Research Scientist,4,Single,2500,10515,0,Y,No,14,3,1,80,0,4,2,4,3,1,0,2 +53.0,No,Travel_Rarely,1219.0,Sales,2.0,4,Life Sciences,1,23,1,Female,78,2,4,Manager,4,Married,15427,22021,2,Y,No,16,3,3,80,0,31,3,3,25,8,3,7 +46.0,No,Non-Travel,849.0,Sales,26.0,2,Life Sciences,1,1801,2,Male,98,2,2,Sales Executive,2,Single,7991,25166,8,Y,No,15,3,3,80,0,6,3,3,2,2,2,2 +31.0,No,Travel_Rarely,1398.0,Human Resources,8.0,2,Medical,1,1461,4,Female,96,4,1,Human Resources,2,Single,2109,24609,9,Y,No,18,3,4,80,0,8,3,3,3,2,0,2 +38.0,No,Travel_Rarely,343.0,Research & Development,15.0,2,Life Sciences,1,461,3,Male,92,2,3,Research Director,4,Divorced,11510,15682,0,Y,Yes,14,3,2,80,1,12,3,3,11,10,2,9 +55.0,No,Travel_Rarely,1136.0,Research & Development,1.0,4,Medical,1,1424,2,Male,81,4,4,Research Director,4,Divorced,14732,12414,2,Y,No,13,3,4,80,2,31,4,4,7,7,0,0 +60.0,No,Travel_Rarely,696.0,Sales,7.0,4,Marketing,1,1233,2,Male,52,4,2,Sales Executive,4,Divorced,5220,10893,0,Y,Yes,18,3,2,80,1,12,3,3,11,7,1,9 +58.0,Yes,Travel_Rarely,286.0,Research & Development,2.0,4,Life Sciences,1,825,4,Male,31,3,5,Research Director,2,Single,19246,25761,7,Y,Yes,12,3,4,80,0,40,2,3,31,15,13,8 +38.0,No,Travel_Frequently,,Research & Development,29.0,5,Life Sciences,1,79,4,Female,50,3,2,Laboratory Technician,4,Single,2406,5456,1,Y,No,11,3,4,80,0,10,2,3,10,3,9,9 +46.0,No,Travel_Rarely,1277.0,Sales,2.0,3,Life Sciences,1,1732,3,Male,74,3,3,Sales Executive,4,Divorced,10368,5596,4,Y,Yes,12,3,2,80,1,13,5,2,10,6,0,3 +,No,Travel_Rarely,1158.0,Research & Development,9.0,3,Medical,1,377,4,Male,94,3,1,Research Scientist,4,Married,2070,2613,1,Y,No,23,4,4,80,1,5,3,2,5,2,0,4 +56.0,Yes,Travel_Rarely,310.0,Research & Development,7.0,2,Technical Degree,1,2032,4,Male,72,3,1,Laboratory Technician,3,Married,2339,3666,8,Y,No,11,3,4,80,1,14,4,1,10,9,9,8 +33.0,No,Travel_Frequently,1146.0,Sales,25.0,3,Medical,1,1220,2,Female,82,3,2,Sales Executive,3,Married,4539,4905,1,Y,No,12,3,1,80,1,10,3,2,10,7,0,1 +40.0,No,Non-Travel,1142.0,Research & Development,8.0,2,Life Sciences,1,1552,4,Male,72,3,2,Healthcare Representative,4,Divorced,4069,8841,3,Y,Yes,18,3,3,80,0,8,2,3,2,2,2,2 +27.0,Yes,Travel_Frequently,1337.0,Human Resources,22.0,3,Human Resources,1,1944,1,Female,58,2,1,Human Resources,2,Married,2863,19555,1,Y,No,12,3,1,80,0,1,2,3,1,0,0,0 +,No,Travel_Frequently,1479.0,Research & Development,1.0,3,Life Sciences,1,384,3,Female,84,3,2,Manufacturing Director,2,Divorced,6397,26767,1,Y,No,20,4,1,80,1,6,6,1,6,5,1,4 +,No,Non-Travel,1180.0,Research & Development,2.0,2,Medical,1,1804,2,Male,90,3,2,Manufacturing Director,4,Divorced,5762,24442,2,Y,No,14,3,3,80,1,15,6,3,7,7,1,7 +33.0,No,Travel_Rarely,1069.0,Research & Development,1.0,3,Life Sciences,1,969,2,Female,42,2,2,Healthcare Representative,4,Single,6949,12291,0,Y,No,14,3,1,80,0,6,3,3,5,0,1,4 +40.0,Yes,Travel_Rarely,575.0,Sales,22.0,2,Marketing,1,492,3,Male,68,2,2,Sales Executive,3,Married,6380,6110,2,Y,Yes,12,3,1,80,2,8,6,3,6,4,1,0 +34.0,Yes,Non-Travel,967.0,Research & Development,16.0,4,Technical Degree,1,1905,4,Male,85,1,1,Research Scientist,1,Married,2307,14460,1,Y,Yes,23,4,2,80,1,5,2,3,5,2,3,0 +50.0,Yes,Travel_Rarely,869.0,Sales,,2,Marketing,1,47,1,Male,86,2,1,Sales Representative,3,Married,2683,3810,1,Y,Yes,14,3,3,80,0,3,2,3,3,2,0,2 +48.0,No,Travel_Rarely,277.0,Research & Development,6.0,3,Life Sciences,1,1022,1,Male,97,2,2,Healthcare Representative,3,Single,4240,13119,2,Y,No,13,3,4,80,0,19,0,3,2,2,2,2 +54.0,No,Travel_Rarely,431.0,Research & Development,7.0,4,Medical,1,1830,4,Female,68,3,2,Research Scientist,4,Married,6854,15696,4,Y,No,15,3,2,80,1,14,2,2,7,1,1,7 +20.0,Yes,Travel_Rarely,500.0,Sales,2.0,3,Medical,1,922,3,Female,49,2,1,Sales Representative,3,Single,2044,22052,1,Y,No,13,3,4,80,0,2,3,2,2,2,0,2 +43.0,No,Non-Travel,343.0,Research & Development,9.0,3,Life Sciences,1,1813,1,Male,52,3,1,Research Scientist,3,Single,2438,24978,4,Y,No,13,3,3,80,0,7,2,2,3,2,1,2 +29.0,No,Travel_Rarely,726.0,Research & Development,29.0,1,Life Sciences,1,1859,4,Male,93,1,2,Healthcare Representative,3,Divorced,6384,21143,8,Y,No,17,3,4,80,2,11,3,3,7,0,1,6 +34.0,No,Non-Travel,999.0,Research & Development,26.0,1,Technical Degree,1,1374,1,Female,92,2,1,Research Scientist,3,Divorced,2029,15891,1,Y,No,20,4,3,80,3,5,2,3,5,4,0,0 +42.0,Yes,Travel_Frequently,933.0,Research & Development,19.0,3,Medical,1,752,3,Male,57,4,1,Research Scientist,3,Divorced,2759,20366,6,Y,Yes,12,3,4,80,0,7,2,3,2,2,2,2 +27.0,No,Travel_Rarely,486.0,Research & Development,8.0,3,Medical,1,1647,2,Female,86,4,1,Research Scientist,3,Married,3517,22490,7,Y,No,17,3,1,80,0,5,0,3,3,2,0,2 +19.0,Yes,Travel_Rarely,419.0,Sales,21.0,3,Other,1,959,4,Male,37,2,1,Sales Representative,2,Single,2121,9947,1,Y,Yes,13,3,2,80,0,1,3,4,1,0,0,0 +39.0,No,Travel_Rarely,466.0,Research & Development,1.0,1,Life Sciences,1,1026,4,Female,65,2,4,Manufacturing Director,4,Married,12742,7060,1,Y,No,16,3,3,80,1,21,3,3,21,6,11,8 +27.0,No,Travel_Rarely,,Research & Development,9.0,3,Medical,1,260,4,Female,99,3,1,Research Scientist,2,Single,2279,11781,1,Y,No,16,3,4,80,0,7,2,2,7,7,0,3 +59.0,No,Travel_Rarely,1429.0,Research & Development,18.0,4,Medical,1,1283,4,Male,67,3,3,Manufacturing Director,4,Single,10512,20002,6,Y,No,12,3,4,80,0,25,6,2,9,7,5,4 +31.0,No,Travel_Rarely,688.0,Sales,7.0,3,Life Sciences,1,613,3,Male,44,2,3,Manager,4,Divorced,11557,25291,9,Y,No,21,4,3,80,1,10,3,2,5,4,0,1 +,No,Travel_Rarely,1179.0,Research & Development,19.0,4,Medical,1,1216,4,Male,78,2,1,Laboratory Technician,1,Married,3196,12449,1,Y,No,12,3,3,80,3,6,2,3,6,5,3,3 +34.0,No,Non-Travel,1381.0,Sales,4.0,4,Marketing,1,523,3,Female,72,3,2,Sales Executive,3,Married,6538,12740,9,Y,No,15,3,1,80,1,6,3,3,3,2,1,2 +31.0,No,Travel_Rarely,154.0,Sales,7.0,4,Life Sciences,1,941,2,Male,41,2,1,Sales Representative,3,Married,2329,11737,3,Y,No,15,3,2,80,0,13,2,4,7,7,5,2 +53.0,No,Travel_Frequently,124.0,Sales,2.0,3,Marketing,1,1050,3,Female,38,2,3,Sales Executive,2,Married,7525,23537,2,Y,No,12,3,1,80,1,30,2,3,15,7,6,12 +41.0,No,Travel_Rarely,582.0,Research & Development,28.0,4,Life Sciences,1,2034,1,Female,60,2,4,Manufacturing Director,2,Married,13570,5640,0,Y,No,23,4,3,80,1,21,3,3,20,7,0,10 +54.0,No,Travel_Rarely,1441.0,Research & Development,17.0,3,Technical Degree,1,1013,3,Female,56,3,3,Manufacturing Director,3,Married,10739,13943,8,Y,No,11,3,3,80,1,22,2,3,10,7,0,8 +30.0,No,Non-Travel,1400.0,Research & Development,,3,Life Sciences,1,562,3,Male,53,3,1,Laboratory Technician,4,Married,2097,16734,4,Y,No,15,3,3,80,1,9,3,1,5,3,1,4 +49.0,No,Travel_Rarely,1261.0,Research & Development,7.0,3,Other,1,499,2,Male,31,2,3,Healthcare Representative,3,Single,10965,12066,8,Y,No,24,4,3,80,0,26,2,3,5,2,0,0 +46.0,No,Travel_Rarely,1485.0,Research & Development,18.0,3,Medical,1,550,3,Female,87,3,2,Manufacturing Director,3,Divorced,4810,26314,2,Y,No,14,3,3,80,1,19,5,2,10,7,0,8 +36.0,No,Travel_Rarely,132.0,Research & Development,6.0,3,Life Sciences,1,97,2,Female,55,4,1,Laboratory Technician,4,Married,3038,22002,3,Y,No,12,3,2,80,0,5,3,3,1,0,0,0 +32.0,Yes,Travel_Frequently,238.0,Research & Development,,2,Life Sciences,1,1939,1,Female,47,4,1,Research Scientist,3,Single,2432,15318,3,Y,Yes,14,3,1,80,0,8,2,3,4,1,0,3 +27.0,No,Travel_Rarely,,Research & Development,19.0,3,Other,1,1619,4,Male,67,2,1,Laboratory Technician,1,Divorced,4066,16290,1,Y,No,11,3,1,80,2,7,3,3,7,7,0,7 +32.0,No,Travel_Rarely,646.0,Research & Development,9.0,4,Life Sciences,1,679,1,Female,92,3,2,Research Scientist,4,Married,6322,18089,1,Y,Yes,12,3,4,80,1,6,2,2,6,4,0,5 +29.0,No,Travel_Rarely,718.0,Research & Development,8.0,1,Medical,1,1150,2,Male,79,2,2,Manufacturing Director,4,Married,5056,17689,1,Y,Yes,15,3,3,80,1,10,2,2,10,7,1,2 +37.0,No,Travel_Rarely,290.0,Research & Development,21.0,3,Life Sciences,1,267,2,Male,65,4,1,Research Scientist,1,Married,3564,22977,1,Y,Yes,12,3,1,80,1,8,3,2,8,7,1,7 +,No,Travel_Rarely,1349.0,Research & Development,7.0,2,Life Sciences,1,1601,3,Male,63,2,1,Laboratory Technician,4,Married,2690,7713,1,Y,No,18,3,4,80,1,1,5,2,1,0,0,1 +51.0,No,Travel_Rarely,1318.0,Sales,26.0,4,Marketing,1,851,1,Female,66,3,4,Manager,3,Married,16307,5594,2,Y,No,14,3,3,80,1,29,2,2,20,6,4,17 +34.0,No,Travel_Rarely,1031.0,Research & Development,6.0,4,Life Sciences,1,151,3,Female,45,2,2,Research Scientist,2,Divorced,4505,15000,6,Y,No,15,3,3,80,1,12,3,3,1,0,0,0 +40.0,No,Travel_Rarely,1398.0,Sales,2.0,4,Life Sciences,1,558,3,Female,79,3,5,Manager,3,Married,18041,13022,0,Y,No,14,3,4,80,0,21,2,3,20,15,1,12 +38.0,No,Travel_Frequently,1444.0,Human Resources,1.0,4,Other,1,1972,4,Male,88,3,1,Human Resources,2,Married,2991,5224,0,Y,Yes,11,3,2,80,1,7,2,3,6,2,1,2 +48.0,No,Travel_Rarely,855.0,Research & Development,4.0,3,Life Sciences,1,1363,4,Male,54,3,3,Manufacturing Director,4,Single,7898,18706,1,Y,No,11,3,3,80,0,11,2,3,10,9,0,8 +42.0,No,Travel_Rarely,933.0,Research & Development,29.0,3,Life Sciences,1,836,2,Male,98,3,2,Manufacturing Director,2,Married,4434,11806,1,Y,No,13,3,4,80,1,10,3,2,9,8,7,8 +31.0,No,Non-Travel,697.0,Research & Development,10.0,3,Medical,1,1979,3,Female,40,3,3,Research Director,3,Married,11031,26862,4,Y,No,20,4,3,80,1,13,2,4,11,7,4,8 +46.0,Yes,Travel_Rarely,669.0,Sales,9.0,2,Medical,1,118,3,Male,64,2,3,Sales Executive,4,Single,9619,13596,1,Y,No,16,3,4,80,0,9,3,3,9,8,4,7 +,No,Travel_Frequently,636.0,Research & Development,4.0,4,Other,1,1185,4,Male,47,2,1,Laboratory Technician,4,Married,2376,26537,1,Y,No,13,3,2,80,1,2,2,4,2,2,2,2 +29.0,Yes,Travel_Frequently,746.0,Sales,24.0,3,Technical Degree,1,1928,3,Male,45,4,1,Sales Representative,1,Single,1091,10642,1,Y,No,17,3,4,80,0,1,3,3,1,0,0,0 +42.0,No,Non-Travel,335.0,Research & Development,23.0,2,Life Sciences,1,1976,4,Male,37,2,2,Research Scientist,3,Single,4332,14811,1,Y,No,12,3,4,80,0,20,2,3,20,9,3,7 +39.0,No,Travel_Frequently,945.0,Research & Development,22.0,3,Medical,1,1043,4,Female,82,3,3,Manufacturing Director,1,Single,10880,5083,1,Y,Yes,13,3,3,80,0,21,2,3,21,6,2,8 +22.0,No,Travel_Rarely,604.0,Research & Development,6.0,1,Medical,1,675,1,Male,69,3,1,Research Scientist,3,Married,2773,12145,0,Y,No,20,4,4,80,0,3,3,3,2,2,2,2 +29.0,No,Travel_Rarely,153.0,Research & Development,15.0,2,Life Sciences,1,15,4,Female,49,2,2,Laboratory Technician,3,Single,4193,12682,0,Y,Yes,12,3,4,80,0,10,3,3,9,5,0,8 +43.0,No,Travel_Rarely,1473.0,Research & Development,8.0,4,Other,1,526,3,Female,74,3,2,Healthcare Representative,3,Divorced,4522,2227,4,Y,Yes,14,3,4,80,0,8,3,3,5,2,0,2 +,No,Travel_Frequently,496.0,Research & Development,11.0,2,Medical,1,390,1,Male,60,3,2,Healthcare Representative,1,Married,4741,22722,1,Y,Yes,13,3,3,80,1,5,3,3,5,3,3,3 +31.0,No,Travel_Rarely,616.0,Research & Development,12.0,3,Medical,1,961,4,Female,41,3,2,Healthcare Representative,4,Married,5855,17369,0,Y,Yes,11,3,3,80,2,10,2,1,9,7,8,5 +32.0,Yes,Travel_Rarely,1259.0,Research & Development,2.0,4,Life Sciences,1,1692,4,Male,95,3,1,Laboratory Technician,2,Single,1393,24852,1,Y,No,12,3,1,80,0,1,2,3,1,0,0,0 +38.0,No,Travel_Rarely,1206.0,Research & Development,9.0,2,Life Sciences,1,1940,2,Male,71,3,1,Research Scientist,4,Divorced,4771,14293,2,Y,No,19,3,4,80,2,10,0,4,5,2,0,3 +20.0,Yes,Travel_Rarely,129.0,Research & Development,4.0,3,Technical Degree,1,960,1,Male,84,3,1,Laboratory Technician,1,Single,2973,13008,1,Y,No,19,3,2,80,0,1,2,3,1,0,0,0 +56.0,No,Travel_Rarely,718.0,Research & Development,4.0,4,Technical Degree,1,1191,4,Female,92,3,5,Manager,1,Divorced,19943,18575,4,Y,No,13,3,4,80,1,28,2,3,5,2,4,2 +34.0,No,Travel_Frequently,303.0,Sales,2.0,4,Marketing,1,216,3,Female,75,3,1,Sales Representative,3,Married,2231,11314,6,Y,No,18,3,4,80,1,6,3,3,4,3,1,2 +31.0,No,Travel_Rarely,1332.0,Research & Development,11.0,2,Medical,1,1251,3,Male,80,3,2,Healthcare Representative,1,Married,6833,17089,1,Y,Yes,12,3,4,80,0,6,2,2,6,5,0,1 +48.0,No,Travel_Frequently,365.0,Research & Development,4.0,5,Medical,1,1644,3,Male,89,2,4,Manager,4,Married,15202,5602,2,Y,No,25,4,2,80,1,23,3,3,2,2,2,2 +40.0,No,Travel_Rarely,1416.0,Research & Development,2.0,2,Medical,1,352,1,Male,49,3,5,Research Director,3,Divorced,19436,5949,0,Y,No,19,3,4,80,1,22,5,3,21,7,3,9 +40.0,No,Travel_Rarely,1124.0,Sales,1.0,2,Medical,1,453,2,Male,57,1,2,Sales Executive,4,Married,7457,13273,2,Y,Yes,22,4,3,80,3,6,2,2,4,3,0,2 +,No,Travel_Rarely,682.0,Sales,18.0,4,Medical,1,1945,2,Male,71,3,2,Sales Executive,1,Married,5561,15975,0,Y,No,16,3,4,80,1,6,2,1,5,3,0,4 +34.0,Yes,Travel_Rarely,1107.0,Human Resources,9.0,4,Technical Degree,1,1467,1,Female,52,3,1,Human Resources,3,Married,2742,3072,1,Y,No,15,3,4,80,0,2,0,3,2,2,2,2 +,No,Non-Travel,727.0,Research & Development,,3,Life Sciences,1,704,3,Male,41,2,1,Laboratory Technician,3,Married,1281,16900,1,Y,No,18,3,3,80,2,1,3,3,1,0,0,0 +34.0,No,Travel_Frequently,560.0,Research & Development,1.0,4,Other,1,1431,4,Male,91,3,1,Research Scientist,1,Divorced,2996,20284,5,Y,No,14,3,3,80,2,10,2,3,4,3,1,3 +40.0,No,Travel_Rarely,300.0,Sales,26.0,3,Marketing,1,1066,3,Male,74,3,2,Sales Executive,1,Married,8396,22217,1,Y,No,14,3,2,80,1,8,3,2,7,7,7,5 +34.0,Yes,Travel_Frequently,234.0,Research & Development,9.0,4,Life Sciences,1,1807,4,Male,93,3,2,Laboratory Technician,1,Married,5346,6208,4,Y,No,17,3,3,80,1,11,3,2,7,1,0,7 +36.0,Yes,Travel_Rarely,660.0,Research & Development,15.0,3,Other,1,1052,1,Male,81,3,2,Laboratory Technician,3,Divorced,4834,7858,7,Y,No,14,3,2,80,1,9,3,2,1,0,0,0 +46.0,No,Travel_Rarely,228.0,Sales,,3,Life Sciences,1,1527,3,Female,51,3,4,Manager,2,Married,16606,11380,8,Y,No,12,3,4,80,1,23,2,4,13,12,5,1 +27.0,No,Travel_Frequently,1410.0,Sales,,1,Medical,1,714,4,Female,71,4,2,Sales Executive,4,Divorced,4647,16673,1,Y,Yes,20,4,2,80,2,6,3,3,6,5,0,4 +34.0,No,Travel_Rarely,419.0,Research & Development,7.0,4,Life Sciences,1,28,1,Female,53,3,3,Research Director,2,Single,11994,21293,0,Y,No,11,3,3,80,0,13,4,3,12,6,2,11 +42.0,No,Travel_Rarely,1332.0,Research & Development,2.0,4,Other,1,477,1,Male,98,2,2,Healthcare Representative,4,Single,6781,17078,3,Y,No,23,4,2,80,0,14,6,3,1,0,0,0 +30.0,Yes,Travel_Frequently,600.0,Human Resources,8.0,3,Human Resources,1,1747,3,Female,66,2,1,Human Resources,4,Divorced,2180,9732,6,Y,No,11,3,3,80,1,6,0,2,4,2,1,2 +37.0,No,Travel_Rarely,1192.0,Research & Development,,2,Medical,1,460,4,Male,61,3,2,Manufacturing Director,4,Divorced,6347,23177,7,Y,No,16,3,3,80,2,8,2,2,6,2,0,4 +54.0,No,Travel_Rarely,548.0,Research & Development,8.0,4,Life Sciences,1,578,3,Female,42,3,2,Laboratory Technician,3,Single,3780,23428,7,Y,No,11,3,3,80,0,19,3,3,1,0,0,0 +49.0,No,Travel_Rarely,1245.0,Research & Development,18.0,4,Life Sciences,1,638,4,Male,58,2,5,Research Director,3,Divorced,19502,2125,1,Y,Yes,17,3,3,80,1,31,5,3,31,9,0,9 +29.0,Yes,Travel_Rarely,992.0,Research & Development,1.0,3,Technical Degree,1,300,3,Male,85,3,1,Research Scientist,3,Single,2058,19757,0,Y,No,14,3,4,80,0,7,1,2,6,2,1,5 +,Yes,Travel_Frequently,599.0,Sales,24.0,1,Life Sciences,1,1273,3,Male,73,1,1,Sales Representative,4,Single,1118,8040,1,Y,Yes,14,3,4,80,0,1,4,3,1,0,1,0 +38.0,No,Travel_Frequently,1394.0,Research & Development,8.0,3,Medical,1,1937,4,Female,58,2,2,Research Scientist,2,Divorced,2133,18115,1,Y,Yes,16,3,3,80,1,20,3,3,20,11,0,7 +36.0,No,Travel_Rarely,1174.0,Sales,,4,Marketing,1,1425,1,Female,99,3,2,Sales Executive,2,Single,9278,20763,3,Y,Yes,16,3,4,80,0,15,3,3,5,4,0,1 +39.0,No,Travel_Rarely,116.0,Research & Development,24.0,1,Life Sciences,1,2014,1,Male,52,3,2,Research Scientist,4,Single,4108,5340,7,Y,No,13,3,1,80,0,18,2,3,7,7,1,7 +46.0,No,Travel_Frequently,638.0,Research & Development,1.0,3,Medical,1,124,3,Male,40,2,3,Healthcare Representative,1,Married,10673,3142,2,Y,Yes,13,3,3,80,1,21,5,2,10,9,9,5 +54.0,No,Travel_Rarely,971.0,Research & Development,1.0,3,Medical,1,1422,4,Female,54,3,4,Research Director,4,Single,17328,5652,6,Y,No,19,3,4,80,0,29,3,2,20,7,12,7 +45.0,No,Non-Travel,805.0,Research & Development,4.0,2,Life Sciences,1,972,3,Male,57,3,2,Laboratory Technician,2,Married,4447,23163,1,Y,No,12,3,2,80,0,9,5,2,9,7,0,8 +27.0,No,Travel_Rarely,205.0,Sales,10.0,3,Marketing,1,1403,4,Female,98,2,2,Sales Executive,4,Married,5769,7100,1,Y,Yes,11,3,4,80,0,6,3,3,6,2,4,4 +45.0,No,Travel_Rarely,194.0,Research & Development,9.0,3,Life Sciences,1,206,2,Male,60,3,2,Laboratory Technician,2,Divorced,2348,10901,8,Y,No,18,3,3,80,1,20,2,1,17,9,0,15 +31.0,No,Travel_Rarely,196.0,Sales,29.0,4,Marketing,1,1784,1,Female,91,2,2,Sales Executive,4,Married,5468,13402,1,Y,No,14,3,1,80,2,13,3,3,12,7,5,7 +27.0,No,Travel_Rarely,155.0,Research & Development,4.0,3,Life Sciences,1,2064,2,Male,87,4,2,Manufacturing Director,2,Married,6142,5174,1,Y,Yes,20,4,2,80,1,6,0,3,6,2,0,3 +44.0,Yes,Travel_Rarely,1376.0,Human Resources,1.0,2,Medical,1,1098,2,Male,91,2,3,Human Resources,1,Married,10482,2326,9,Y,No,14,3,4,80,1,24,1,3,20,6,3,6 +,No,Travel_Rarely,384.0,Sales,8.0,4,Life Sciences,1,805,1,Female,72,3,1,Sales Representative,4,Married,2572,20317,1,Y,No,16,3,2,80,1,3,1,2,3,2,0,2 +38.0,No,Non-Travel,152.0,Sales,10.0,3,Technical Degree,1,983,3,Female,85,3,2,Sales Executive,4,Single,5666,19899,1,Y,Yes,13,3,2,80,0,6,1,3,5,3,1,3 +30.0,No,Travel_Rarely,793.0,Research & Development,16.0,1,Life Sciences,1,1729,2,Male,33,3,1,Research Scientist,4,Married,2862,3811,1,Y,No,12,3,2,80,1,10,2,2,10,0,0,8 +20.0,No,Travel_Rarely,959.0,Research & Development,1.0,3,Life Sciences,1,657,4,Female,83,2,1,Research Scientist,2,Single,2836,11757,1,Y,No,13,3,4,80,0,1,0,4,1,0,0,0 +38.0,No,Travel_Rarely,268.0,Research & Development,2.0,5,Medical,1,773,4,Male,92,3,1,Research Scientist,3,Married,3057,20471,6,Y,Yes,13,3,2,80,1,6,0,1,1,0,0,1 +50.0,Yes,Travel_Frequently,959.0,Sales,1.0,4,Other,1,1113,4,Male,81,3,2,Sales Executive,3,Single,4728,17251,3,Y,Yes,14,3,4,80,0,5,4,3,0,0,0,0 +27.0,No,Travel_Rarely,1115.0,Research & Development,,4,Medical,1,700,1,Male,54,2,1,Research Scientist,4,Single,2045,15174,0,Y,No,13,3,4,80,0,5,0,3,4,2,1,1 +36.0,No,Travel_Rarely,1278.0,Human Resources,8.0,3,Life Sciences,1,878,1,Male,77,2,1,Human Resources,1,Married,2342,8635,0,Y,No,21,4,3,80,0,6,3,3,5,4,0,3 +42.0,No,Travel_Rarely,1210.0,Research & Development,2.0,3,Medical,1,1542,3,Male,68,2,1,Laboratory Technician,2,Married,4841,24052,4,Y,No,14,3,2,80,1,4,3,3,1,0,0,0 +58.0,No,Travel_Frequently,1216.0,Research & Development,15.0,4,Life Sciences,1,1837,1,Male,87,3,4,Research Director,3,Married,15787,21624,2,Y,Yes,14,3,2,80,0,23,3,3,2,2,2,2 +33.0,No,Travel_Rarely,654.0,Research & Development,,3,Life Sciences,1,1099,4,Male,34,2,3,Healthcare Representative,4,Divorced,7119,21214,4,Y,No,15,3,3,80,1,9,2,3,3,2,1,2 +34.0,No,Travel_Rarely,1354.0,Research & Development,,3,Medical,1,153,3,Female,45,2,3,Manager,1,Single,11631,5615,2,Y,No,12,3,4,80,0,14,6,3,11,10,5,8 +,No,Travel_Rarely,802.0,Research & Development,10.0,3,Other,1,1028,2,Male,45,3,1,Laboratory Technician,4,Divorced,3917,9541,1,Y,No,20,4,1,80,1,3,4,2,3,2,1,2 +,No,Travel_Rarely,1029.0,Research & Development,16.0,3,Life Sciences,1,1529,4,Female,91,2,3,Healthcare Representative,2,Single,8606,21195,1,Y,No,19,3,4,80,0,11,3,1,11,8,3,3 +41.0,No,Travel_Rarely,167.0,Research & Development,12.0,4,Life Sciences,1,1158,2,Male,46,3,1,Laboratory Technician,4,Married,4766,9051,3,Y,Yes,11,3,1,80,1,6,4,3,1,0,0,0 +43.0,No,Travel_Frequently,394.0,Sales,26.0,2,Life Sciences,1,158,3,Male,92,3,4,Manager,4,Married,16959,19494,1,Y,Yes,12,3,4,80,2,25,3,4,25,12,4,12 +32.0,Yes,Travel_Rarely,374.0,Research & Development,25.0,4,Life Sciences,1,911,1,Male,87,3,1,Laboratory Technician,4,Single,2795,18016,1,Y,Yes,24,4,3,80,0,1,2,1,1,0,0,1 +,No,Travel_Rarely,607.0,Research & Development,9.0,3,Life Sciences,1,880,4,Female,66,2,3,Manufacturing Director,3,Married,10685,23457,1,Y,Yes,20,4,2,80,1,17,2,3,17,14,5,15 +31.0,No,Travel_Rarely,408.0,Research & Development,9.0,4,Life Sciences,1,493,3,Male,42,2,1,Research Scientist,2,Single,2657,7551,0,Y,Yes,16,3,4,80,0,3,5,3,2,2,2,2 +45.0,No,Travel_Rarely,1385.0,Research & Development,20.0,2,Medical,1,372,3,Male,79,3,4,Healthcare Representative,4,Married,13496,7501,0,Y,Yes,14,3,2,80,0,21,2,3,20,7,4,10 +33.0,No,Travel_Rarely,1075.0,Human Resources,,2,Human Resources,1,910,4,Male,57,3,1,Human Resources,2,Divorced,2277,22650,3,Y,Yes,11,3,3,80,1,7,4,4,4,3,0,3 +32.0,No,Travel_Rarely,604.0,Sales,8.0,3,Medical,1,1304,3,Male,56,4,2,Sales Executive,4,Married,6209,11693,1,Y,No,15,3,3,80,2,10,4,4,10,7,0,8 +34.0,No,Travel_Frequently,1003.0,Research & Development,2.0,2,Life Sciences,1,1140,4,Male,95,3,2,Manufacturing Director,3,Single,4033,15834,2,Y,No,11,3,4,80,0,5,3,2,3,2,0,2 +40.0,No,Travel_Frequently,1184.0,Sales,2.0,4,Medical,1,1212,2,Male,62,3,2,Sales Executive,2,Married,4327,25440,5,Y,No,12,3,4,80,3,5,2,3,0,0,0,0 +34.0,No,Non-Travel,1065.0,Sales,23.0,4,Marketing,1,60,2,Male,72,3,2,Sales Executive,3,Single,4568,10034,0,Y,No,20,4,3,80,0,10,2,3,9,5,8,7 +33.0,No,Non-Travel,775.0,Research & Development,4.0,3,Technical Degree,1,1771,4,Male,90,3,2,Research Scientist,2,Divorced,3055,6194,5,Y,No,15,3,4,80,2,11,2,2,9,8,1,7 +32.0,No,Travel_Rarely,499.0,Sales,2.0,1,Marketing,1,1396,3,Male,36,3,2,Sales Executive,2,Married,4078,20497,0,Y,Yes,13,3,1,80,3,4,3,2,3,2,1,2 +20.0,No,Travel_Rarely,654.0,Sales,21.0,3,Marketing,1,1226,3,Male,43,4,1,Sales Representative,4,Single,2678,5050,1,Y,No,17,3,4,80,0,2,2,3,2,1,2,2 +36.0,No,Travel_Rarely,796.0,Research & Development,12.0,5,Medical,1,1073,4,Female,51,2,3,Manufacturing Director,4,Single,8858,15669,0,Y,No,11,3,2,80,0,15,2,2,14,8,7,8 +27.0,No,Travel_Rarely,591.0,Research & Development,2.0,1,Medical,1,7,1,Male,40,3,1,Laboratory Technician,2,Married,3468,16632,9,Y,No,12,3,4,80,1,6,3,3,2,2,2,2 +,No,Travel_Rarely,949.0,Research & Development,1.0,3,Technical Degree,1,1415,1,Male,81,3,1,Laboratory Technician,4,Married,3229,4910,4,Y,No,11,3,2,80,1,7,2,2,3,2,0,2 +37.0,No,Travel_Rarely,589.0,Sales,9.0,2,Marketing,1,1787,2,Male,46,2,2,Sales Executive,2,Married,4189,8800,1,Y,No,14,3,1,80,2,5,2,3,5,2,0,3 +46.0,No,Travel_Rarely,488.0,Sales,2.0,3,Technical Degree,1,363,3,Female,75,1,4,Manager,2,Married,16872,14977,3,Y,Yes,12,3,2,80,1,28,2,2,7,7,7,7 +45.0,No,Travel_Rarely,1329.0,Research & Development,2.0,2,Other,1,1635,4,Female,59,2,2,Manufacturing Director,4,Divorced,5770,5388,1,Y,No,19,3,1,80,2,10,3,3,10,7,3,9 +34.0,No,Travel_Rarely,1480.0,Sales,4.0,3,Life Sciences,1,1882,3,Male,64,3,3,Sales Executive,4,Married,9713,24444,2,Y,Yes,13,3,4,80,3,9,3,3,5,3,1,0 +22.0,Yes,Travel_Frequently,1368.0,Research & Development,4.0,1,Technical Degree,1,593,3,Male,99,2,1,Laboratory Technician,3,Single,3894,9129,5,Y,No,16,3,3,80,0,4,3,3,2,2,1,2 +,No,Travel_Frequently,200.0,Research & Development,18.0,2,Life Sciences,1,1412,3,Male,60,3,3,Manufacturing Director,4,Single,9362,19944,2,Y,No,11,3,3,80,0,10,2,3,2,2,2,2 +29.0,Yes,Travel_Rarely,224.0,Research & Development,1.0,4,Technical Degree,1,1522,1,Male,100,2,1,Research Scientist,1,Single,2362,7568,6,Y,No,13,3,3,80,0,11,2,1,9,7,0,7 +40.0,No,Travel_Frequently,593.0,Research & Development,9.0,4,Medical,1,1166,2,Female,88,3,3,Research Director,3,Single,13499,13782,9,Y,No,17,3,3,80,0,20,3,2,18,7,2,13 +31.0,Yes,Travel_Rarely,359.0,Human Resources,18.0,5,Human Resources,1,1842,4,Male,89,4,1,Human Resources,1,Married,2956,21495,0,Y,No,17,3,3,80,0,2,4,3,1,0,0,0 +39.0,No,Travel_Rarely,1132.0,Research & Development,1.0,3,Medical,1,417,3,Male,48,4,3,Healthcare Representative,4,Divorced,9613,10942,0,Y,No,17,3,1,80,3,19,5,2,18,10,3,7 +,No,Travel_Rarely,580.0,Research & Development,27.0,3,Medical,1,1622,2,Female,39,1,2,Manufacturing Director,1,Divorced,4877,20460,0,Y,No,21,4,2,80,1,6,5,2,5,3,0,0 +33.0,No,Travel_Frequently,553.0,Research & Development,,4,Life Sciences,1,428,4,Female,74,3,3,Manager,2,Married,11878,23364,6,Y,No,11,3,2,80,2,12,2,3,10,6,8,8 +19.0,No,Travel_Rarely,1181.0,Research & Development,,1,Medical,1,201,2,Female,79,3,1,Laboratory Technician,2,Single,1483,16102,1,Y,No,14,3,4,80,0,1,3,3,1,0,0,0 +34.0,No,Travel_Rarely,182.0,Research & Development,1.0,4,Life Sciences,1,797,2,Female,72,4,1,Research Scientist,4,Single,3280,13551,2,Y,No,16,3,3,80,0,10,2,3,4,2,1,3 +48.0,Yes,Travel_Rarely,626.0,Research & Development,1.0,2,Life Sciences,1,64,1,Male,98,2,3,Laboratory Technician,3,Single,5381,19294,9,Y,Yes,13,3,4,80,0,23,2,3,1,0,0,0 +39.0,No,Travel_Rarely,1387.0,Research & Development,10.0,5,Medical,1,1618,2,Male,76,3,2,Manufacturing Director,1,Married,5377,3835,2,Y,No,13,3,4,80,3,10,3,3,7,7,7,7 +31.0,No,Travel_Frequently,853.0,Research & Development,1.0,1,Life Sciences,1,1011,3,Female,96,3,2,Manufacturing Director,1,Married,4148,11275,1,Y,No,12,3,3,80,1,4,1,3,4,3,0,3 +27.0,No,Travel_Rarely,199.0,Research & Development,6.0,3,Life Sciences,1,1162,4,Male,55,2,1,Research Scientist,3,Married,2539,7950,1,Y,No,13,3,3,80,1,4,0,3,4,2,2,2 +34.0,No,Travel_Rarely,479.0,Research & Development,7.0,4,Medical,1,1577,1,Male,35,3,1,Research Scientist,4,Single,2972,22061,1,Y,No,13,3,3,80,0,1,4,1,1,0,0,0 +24.0,No,Travel_Frequently,535.0,Sales,24.0,3,Medical,1,632,4,Male,38,3,1,Sales Representative,4,Married,2400,5530,0,Y,No,13,3,3,80,2,3,3,3,2,2,2,1 +51.0,No,Travel_Rarely,1405.0,Research & Development,11.0,2,Technical Degree,1,1367,4,Female,82,2,4,Manufacturing Director,2,Single,13142,24439,3,Y,No,16,3,2,80,0,29,1,2,5,2,0,3 +50.0,No,Non-Travel,881.0,Research & Development,2.0,4,Life Sciences,1,905,1,Male,98,3,4,Manager,1,Divorced,17924,4544,1,Y,No,11,3,4,80,1,31,3,3,31,6,14,7 +31.0,No,Travel_Rarely,329.0,Research & Development,1.0,2,Life Sciences,1,530,4,Male,98,2,1,Laboratory Technician,1,Married,2218,16193,1,Y,No,12,3,3,80,1,4,3,3,4,2,3,2 +36.0,No,Travel_Rarely,913.0,Research & Development,9.0,2,Medical,1,699,2,Male,48,2,2,Manufacturing Director,2,Divorced,8847,13934,2,Y,Yes,11,3,3,80,1,13,2,3,3,2,0,2 +27.0,No,Travel_Rarely,1377.0,Sales,2.0,3,Life Sciences,1,437,4,Male,74,3,2,Sales Executive,3,Single,4478,5242,1,Y,Yes,11,3,1,80,0,5,3,3,5,4,0,4 +38.0,No,Travel_Rarely,371.0,Research & Development,2.0,3,Life Sciences,1,24,4,Male,45,3,1,Research Scientist,4,Single,3944,4306,5,Y,Yes,11,3,3,80,0,6,3,3,3,2,1,2 +40.0,No,Travel_Rarely,658.0,Sales,10.0,4,Marketing,1,954,1,Male,67,2,3,Sales Executive,2,Divorced,9705,20652,2,Y,No,12,3,2,80,1,11,2,2,1,0,0,0 +43.0,No,Travel_Rarely,1273.0,Research & Development,2.0,2,Medical,1,46,4,Female,72,4,1,Research Scientist,3,Divorced,2645,21923,1,Y,No,12,3,4,80,2,6,3,2,5,3,1,4 +27.0,No,Travel_Rarely,1167.0,Research & Development,4.0,2,Life Sciences,1,1259,1,Male,76,3,1,Research Scientist,3,Divorced,2517,3208,1,Y,No,11,3,2,80,3,5,2,3,5,3,0,3 +,No,Travel_Frequently,773.0,Research & Development,6.0,3,Life Sciences,1,1154,3,Male,39,2,1,Research Scientist,3,Divorced,2703,22088,1,Y,Yes,14,3,4,80,1,3,2,3,3,1,0,2 +27.0,No,Travel_Frequently,1297.0,Research & Development,,2,Life Sciences,1,1850,4,Female,53,3,1,Laboratory Technician,4,Single,2379,19826,0,Y,Yes,14,3,3,80,0,6,3,2,5,4,0,2 +45.0,No,Travel_Rarely,,Research & Development,10.0,2,Life Sciences,1,544,1,Male,69,3,1,Research Scientist,4,Married,2654,9655,3,Y,No,21,4,4,80,2,8,3,2,2,2,0,2 +34.0,No,Travel_Frequently,135.0,Research & Development,19.0,3,Medical,1,1285,3,Female,46,3,2,Laboratory Technician,2,Divorced,4444,22534,4,Y,No,13,3,3,80,2,15,2,4,11,8,5,10 +27.0,No,Travel_Frequently,294.0,Research & Development,10.0,2,Life Sciences,1,733,4,Male,32,3,3,Manufacturing Director,1,Divorced,8793,4809,1,Y,No,21,4,3,80,2,9,4,2,9,7,1,7 +59.0,No,Travel_Rarely,1089.0,Sales,1.0,2,Technical Degree,1,1048,2,Male,66,3,3,Manager,4,Married,11904,11038,3,Y,Yes,14,3,3,80,1,14,1,1,6,4,0,4 +44.0,No,Travel_Frequently,1193.0,Research & Development,2.0,1,Medical,1,1496,2,Male,86,3,3,Manufacturing Director,3,Single,10209,19719,5,Y,Yes,18,3,2,80,0,16,2,2,2,2,2,2 +31.0,No,Travel_Frequently,1327.0,Research & Development,,4,Medical,1,337,2,Male,73,3,3,Research Director,3,Divorced,13675,13523,9,Y,No,12,3,1,80,1,9,3,3,2,2,2,2 +23.0,No,Travel_Rarely,977.0,Research & Development,10.0,3,Technical Degree,1,1592,4,Male,45,4,1,Research Scientist,3,Married,2073,12826,2,Y,No,16,3,4,80,1,4,2,3,2,2,2,2 +38.0,No,Travel_Rarely,330.0,Research & Development,17.0,1,Life Sciences,1,1088,3,Female,65,2,3,Healthcare Representative,3,Married,8823,24608,0,Y,No,18,3,1,80,1,20,4,2,19,9,1,9 +43.0,No,Travel_Rarely,782.0,Research & Development,6.0,4,Other,1,661,2,Male,50,2,4,Research Director,4,Divorced,16627,2671,4,Y,Yes,14,3,3,80,1,21,3,2,1,0,0,0 +32.0,No,Travel_Frequently,967.0,Sales,8.0,3,Marketing,1,207,2,Female,43,3,3,Sales Executive,4,Single,8998,15589,1,Y,No,14,3,4,80,0,9,2,3,9,8,3,7 +,No,Travel_Frequently,482.0,Research & Development,4.0,4,Life Sciences,1,1350,3,Male,87,3,2,Research Scientist,3,Single,4249,2690,1,Y,Yes,11,3,2,80,0,9,3,3,9,6,1,1 +19.0,No,Travel_Rarely,645.0,Research & Development,9.0,2,Life Sciences,1,1193,3,Male,54,3,1,Research Scientist,1,Single,2552,7172,1,Y,No,25,4,3,80,0,1,4,3,1,1,0,0 +45.0,No,Travel_Rarely,930.0,Sales,9.0,3,Marketing,1,864,4,Male,74,3,3,Sales Executive,1,Divorced,10761,19239,4,Y,Yes,12,3,3,80,1,18,2,3,5,4,0,2 +,No,Travel_Frequently,1283.0,Sales,1.0,3,Medical,1,956,3,Male,52,2,2,Sales Executive,1,Single,4294,11148,1,Y,No,12,3,2,80,0,7,2,3,7,7,0,7 +36.0,No,Non-Travel,1434.0,Sales,8.0,4,Life Sciences,1,789,1,Male,76,2,3,Sales Executive,1,Single,7587,14229,1,Y,No,15,3,2,80,0,10,1,3,10,7,0,9 +43.0,No,Travel_Rarely,574.0,Research & Development,11.0,3,Life Sciences,1,1971,1,Male,30,3,3,Healthcare Representative,3,Married,7510,16873,1,Y,No,17,3,2,80,1,10,1,3,10,9,0,9 +22.0,No,Non-Travel,1123.0,Research & Development,16.0,2,Medical,1,22,4,Male,96,4,1,Laboratory Technician,4,Divorced,2935,7324,1,Y,Yes,13,3,2,80,2,1,2,2,1,0,0,0 +19.0,Yes,Travel_Rarely,528.0,Sales,22.0,1,Marketing,1,167,4,Male,50,3,1,Sales Representative,3,Single,1675,26820,1,Y,Yes,19,3,4,80,0,0,2,2,0,0,0,0 +36.0,No,Travel_Rarely,429.0,Research & Development,2.0,4,Life Sciences,1,1294,3,Female,53,3,2,Manufacturing Director,2,Single,5410,2323,9,Y,Yes,11,3,4,80,0,18,2,3,16,14,5,12 +31.0,Yes,Travel_Frequently,703.0,Sales,2.0,3,Life Sciences,1,1379,3,Female,90,2,1,Sales Representative,4,Single,2785,11882,7,Y,No,14,3,3,80,0,3,3,4,1,0,0,0 +36.0,No,Travel_Frequently,688.0,Research & Development,4.0,2,Life Sciences,1,2025,4,Female,97,3,2,Manufacturing Director,2,Divorced,5131,9192,7,Y,No,13,3,2,80,3,18,3,3,4,2,0,2 +52.0,No,Travel_Rarely,699.0,Research & Development,1.0,4,Life Sciences,1,259,3,Male,65,2,5,Manager,3,Married,19999,5678,0,Y,No,14,3,1,80,1,34,5,3,33,18,11,9 +32.0,No,Travel_Rarely,634.0,Research & Development,,4,Other,1,1607,2,Female,35,4,1,Research Scientist,4,Married,3312,18783,3,Y,No,17,3,4,80,2,6,3,3,3,2,0,2 +39.0,No,Non-Travel,1485.0,Research & Development,25.0,2,Life Sciences,1,1397,3,Male,71,3,3,Healthcare Representative,3,Married,10920,3449,3,Y,No,21,4,2,80,1,13,2,3,6,4,0,5 +52.0,No,Non-Travel,585.0,Sales,29.0,4,Life Sciences,1,2019,1,Male,40,3,1,Sales Representative,4,Divorced,3482,19788,2,Y,No,15,3,2,80,2,16,3,2,9,8,0,0 +32.0,No,Travel_Frequently,585.0,Research & Development,10.0,3,Life Sciences,1,1720,1,Male,56,3,1,Research Scientist,3,Married,3433,17360,6,Y,No,13,3,1,80,1,10,3,2,5,2,1,3 +34.0,No,Travel_Frequently,702.0,Research & Development,16.0,4,Life Sciences,1,838,3,Female,100,2,1,Research Scientist,4,Single,2553,8306,1,Y,No,16,3,3,80,0,6,3,3,5,2,1,3 +31.0,No,Travel_Rarely,140.0,Research & Development,12.0,1,Medical,1,246,3,Female,95,3,1,Research Scientist,4,Married,3929,6984,8,Y,Yes,23,4,3,80,1,7,0,3,4,2,0,2 +18.0,No,Travel_Rarely,812.0,Sales,10.0,3,Medical,1,411,4,Female,69,2,1,Sales Representative,3,Single,1200,9724,1,Y,No,12,3,1,80,0,0,2,3,0,0,0,0 +21.0,No,Travel_Rarely,1343.0,Sales,22.0,1,Technical Degree,1,669,3,Male,49,3,1,Sales Representative,3,Single,3447,24444,1,Y,No,11,3,3,80,0,3,2,3,3,2,1,2 +36.0,No,Travel_Rarely,430.0,Research & Development,2.0,4,Other,1,1847,4,Female,73,3,2,Research Scientist,2,Married,6962,19573,4,Y,Yes,22,4,4,80,1,15,2,3,1,0,0,0 +24.0,No,Travel_Rarely,506.0,Research & Development,29.0,1,Medical,1,1725,2,Male,91,3,1,Laboratory Technician,1,Divorced,3907,3622,1,Y,No,13,3,2,80,3,6,2,4,6,2,1,2 +34.0,No,Travel_Rarely,678.0,Research & Development,19.0,3,Life Sciences,1,1701,2,Female,35,2,1,Research Scientist,4,Married,2929,20338,1,Y,No,12,3,2,80,0,10,3,3,10,9,8,7 +,No,Travel_Rarely,810.0,Sales,8.0,3,Life Sciences,1,707,4,Male,57,4,2,Sales Executive,2,Married,4851,15678,0,Y,No,22,4,3,80,1,4,4,3,3,2,1,2 +,No,Travel_Rarely,1423.0,Research & Development,1.0,3,Life Sciences,1,1506,1,Male,72,2,1,Research Scientist,3,Divorced,1563,12530,1,Y,No,14,3,4,80,1,1,2,1,1,0,0,0 +24.0,No,Travel_Rarely,,Research & Development,17.0,2,Other,1,643,4,Male,94,2,1,Laboratory Technician,2,Married,2127,9100,1,Y,No,21,4,4,80,1,1,2,3,1,0,0,0 +58.0,No,Travel_Rarely,1145.0,Research & Development,9.0,3,Medical,1,214,2,Female,75,2,1,Research Scientist,2,Married,3346,11873,4,Y,Yes,20,4,2,80,1,9,3,2,1,0,0,0 +32.0,No,Travel_Rarely,334.0,Research & Development,,2,Life Sciences,1,21,1,Male,80,4,1,Research Scientist,2,Divorced,3298,15053,0,Y,Yes,12,3,4,80,2,7,5,2,6,2,0,5 +29.0,No,Travel_Frequently,410.0,Research & Development,2.0,1,Life Sciences,1,1513,4,Female,97,3,1,Laboratory Technician,2,Married,3180,4668,0,Y,No,13,3,3,80,3,4,3,3,3,2,0,2 +29.0,No,Travel_Rarely,1396.0,Sales,10.0,3,Life Sciences,1,749,3,Male,99,3,1,Sales Representative,3,Single,2642,2755,1,Y,No,11,3,3,80,0,1,6,3,1,0,0,0 +44.0,No,Travel_Rarely,661.0,Research & Development,9.0,2,Life Sciences,1,913,2,Male,61,3,1,Research Scientist,1,Married,2559,7508,1,Y,Yes,13,3,4,80,0,8,0,3,8,7,7,1 +23.0,Yes,Travel_Rarely,1320.0,Research & Development,8.0,1,Medical,1,1684,4,Male,93,2,1,Laboratory Technician,3,Single,3989,20586,1,Y,Yes,11,3,1,80,0,5,2,3,5,4,1,2 +36.0,No,Travel_Rarely,329.0,Sales,16.0,4,Marketing,1,1436,3,Female,98,2,2,Sales Executive,1,Married,5647,13494,4,Y,No,13,3,1,80,2,11,3,2,3,2,0,2 +46.0,No,Travel_Rarely,717.0,Research & Development,13.0,4,Life Sciences,1,1727,3,Male,34,3,2,Healthcare Representative,2,Single,5562,9697,6,Y,No,14,3,4,80,0,19,3,3,10,7,0,9 +40.0,No,Travel_Rarely,523.0,Research & Development,2.0,3,Life Sciences,1,1346,3,Male,98,3,2,Research Scientist,4,Single,4661,22455,1,Y,No,13,3,3,80,0,9,4,3,9,8,8,8 +31.0,No,Non-Travel,976.0,Research & Development,,2,Medical,1,1948,3,Male,48,3,1,Research Scientist,1,Divorced,3065,3995,1,Y,Yes,13,3,4,80,1,4,3,4,4,2,2,3 +55.0,No,Travel_Rarely,147.0,Research & Development,20.0,2,Technical Degree,1,389,2,Male,37,3,2,Laboratory Technician,4,Married,5415,15972,3,Y,Yes,19,3,4,80,1,12,4,3,10,7,0,8 +,Yes,Travel_Rarely,1330.0,Research & Development,21.0,3,Medical,1,1107,1,Male,37,3,1,Laboratory Technician,3,Divorced,2377,19373,1,Y,No,20,4,3,80,1,1,0,2,1,1,0,0 +59.0,No,Travel_Rarely,142.0,Research & Development,,3,Life Sciences,1,309,3,Male,70,2,1,Research Scientist,4,Married,2177,8456,3,Y,No,17,3,1,80,1,7,6,3,1,0,0,0 +32.0,Yes,Travel_Frequently,1125.0,Research & Development,16.0,1,Life Sciences,1,33,2,Female,72,1,1,Research Scientist,1,Single,3919,4681,1,Y,Yes,22,4,2,80,0,10,5,3,10,2,6,7 +30.0,No,Travel_Rarely,413.0,Sales,7.0,1,Marketing,1,585,4,Male,57,3,1,Sales Representative,2,Single,2983,18398,0,Y,No,14,3,1,80,0,4,3,3,3,2,1,2 +32.0,No,Travel_Rarely,234.0,Sales,1.0,4,Medical,1,2013,2,Male,68,2,1,Sales Representative,2,Married,2269,18024,0,Y,No,14,3,2,80,1,3,2,3,2,2,2,2 +29.0,Yes,Travel_Rarely,896.0,Research & Development,18.0,1,Medical,1,315,3,Male,86,2,1,Research Scientist,4,Single,2389,14961,1,Y,Yes,13,3,3,80,0,4,3,2,4,3,0,1 +,No,Travel_Rarely,890.0,Sales,2.0,3,Marketing,1,49,4,Female,97,3,1,Sales Representative,4,Married,2014,9687,1,Y,No,13,3,1,80,0,2,3,3,2,2,2,2 +52.0,Yes,Travel_Rarely,266.0,Sales,2.0,1,Marketing,1,1038,1,Female,57,1,5,Manager,4,Married,19845,25846,1,Y,No,15,3,4,80,1,33,3,3,32,14,6,9 +40.0,No,Travel_Rarely,896.0,Research & Development,2.0,3,Medical,1,1474,3,Male,68,3,1,Research Scientist,3,Divorced,2345,8045,2,Y,No,14,3,3,80,1,8,3,4,3,1,1,2 +32.0,Yes,Non-Travel,1474.0,Sales,11.0,4,Other,1,631,4,Male,60,4,2,Sales Executive,3,Married,4707,23914,8,Y,No,12,3,4,80,0,6,2,3,4,2,1,2 +33.0,No,Non-Travel,1283.0,Sales,2.0,3,Marketing,1,1756,4,Female,62,3,2,Sales Executive,2,Single,5147,10697,8,Y,No,15,3,4,80,0,13,2,2,11,7,1,7 +42.0,No,Travel_Rarely,300.0,Research & Development,2.0,3,Life Sciences,1,2031,1,Male,56,3,5,Manager,3,Married,18880,17312,5,Y,No,11,3,1,80,0,24,2,2,22,6,4,14 +36.0,No,Travel_Rarely,938.0,Research & Development,2.0,4,Medical,1,958,3,Male,79,3,1,Laboratory Technician,3,Single,2519,12287,4,Y,No,21,4,3,80,0,16,6,3,11,8,3,9 +48.0,No,Travel_Frequently,117.0,Research & Development,22.0,3,Medical,1,1900,4,Female,58,3,4,Manager,4,Divorced,17174,2437,3,Y,No,11,3,2,80,1,24,3,3,22,17,4,7 +49.0,No,Travel_Rarely,1418.0,Research & Development,1.0,3,Technical Degree,1,887,3,Female,36,3,1,Research Scientist,1,Married,3580,10554,2,Y,No,16,3,2,80,1,7,2,3,4,2,0,2 +43.0,No,Travel_Rarely,244.0,Human Resources,2.0,3,Life Sciences,1,1778,2,Male,97,3,1,Human Resources,4,Single,3539,5033,0,Y,No,13,3,2,80,0,10,5,3,9,7,1,8 +37.0,No,Travel_Rarely,671.0,Research & Development,19.0,3,Life Sciences,1,1631,3,Male,85,3,2,Manufacturing Director,3,Married,5768,26493,3,Y,No,17,3,1,80,3,9,2,2,4,3,0,2 +45.0,No,Travel_Rarely,1005.0,Research & Development,28.0,2,Technical Degree,1,1719,4,Female,48,2,4,Research Director,2,Single,16704,17119,1,Y,No,11,3,3,80,0,21,2,3,21,6,8,6 +55.0,No,Travel_Rarely,,Research & Development,2.0,4,Technical Degree,1,1873,2,Male,98,2,1,Research Scientist,4,Married,2662,7975,8,Y,No,20,4,2,80,1,19,2,4,5,2,0,4 +,Yes,Travel_Frequently,1009.0,Research & Development,1.0,3,Medical,1,1111,1,Male,45,2,1,Laboratory Technician,2,Divorced,2596,7160,1,Y,No,15,3,1,80,2,1,2,3,1,0,0,0 +22.0,No,Travel_Rarely,1256.0,Research & Development,19.0,1,Medical,1,217,3,Male,80,3,1,Research Scientist,4,Married,2323,11992,1,Y,No,24,4,1,80,2,2,6,3,2,2,2,2 +56.0,No,Travel_Rarely,206.0,Human Resources,8.0,4,Life Sciences,1,1338,4,Male,99,3,5,Manager,2,Single,19717,4022,6,Y,No,14,3,1,80,0,36,4,3,7,3,7,7 +,Yes,Travel_Frequently,880.0,Sales,12.0,4,Other,1,1667,4,Male,36,3,2,Sales Executive,4,Single,4581,10414,3,Y,Yes,24,4,1,80,0,13,2,4,11,9,6,7 +49.0,No,Travel_Rarely,174.0,Sales,8.0,4,Technical Degree,1,1138,4,Male,56,2,4,Sales Executive,2,Married,13120,11879,6,Y,No,17,3,2,80,1,22,3,3,9,8,2,3 +24.0,No,Travel_Frequently,897.0,Human Resources,10.0,3,Medical,1,1746,1,Male,59,3,1,Human Resources,4,Married,2145,2097,0,Y,No,14,3,4,80,1,3,2,3,2,2,2,1 +46.0,No,Travel_Rarely,150.0,Research & Development,2.0,4,Technical Degree,1,1228,4,Male,60,3,2,Manufacturing Director,4,Divorced,7379,17433,2,Y,No,11,3,3,80,1,12,3,2,6,3,1,4 +45.0,Yes,Travel_Rarely,1449.0,Sales,2.0,3,Marketing,1,1277,1,Female,94,1,5,Manager,2,Single,18824,2493,2,Y,Yes,16,3,1,80,0,26,2,3,24,10,1,11 +53.0,No,Travel_Rarely,1436.0,Sales,6.0,2,Marketing,1,205,2,Male,34,3,2,Sales Representative,3,Married,2306,16047,2,Y,Yes,20,4,4,80,1,13,3,1,7,7,4,5 +45.0,No,Travel_Rarely,556.0,Research & Development,25.0,2,Life Sciences,1,1888,2,Female,93,2,2,Manufacturing Director,4,Married,5906,23888,0,Y,No,13,3,4,80,2,10,2,2,9,8,3,8 +33.0,No,Travel_Frequently,1296.0,Research & Development,6.0,3,Life Sciences,1,692,3,Male,30,3,2,Healthcare Representative,4,Divorced,7725,5335,3,Y,No,23,4,3,80,1,15,2,1,13,11,4,7 +46.0,No,Travel_Rarely,563.0,Sales,1.0,4,Life Sciences,1,1602,4,Male,56,4,4,Manager,1,Single,17567,3156,1,Y,No,15,3,2,80,0,27,5,1,26,0,0,12 +,No,Travel_Rarely,,Research & Development,27.0,4,Life Sciences,1,1728,4,Male,49,3,2,Manufacturing Director,3,Married,6883,5151,2,Y,No,16,3,2,80,1,17,3,3,7,7,0,7 +34.0,No,Travel_Rarely,665.0,Research & Development,6.0,4,Other,1,138,1,Female,41,3,2,Research Scientist,3,Single,4809,12482,1,Y,No,14,3,3,80,0,16,3,3,16,13,2,10 +24.0,No,Non-Travel,1092.0,Research & Development,9.0,3,Life Sciences,1,812,3,Male,60,2,1,Laboratory Technician,2,Divorced,2694,26551,1,Y,No,11,3,3,80,3,1,4,3,1,0,0,0 +,No,Travel_Rarely,185.0,Research & Development,23.0,4,Medical,1,1826,2,Male,91,1,1,Laboratory Technician,3,Married,2705,9696,0,Y,No,16,3,2,80,1,6,2,4,5,4,0,3 +45.0,No,Non-Travel,336.0,Sales,26.0,3,Marketing,1,1612,1,Male,52,2,2,Sales Executive,1,Married,4385,24162,1,Y,No,15,3,1,80,1,10,2,3,10,7,4,5 +,No,Non-Travel,1097.0,Research & Development,11.0,2,Medical,1,70,3,Male,79,2,3,Healthcare Representative,1,Married,9884,8302,2,Y,Yes,13,3,3,80,1,10,3,3,4,0,2,3 +,No,Travel_Rarely,662.0,Sales,1.0,5,Marketing,1,204,3,Male,94,3,3,Sales Executive,2,Married,7295,11439,1,Y,No,13,3,1,80,2,10,3,3,10,8,0,6 +41.0,No,Travel_Rarely,645.0,Sales,1.0,3,Marketing,1,534,2,Male,49,4,3,Sales Executive,1,Married,8392,19566,1,Y,No,16,3,3,80,1,10,2,3,10,7,0,7 +33.0,No,Travel_Rarely,,Research & Development,15.0,2,Medical,1,2009,2,Female,95,3,2,Healthcare Representative,4,Married,4878,21653,0,Y,Yes,13,3,1,80,1,10,6,3,9,7,8,1 +36.0,No,Travel_Frequently,635.0,Research & Development,18.0,1,Medical,1,286,2,Female,73,3,1,Laboratory Technician,4,Single,2153,7703,1,Y,No,13,3,1,80,0,8,2,3,8,1,1,7 +23.0,No,Travel_Rarely,571.0,Research & Development,12.0,2,Other,1,1982,4,Male,78,3,1,Laboratory Technician,4,Single,2647,13672,1,Y,No,13,3,3,80,0,5,6,4,5,2,1,4 +29.0,No,Travel_Rarely,,Research & Development,,1,Medical,1,1586,2,Male,87,3,1,Laboratory Technician,1,Single,4723,16213,1,Y,Yes,18,3,4,80,0,10,3,3,10,9,1,5 +38.0,No,Travel_Frequently,216.0,Research & Development,23.0,3,Life Sciences,1,12,4,Male,44,2,3,Manufacturing Director,3,Single,9526,8787,0,Y,No,21,4,2,80,0,10,2,3,9,7,1,8 +31.0,No,Travel_Rarely,182.0,Research & Development,8.0,5,Life Sciences,1,1430,1,Female,93,3,4,Research Director,2,Single,16422,8847,3,Y,No,11,3,3,80,0,9,3,4,3,2,1,0 +43.0,No,Travel_Frequently,1422.0,Sales,2.0,4,Life Sciences,1,1849,1,Male,92,3,2,Sales Executive,4,Married,5675,19246,1,Y,No,20,4,3,80,1,7,5,3,7,7,7,7 +24.0,Yes,Travel_Frequently,381.0,Research & Development,9.0,3,Medical,1,1494,2,Male,89,3,1,Laboratory Technician,1,Single,3172,16998,2,Y,Yes,11,3,3,80,0,4,2,2,0,0,0,0 +45.0,No,Travel_Rarely,561.0,Sales,2.0,3,Other,1,606,4,Male,61,3,2,Sales Executive,2,Married,4805,16177,0,Y,No,19,3,2,80,1,9,3,4,8,7,3,7 +42.0,No,Travel_Rarely,916.0,Research & Development,17.0,2,Life Sciences,1,347,4,Female,82,4,2,Research Scientist,1,Single,6545,23016,3,Y,Yes,13,3,3,80,0,10,1,3,3,2,0,2 +31.0,No,Travel_Rarely,1062.0,Research & Development,24.0,3,Medical,1,1252,3,Female,96,2,2,Healthcare Representative,1,Single,6812,17198,1,Y,No,19,3,2,80,0,10,2,3,10,9,1,8 +,No,Travel_Rarely,1181.0,Research & Development,1.0,3,Life Sciences,1,1799,3,Male,82,3,1,Research Scientist,4,Married,2044,5531,1,Y,No,11,3,3,80,1,5,6,4,5,3,0,3 +32.0,No,Travel_Frequently,116.0,Research & Development,13.0,3,Other,1,1234,3,Female,77,2,1,Laboratory Technician,2,Married,2743,7331,1,Y,No,20,4,3,80,1,2,2,3,2,2,2,2 +,No,Travel_Rarely,157.0,Research & Development,1.0,3,Medical,1,1952,3,Male,95,3,1,Laboratory Technician,1,Single,2867,20006,0,Y,No,13,3,4,80,0,8,6,2,7,7,7,6 +30.0,No,Travel_Frequently,1012.0,Research & Development,,4,Life Sciences,1,861,2,Male,75,2,1,Research Scientist,4,Divorced,3761,2373,9,Y,No,12,3,2,80,1,10,3,2,5,4,0,3 +23.0,No,Travel_Rarely,1309.0,Research & Development,26.0,1,Life Sciences,1,465,3,Male,83,3,1,Research Scientist,4,Divorced,2904,16092,1,Y,No,12,3,3,80,2,4,2,2,4,2,0,2 +38.0,No,Travel_Rarely,833.0,Research & Development,18.0,3,Medical,1,1766,2,Male,60,1,2,Healthcare Representative,4,Married,5811,24539,3,Y,Yes,16,3,3,80,1,15,2,3,1,0,1,0 +32.0,No,Travel_Rarely,128.0,Research & Development,2.0,1,Technical Degree,1,362,4,Male,84,2,2,Laboratory Technician,1,Single,2176,19737,4,Y,No,13,3,4,80,0,9,5,3,6,2,0,4 +40.0,No,Travel_Frequently,1395.0,Research & Development,26.0,3,Medical,1,202,2,Female,54,3,2,Research Scientist,2,Divorced,5605,8504,1,Y,No,11,3,1,80,1,20,2,3,20,7,2,13 +37.0,No,Travel_Rarely,446.0,Research & Development,1.0,4,Life Sciences,1,635,2,Female,65,3,2,Manufacturing Director,2,Married,6447,15701,6,Y,No,12,3,2,80,1,8,2,2,6,5,4,3 +24.0,No,Non-Travel,1269.0,Research & Development,4.0,1,Life Sciences,1,888,1,Male,46,2,1,Laboratory Technician,4,Married,3162,10778,0,Y,No,17,3,4,80,0,6,2,2,5,2,3,4 +40.0,No,Travel_Rarely,1322.0,Research & Development,2.0,4,Life Sciences,1,2048,3,Male,52,2,1,Research Scientist,3,Single,2809,2725,2,Y,No,14,3,4,80,0,8,2,3,2,2,2,2 +36.0,No,Non-Travel,1351.0,Research & Development,9.0,4,Life Sciences,1,1949,1,Male,66,4,1,Laboratory Technician,2,Married,2810,9238,1,Y,No,22,4,2,80,0,5,3,3,5,4,0,2 +23.0,No,Travel_Rarely,650.0,Research & Development,9.0,1,Medical,1,758,2,Male,37,3,1,Laboratory Technician,1,Married,2500,4344,1,Y,No,14,3,4,80,1,5,2,4,4,3,0,2 +44.0,Yes,Travel_Rarely,621.0,Research & Development,15.0,3,Medical,1,1295,1,Female,73,3,3,Healthcare Representative,4,Married,7978,14075,1,Y,No,11,3,4,80,1,10,2,3,10,7,0,5 +42.0,No,Travel_Rarely,622.0,Research & Development,2.0,4,Life Sciences,1,659,3,Female,81,3,2,Healthcare Representative,4,Married,4089,5718,1,Y,No,13,3,2,80,2,10,4,3,10,2,2,2 +29.0,No,Travel_Rarely,352.0,Human Resources,6.0,1,Medical,1,1865,4,Male,87,2,1,Human Resources,2,Married,2804,15434,1,Y,No,11,3,4,80,0,1,3,3,1,0,0,0 +40.0,Yes,Travel_Rarely,1329.0,Research & Development,7.0,3,Life Sciences,1,1649,1,Male,73,3,1,Laboratory Technician,1,Single,2166,3339,3,Y,Yes,14,3,2,80,0,10,3,1,4,2,0,3 +30.0,No,Travel_Rarely,1427.0,Research & Development,2.0,1,Medical,1,198,2,Male,35,2,1,Laboratory Technician,4,Single,2720,11162,0,Y,No,13,3,4,80,0,6,3,3,5,3,1,2 +30.0,No,Travel_Rarely,1082.0,Sales,12.0,3,Technical Degree,1,533,2,Female,83,3,2,Sales Executive,3,Single,6577,19558,0,Y,No,11,3,2,80,0,6,6,3,5,4,4,4 +42.0,No,Non-Travel,495.0,Research & Development,2.0,1,Life Sciences,1,1334,3,Male,37,3,4,Manager,3,Married,17861,26582,0,Y,Yes,13,3,4,80,0,21,3,2,20,8,2,10 +42.0,No,Travel_Rarely,419.0,Sales,12.0,4,Marketing,1,1943,2,Male,77,3,2,Sales Executive,4,Divorced,5087,2900,3,Y,Yes,12,3,3,80,2,14,4,3,0,0,0,0 +,No,Travel_Rarely,821.0,Sales,,4,Medical,1,916,1,Male,98,3,2,Sales Executive,4,Single,4908,24252,1,Y,No,14,3,2,80,0,4,3,3,4,2,0,2 +,Yes,Travel_Rarely,471.0,Research & Development,24.0,3,Technical Degree,1,622,3,Male,66,1,1,Laboratory Technician,4,Single,2340,23213,1,Y,Yes,18,3,2,80,0,1,3,1,1,0,0,0 +40.0,No,Travel_Rarely,989.0,Research & Development,4.0,1,Medical,1,253,4,Female,46,3,5,Manager,3,Married,19033,6499,1,Y,No,14,3,2,80,1,21,2,3,20,8,9,9 +49.0,No,Travel_Rarely,722.0,Research & Development,25.0,4,Life Sciences,1,1617,3,Female,84,3,1,Laboratory Technician,1,Married,3211,22102,1,Y,No,14,3,4,80,1,10,3,2,9,6,1,4 +,No,Travel_Rarely,390.0,Research & Development,17.0,4,Medical,1,1718,4,Male,62,1,1,Laboratory Technician,3,Married,2305,6217,1,Y,No,15,3,3,80,3,3,3,4,3,2,0,2 +55.0,Yes,Travel_Rarely,436.0,Sales,2.0,1,Medical,1,842,3,Male,37,3,2,Sales Executive,4,Single,5160,21519,4,Y,No,16,3,3,80,0,12,3,2,9,7,7,3 +30.0,No,Travel_Rarely,438.0,Research & Development,18.0,3,Life Sciences,1,194,1,Female,75,3,1,Research Scientist,3,Single,2632,23910,1,Y,No,14,3,3,80,0,5,4,2,5,4,0,4 +50.0,No,Non-Travel,145.0,Sales,1.0,3,Life Sciences,1,1040,4,Female,95,3,2,Sales Executive,3,Married,6347,24920,0,Y,No,12,3,1,80,1,19,3,3,18,7,0,13 +,Yes,Travel_Frequently,662.0,Sales,18.0,4,Marketing,1,1380,4,Female,67,3,2,Sales Executive,3,Married,4614,23288,0,Y,Yes,18,3,3,80,1,5,0,2,4,2,3,2 +42.0,No,Non-Travel,926.0,Research & Development,21.0,2,Medical,1,270,3,Female,36,3,2,Manufacturing Director,3,Divorced,5265,16439,2,Y,No,16,3,2,80,1,11,5,3,5,3,0,2 +33.0,No,Travel_Rarely,117.0,Research & Development,9.0,3,Medical,1,1238,1,Male,60,3,1,Research Scientist,4,Married,2781,6311,0,Y,No,13,3,2,80,1,15,5,3,14,10,4,10 +50.0,No,Travel_Rarely,797.0,Research & Development,4.0,1,Life Sciences,1,385,1,Male,96,3,5,Research Director,2,Divorced,19144,15815,3,Y,No,14,3,1,80,2,28,4,2,10,4,1,6 +,Yes,Travel_Rarely,950.0,Sales,4.0,4,Marketing,1,401,4,Male,48,2,2,Sales Executive,4,Single,5828,8450,1,Y,Yes,12,3,2,80,0,8,0,3,8,7,7,4 +29.0,Yes,Travel_Rarely,1092.0,Research & Development,1.0,4,Medical,1,2027,1,Male,36,3,1,Research Scientist,4,Married,4787,26124,9,Y,Yes,14,3,2,80,3,4,3,4,2,2,2,2 +39.0,No,Travel_Frequently,1218.0,Research & Development,1.0,1,Life Sciences,1,531,2,Male,52,3,5,Manager,3,Divorced,19197,8213,1,Y,Yes,14,3,3,80,1,21,3,3,21,8,1,6 +56.0,Yes,Travel_Rarely,441.0,Research & Development,14.0,4,Life Sciences,1,161,2,Female,72,3,1,Research Scientist,2,Married,4963,4510,9,Y,Yes,18,3,1,80,3,7,2,3,5,4,4,3 +55.0,No,Travel_Rarely,1441.0,Research & Development,22.0,3,Technical Degree,1,1694,1,Male,94,2,1,Research Scientist,2,Divorced,3537,23737,5,Y,No,12,3,4,80,1,8,1,3,4,2,1,2 +34.0,No,Travel_Frequently,878.0,Research & Development,10.0,4,Medical,1,277,4,Male,43,3,1,Research Scientist,3,Divorced,3815,5972,1,Y,Yes,17,3,4,80,1,5,4,4,5,3,2,0 +,No,Travel_Rarely,528.0,Human Resources,8.0,4,Technical Degree,1,1164,3,Male,100,3,1,Human Resources,3,Single,4323,7108,1,Y,No,17,3,2,80,0,6,2,1,5,4,1,4 +33.0,No,Travel_Rarely,832.0,Research & Development,,4,Life Sciences,1,338,3,Female,63,2,1,Research Scientist,4,Married,2911,14776,1,Y,No,13,3,3,80,1,2,2,2,2,2,0,2 +31.0,Yes,Travel_Frequently,754.0,Sales,26.0,4,Marketing,1,1967,1,Male,63,3,2,Sales Executive,4,Married,5617,21075,1,Y,Yes,11,3,3,80,0,10,4,3,10,7,0,8 +,No,Non-Travel,1103.0,Research & Development,16.0,3,Medical,1,1947,3,Male,49,3,1,Research Scientist,3,Single,2144,2122,1,Y,No,14,3,3,80,0,5,3,2,5,3,1,4 +18.0,Yes,Travel_Frequently,544.0,Sales,,2,Medical,1,1624,2,Female,70,3,1,Sales Representative,4,Single,1569,18420,1,Y,Yes,12,3,3,80,0,0,2,4,0,0,0,0 +36.0,No,Travel_Rarely,164.0,Sales,2.0,2,Medical,1,513,2,Male,61,2,3,Sales Executive,3,Married,7596,3809,1,Y,No,13,3,2,80,2,10,2,3,10,9,9,0 +30.0,No,Travel_Rarely,1092.0,Research & Development,10.0,3,Medical,1,1816,1,Female,64,3,3,Manufacturing Director,3,Single,9667,2739,9,Y,No,14,3,2,80,0,9,3,3,7,7,0,2 +45.0,No,Travel_Rarely,1457.0,Research & Development,7.0,3,Medical,1,1195,1,Female,83,3,1,Research Scientist,3,Married,4477,20100,4,Y,Yes,19,3,3,80,1,7,2,2,3,2,0,2 +54.0,No,Travel_Rarely,1147.0,Sales,,3,Marketing,1,303,4,Female,52,3,2,Sales Executive,1,Married,5940,17011,2,Y,No,14,3,4,80,1,16,4,3,6,2,0,5 +32.0,No,Travel_Frequently,379.0,Sales,,2,Life Sciences,1,889,2,Male,48,3,2,Sales Executive,2,Married,6524,8891,1,Y,No,14,3,4,80,1,10,3,3,10,8,5,3 +49.0,No,Travel_Frequently,279.0,Research & Development,8.0,1,Life Sciences,1,2,3,Male,61,2,2,Research Scientist,2,Married,5130,24907,1,Y,No,23,4,4,80,1,10,3,3,10,7,1,7 +54.0,No,Non-Travel,142.0,Human Resources,26.0,3,Human Resources,1,148,4,Female,30,4,4,Manager,4,Single,17328,13871,2,Y,Yes,12,3,3,80,0,23,3,3,5,3,4,4 +,No,Travel_Rarely,1219.0,Sales,18.0,3,Medical,1,975,3,Female,86,3,2,Sales Executive,3,Married,4601,6179,1,Y,No,16,3,2,80,0,5,3,3,5,2,1,0 +31.0,No,Travel_Rarely,1276.0,Research & Development,2.0,1,Medical,1,1974,4,Female,59,1,1,Laboratory Technician,4,Divorced,1129,17536,1,Y,Yes,11,3,3,80,3,1,4,3,1,0,0,0 +41.0,No,Non-Travel,256.0,Sales,10.0,2,Medical,1,1329,3,Male,40,1,2,Sales Executive,2,Single,6151,22074,1,Y,No,13,3,1,80,0,19,4,3,19,2,11,9 +37.0,Yes,Travel_Rarely,,Research & Development,10.0,4,Medical,1,1809,4,Male,58,3,2,Manufacturing Director,1,Single,4213,4992,1,Y,No,15,3,2,80,0,10,4,1,10,3,0,8 +32.0,Yes,Travel_Rarely,414.0,Sales,2.0,4,Marketing,1,1862,3,Male,82,2,2,Sales Executive,2,Single,9907,26186,7,Y,Yes,12,3,3,80,0,7,3,2,2,2,2,2 +42.0,No,Travel_Frequently,1474.0,Research & Development,,2,Other,1,591,2,Male,97,3,1,Laboratory Technician,3,Married,2093,9260,4,Y,No,17,3,4,80,1,8,4,3,2,2,2,0 +,Yes,Travel_Rarely,329.0,Research & Development,24.0,3,Medical,1,1604,3,Male,51,3,1,Laboratory Technician,2,Married,2408,7324,1,Y,Yes,17,3,3,80,3,1,3,3,1,1,0,0 +38.0,No,Travel_Frequently,594.0,Research & Development,2.0,2,Medical,1,1760,3,Female,75,2,1,Laboratory Technician,2,Married,2468,15963,4,Y,No,14,3,2,80,1,9,4,2,6,1,0,5 +21.0,Yes,Travel_Rarely,1427.0,Research & Development,18.0,1,Other,1,923,4,Female,65,3,1,Research Scientist,4,Single,2693,8870,1,Y,No,19,3,1,80,0,1,3,2,1,0,0,0 +,No,Travel_Rarely,219.0,Research & Development,16.0,2,Other,1,1886,4,Female,44,2,2,Manufacturing Director,2,Married,4788,25388,0,Y,Yes,11,3,4,80,0,4,2,3,3,2,0,2 +31.0,Yes,Travel_Rarely,1079.0,Sales,16.0,4,Marketing,1,1761,1,Male,70,3,3,Sales Executive,3,Married,8161,19002,2,Y,No,13,3,1,80,3,10,2,3,1,0,0,0 +40.0,No,Travel_Rarely,750.0,Research & Development,12.0,3,Life Sciences,1,1829,2,Female,47,3,2,Healthcare Representative,1,Divorced,4448,10748,2,Y,No,12,3,2,80,1,15,3,3,7,4,7,7 +52.0,Yes,Travel_Rarely,723.0,Research & Development,8.0,4,Medical,1,433,3,Male,85,2,2,Research Scientist,2,Married,4941,17747,2,Y,No,15,3,1,80,0,11,3,2,8,2,7,7 +37.0,No,Travel_Frequently,1231.0,Sales,21.0,2,Medical,1,900,3,Female,54,3,1,Sales Representative,4,Married,2973,21222,5,Y,No,15,3,2,80,1,10,3,3,5,4,0,0 +31.0,Yes,Non-Travel,335.0,Research & Development,9.0,2,Medical,1,991,3,Male,46,2,1,Research Scientist,1,Single,2321,10322,0,Y,Yes,22,4,1,80,0,4,0,3,3,2,1,2 +33.0,No,Travel_Rarely,867.0,Research & Development,8.0,4,Life Sciences,1,1798,4,Male,90,4,1,Research Scientist,1,Married,3143,6076,6,Y,No,19,3,2,80,1,14,1,3,10,8,7,6 +18.0,No,Non-Travel,1124.0,Research & Development,1.0,3,Life Sciences,1,1368,4,Female,97,3,1,Laboratory Technician,4,Single,1611,19305,1,Y,No,15,3,3,80,0,0,5,4,0,0,0,0 +52.0,No,Travel_Frequently,890.0,Research & Development,25.0,4,Medical,1,867,3,Female,81,2,4,Manufacturing Director,4,Married,13826,19028,3,Y,No,22,4,3,80,0,31,3,3,9,8,0,0 +42.0,No,Travel_Frequently,1271.0,Research & Development,2.0,1,Medical,1,875,2,Male,35,3,1,Research Scientist,4,Single,2515,9068,5,Y,Yes,14,3,4,80,0,8,2,3,2,1,2,2 +27.0,No,Travel_Rarely,1054.0,Research & Development,8.0,3,Medical,1,1751,3,Female,67,3,1,Research Scientist,4,Single,3445,6152,1,Y,No,11,3,3,80,0,6,5,2,6,2,1,4 +37.0,No,Travel_Rarely,161.0,Research & Development,10.0,3,Life Sciences,1,2017,3,Female,42,4,3,Research Director,4,Married,13744,15471,1,Y,Yes,25,4,1,80,1,16,2,3,16,11,6,8 +49.0,No,Travel_Rarely,1313.0,Sales,11.0,4,Marketing,1,1757,4,Female,80,3,2,Sales Executive,4,Single,4507,8191,3,Y,No,12,3,3,80,0,8,1,4,5,1,0,4 +41.0,No,Travel_Rarely,337.0,Sales,8.0,3,Marketing,1,1909,3,Female,54,3,2,Sales Executive,2,Married,4393,26841,5,Y,No,21,4,3,80,1,14,3,3,5,4,1,4 +37.0,No,Travel_Rarely,309.0,Sales,10.0,4,Life Sciences,1,1105,4,Female,88,2,2,Sales Executive,4,Divorced,6694,24223,2,Y,Yes,14,3,3,80,3,8,5,3,1,0,0,0 +29.0,Yes,Travel_Rarely,341.0,Sales,1.0,3,Medical,1,896,2,Female,48,2,1,Sales Representative,3,Divorced,2800,23522,6,Y,Yes,19,3,3,80,3,5,3,3,3,2,0,2 +31.0,Yes,Travel_Frequently,667.0,Sales,1.0,4,Life Sciences,1,1427,2,Female,50,1,1,Sales Representative,3,Single,1359,16154,1,Y,No,12,3,2,80,0,1,3,3,1,0,0,0 +53.0,No,Travel_Rarely,346.0,Research & Development,6.0,3,Life Sciences,1,769,4,Male,86,3,2,Laboratory Technician,4,Single,2450,10919,2,Y,No,17,3,4,80,0,19,4,3,2,2,2,2 +38.0,No,Travel_Rarely,1333.0,Research & Development,1.0,3,Technical Degree,1,950,4,Female,80,3,3,Research Director,1,Married,13582,16292,1,Y,No,13,3,2,80,1,15,3,3,15,12,5,11 +37.0,No,Travel_Rarely,571.0,Research & Development,10.0,1,Life Sciences,1,802,4,Female,82,3,1,Research Scientist,1,Divorced,2782,19905,0,Y,Yes,13,3,2,80,2,6,3,2,5,3,4,3 +30.0,No,Travel_Rarely,1288.0,Sales,29.0,4,Technical Degree,1,1568,3,Male,33,3,3,Sales Executive,2,Married,9250,17799,3,Y,No,12,3,2,80,1,9,3,3,4,2,1,3 +41.0,No,Travel_Rarely,548.0,Research & Development,9.0,4,Life Sciences,1,1772,3,Male,94,3,1,Laboratory Technician,1,Divorced,2289,20520,1,Y,No,20,4,2,80,2,5,2,3,5,3,0,4 +36.0,No,Travel_Rarely,1040.0,Research & Development,,2,Life Sciences,1,1664,4,Male,79,4,2,Healthcare Representative,1,Divorced,6842,26308,6,Y,No,20,4,1,80,1,13,3,3,5,4,0,4 +34.0,No,Travel_Rarely,1442.0,Research & Development,9.0,3,Medical,1,717,4,Female,46,2,3,Healthcare Representative,2,Single,8621,17654,1,Y,No,14,3,2,80,0,9,3,4,8,7,7,7 +,No,Travel_Rarely,660.0,Sales,7.0,1,Life Sciences,1,1492,4,Male,76,3,1,Sales Representative,3,Married,2404,16192,1,Y,No,13,3,1,80,1,1,3,3,1,0,0,0 +,Yes,Travel_Rarely,654.0,Research & Development,1.0,2,Life Sciences,1,741,1,Female,67,1,1,Research Scientist,2,Single,2216,3872,7,Y,Yes,13,3,4,80,0,10,4,3,7,7,3,7 +47.0,No,Travel_Rarely,1225.0,Sales,2.0,4,Life Sciences,1,1676,2,Female,47,4,4,Manager,2,Divorced,15972,21086,6,Y,No,14,3,3,80,3,29,2,3,3,2,1,2 +,Yes,Non-Travel,265.0,Sales,29.0,2,Medical,1,1037,2,Male,79,1,2,Sales Executive,1,Single,4969,21813,8,Y,No,18,3,4,80,0,7,6,3,2,2,2,2 +34.0,No,Travel_Rarely,735.0,Sales,,1,Medical,1,1915,4,Female,75,2,2,Sales Executive,4,Married,8103,16495,3,Y,Yes,12,3,3,80,0,9,3,2,4,2,0,1 +31.0,No,Travel_Rarely,525.0,Sales,6.0,4,Medical,1,653,1,Male,66,4,2,Sales Executive,4,Divorced,5460,6219,4,Y,No,22,4,4,80,2,13,4,4,7,7,5,7 +54.0,No,Travel_Rarely,1217.0,Research & Development,2.0,4,Technical Degree,1,126,1,Female,60,3,3,Research Director,3,Married,13549,24001,9,Y,No,12,3,1,80,1,16,5,1,4,3,0,3 +47.0,No,Travel_Rarely,465.0,Research & Development,1.0,3,Technical Degree,1,1438,1,Male,74,3,1,Research Scientist,4,Married,3420,10205,7,Y,No,12,3,3,80,1,17,2,2,6,5,1,2 +,No,Travel_Rarely,883.0,Sales,26.0,1,Medical,1,781,3,Female,32,3,2,Sales Executive,4,Single,6180,22807,1,Y,No,23,4,2,80,0,6,5,2,6,5,1,4 +55.0,No,Travel_Rarely,478.0,Research & Development,2.0,3,Medical,1,1770,3,Male,60,2,5,Research Director,1,Married,19038,19805,8,Y,No,12,3,2,80,3,34,2,3,1,0,0,0 +50.0,No,Travel_Rarely,804.0,Research & Development,9.0,3,Life Sciences,1,1030,1,Male,64,3,1,Laboratory Technician,4,Married,2380,20165,4,Y,No,18,3,2,80,0,8,5,3,1,0,0,0 +33.0,No,Travel_Rarely,147.0,Human Resources,2.0,3,Human Resources,1,1207,2,Male,99,3,1,Human Resources,3,Married,3600,8429,1,Y,No,13,3,4,80,1,5,2,3,5,4,1,4 +44.0,No,Travel_Rarely,1117.0,Research & Development,2.0,1,Life Sciences,1,1246,1,Female,72,4,1,Research Scientist,4,Married,2011,19982,1,Y,No,13,3,4,80,1,10,5,3,10,5,7,7 +48.0,No,Travel_Rarely,1221.0,Sales,7.0,3,Marketing,1,1466,3,Male,96,3,2,Sales Executive,1,Divorced,5486,24795,4,Y,No,11,3,1,80,3,15,3,3,2,2,2,2 +22.0,No,Travel_Rarely,1136.0,Research & Development,,3,Life Sciences,1,284,4,Male,60,4,1,Research Scientist,2,Divorced,2328,12392,1,Y,Yes,16,3,1,80,1,4,2,2,4,2,2,2 +54.0,No,Travel_Rarely,821.0,Research & Development,,2,Medical,1,522,1,Male,86,3,5,Research Director,1,Married,19406,8509,4,Y,No,11,3,3,80,1,24,4,2,4,2,1,2 +34.0,No,Travel_Frequently,618.0,Research & Development,,1,Life Sciences,1,1103,1,Male,45,3,2,Healthcare Representative,4,Single,7756,22266,0,Y,No,17,3,3,80,0,7,1,2,6,2,0,4 +,No,Travel_Rarely,1361.0,Sales,17.0,4,Life Sciences,1,1218,3,Male,94,3,2,Sales Executive,1,Married,8966,21026,3,Y,Yes,15,3,4,80,3,15,2,3,7,7,1,7 +,No,Travel_Rarely,891.0,Sales,4.0,2,Life Sciences,1,527,2,Female,99,2,2,Sales Executive,4,Single,4487,12090,1,Y,Yes,11,3,2,80,0,5,3,3,5,4,1,3 +50.0,No,Travel_Rarely,1464.0,Research & Development,2.0,4,Medical,1,1061,2,Male,62,3,5,Research Director,3,Married,19237,12853,2,Y,Yes,11,3,4,80,1,29,2,2,8,1,7,7 +,No,Travel_Rarely,482.0,Research & Development,1.0,2,Life Sciences,1,1893,2,Female,90,2,1,Research Scientist,3,Married,2933,14908,1,Y,Yes,13,3,3,80,1,1,3,2,1,0,1,0 +32.0,No,Travel_Rarely,371.0,Sales,19.0,3,Life Sciences,1,1739,4,Male,80,1,3,Sales Executive,3,Married,9610,3840,3,Y,No,13,3,3,80,1,10,2,1,4,3,0,2 +41.0,No,Travel_Rarely,1283.0,Research & Development,,5,Medical,1,1448,2,Male,90,4,1,Research Scientist,3,Married,2127,5561,2,Y,Yes,12,3,1,80,0,7,5,2,4,2,0,3 +38.0,No,Travel_Rarely,395.0,Sales,9.0,3,Marketing,1,893,2,Male,98,2,1,Sales Representative,2,Married,2899,12102,0,Y,No,19,3,4,80,1,3,3,3,2,2,1,2 +,No,Travel_Rarely,760.0,Sales,2.0,4,Marketing,1,846,2,Female,81,3,2,Sales Executive,2,Married,4779,3698,1,Y,Yes,20,4,1,80,0,8,2,3,8,7,7,5 +41.0,No,Travel_Frequently,1018.0,Sales,1.0,3,Marketing,1,1349,3,Female,66,3,2,Sales Executive,1,Divorced,4103,4297,0,Y,No,17,3,4,80,1,10,2,3,9,3,1,7 +,Yes,Travel_Rarely,622.0,Research & Development,14.0,4,Other,1,1010,3,Male,39,2,1,Laboratory Technician,2,Divorced,3743,10074,1,Y,Yes,24,4,4,80,1,5,2,1,4,2,0,2 +,Yes,Travel_Rarely,867.0,Sales,19.0,2,Marketing,1,952,3,Male,36,2,1,Sales Representative,2,Married,2413,18798,1,Y,Yes,18,3,3,80,3,1,2,3,1,0,0,0 +58.0,No,Travel_Rarely,682.0,Sales,10.0,4,Medical,1,131,4,Male,37,3,4,Sales Executive,3,Single,13872,24409,0,Y,No,13,3,3,80,0,38,1,2,37,10,1,8 +48.0,No,Non-Travel,1262.0,Research & Development,1.0,4,Medical,1,1116,1,Male,35,4,4,Manager,4,Single,16885,16154,2,Y,No,22,4,3,80,0,27,3,2,5,4,2,1 +52.0,No,Travel_Rarely,319.0,Research & Development,,3,Medical,1,543,4,Male,39,2,3,Manufacturing Director,3,Married,7969,19609,2,Y,Yes,14,3,3,80,0,28,4,3,5,4,0,4 +53.0,No,Travel_Rarely,238.0,Sales,1.0,1,Medical,1,682,4,Female,34,3,2,Sales Executive,1,Single,8381,7507,7,Y,No,20,4,4,80,0,18,2,4,14,7,8,10 +49.0,No,Travel_Rarely,271.0,Research & Development,,2,Medical,1,1509,3,Female,43,2,2,Laboratory Technician,1,Married,4789,23070,4,Y,No,25,4,1,80,1,10,3,3,3,2,1,2 +,Yes,Travel_Frequently,1496.0,Sales,1.0,3,Technical Degree,1,1486,1,Male,92,3,1,Sales Representative,3,Married,2909,15747,3,Y,No,15,3,4,80,1,5,3,4,3,2,1,2 +,No,Travel_Frequently,193.0,Research & Development,2.0,3,Life Sciences,1,1296,4,Male,52,2,1,Laboratory Technician,4,Married,3867,14222,1,Y,Yes,12,3,2,80,1,2,2,3,2,2,2,2 +51.0,Yes,Travel_Rarely,1323.0,Research & Development,4.0,4,Life Sciences,1,1081,1,Male,34,3,1,Research Scientist,3,Married,2461,10332,9,Y,Yes,12,3,3,80,3,18,2,4,10,0,2,7 +27.0,No,Travel_Frequently,472.0,Research & Development,1.0,1,Technical Degree,1,274,3,Male,60,2,2,Manufacturing Director,1,Married,4298,9679,5,Y,No,19,3,3,80,1,6,1,3,2,2,2,0 +,No,Travel_Rarely,1355.0,Human Resources,25.0,1,Life Sciences,1,177,3,Female,61,3,1,Human Resources,3,Married,2942,8916,1,Y,No,23,4,4,80,1,8,3,3,8,7,5,7 +44.0,No,Travel_Frequently,383.0,Sales,1.0,5,Marketing,1,1481,1,Female,79,3,2,Sales Executive,3,Married,4768,9282,7,Y,No,12,3,3,80,1,11,4,2,1,0,0,0 +,No,Travel_Rarely,464.0,Research & Development,4.0,2,Other,1,53,3,Male,75,3,1,Laboratory Technician,4,Divorced,1951,10910,1,Y,No,12,3,3,80,1,1,3,3,1,0,0,0 +27.0,No,Travel_Rarely,1377.0,Research & Development,11.0,1,Life Sciences,1,1434,2,Male,91,3,1,Laboratory Technician,1,Married,2099,7679,0,Y,No,14,3,2,80,0,6,3,4,5,0,1,4 +52.0,No,Travel_Rarely,1323.0,Research & Development,2.0,3,Life Sciences,1,316,3,Female,89,2,1,Laboratory Technician,4,Single,3212,3300,7,Y,No,15,3,2,80,0,6,3,2,2,2,2,2 +34.0,Yes,Non-Travel,1362.0,Sales,19.0,3,Marketing,1,502,1,Male,67,4,2,Sales Executive,4,Single,5304,4652,8,Y,Yes,13,3,2,80,0,9,3,2,5,2,0,4 +,Yes,Travel_Rarely,1449.0,Research & Development,16.0,4,Medical,1,394,1,Male,45,3,1,Laboratory Technician,2,Divorced,2373,14180,2,Y,Yes,13,3,4,80,1,5,2,3,3,2,0,2 +,No,Travel_Rarely,1349.0,Research & Development,23.0,3,Life Sciences,1,560,1,Female,90,3,1,Research Scientist,4,Divorced,2886,3032,1,Y,No,22,4,2,80,2,3,3,1,3,2,0,2 +40.0,No,Travel_Rarely,555.0,Research & Development,2.0,3,Medical,1,521,2,Female,78,2,2,Laboratory Technician,3,Married,3448,13436,6,Y,No,22,4,2,80,1,20,3,3,1,0,0,0 +47.0,No,Travel_Rarely,202.0,Research & Development,2.0,2,Other,1,820,3,Female,33,3,4,Manager,4,Married,16752,12982,1,Y,Yes,11,3,3,80,1,26,3,2,26,14,3,0 +,Yes,Travel_Rarely,737.0,Sales,10.0,3,Medical,1,1639,4,Male,55,2,3,Sales Executive,1,Married,10306,21530,9,Y,No,17,3,3,80,0,15,3,3,13,12,6,0 +50.0,No,Travel_Frequently,333.0,Research & Development,22.0,5,Medical,1,1539,3,Male,88,1,4,Research Director,4,Single,14411,24450,1,Y,Yes,13,3,4,80,0,32,2,3,32,6,13,9 +,No,Travel_Rarely,672.0,Research & Development,25.0,3,Technical Degree,1,899,4,Male,78,2,3,Manufacturing Director,2,Married,10903,9129,3,Y,No,16,3,1,80,0,16,2,3,13,10,4,8 +21.0,No,Travel_Rarely,546.0,Research & Development,,1,Medical,1,1623,3,Male,97,3,1,Research Scientist,4,Single,3117,26009,1,Y,No,18,3,3,80,0,3,2,3,2,2,2,2 +27.0,No,Travel_Rarely,1354.0,Research & Development,2.0,4,Technical Degree,1,1931,2,Male,41,3,1,Research Scientist,2,Married,2226,6073,1,Y,No,11,3,3,80,1,6,3,2,5,3,1,2 +48.0,No,Travel_Rarely,817.0,Sales,2.0,1,Marketing,1,712,2,Male,56,4,2,Sales Executive,2,Married,8120,18597,3,Y,No,12,3,4,80,0,12,3,3,2,2,2,2 +36.0,No,Travel_Rarely,1223.0,Research & Development,8.0,3,Technical Degree,1,83,3,Female,59,3,3,Healthcare Representative,3,Divorced,10096,8202,1,Y,No,13,3,2,80,3,17,2,3,17,14,12,8 +,Yes,Travel_Rarely,103.0,Research & Development,24.0,3,Life Sciences,1,19,3,Male,50,2,1,Laboratory Technician,3,Single,2028,12947,5,Y,Yes,14,3,2,80,0,6,4,3,4,2,0,3 +36.0,No,Travel_Rarely,311.0,Research & Development,7.0,3,Life Sciences,1,1659,1,Male,77,3,1,Laboratory Technician,2,Single,2013,10950,2,Y,No,11,3,3,80,0,15,4,3,4,3,1,3 +30.0,No,Travel_Rarely,330.0,Human Resources,1.0,3,Life Sciences,1,1499,3,Male,46,3,1,Human Resources,3,Divorced,2064,15428,0,Y,No,21,4,1,80,1,6,3,4,5,3,1,3 +48.0,No,Travel_Rarely,1236.0,Research & Development,1.0,4,Life Sciences,1,664,4,Female,40,2,4,Manager,1,Married,15402,17997,7,Y,No,11,3,1,80,1,21,3,1,3,2,0,2 +55.0,No,Travel_Rarely,1311.0,Research & Development,2.0,3,Life Sciences,1,505,3,Female,97,3,4,Manager,4,Single,16659,23258,2,Y,Yes,13,3,3,80,0,30,2,3,5,4,1,2 +55.0,No,Travel_Rarely,692.0,Research & Development,14.0,4,Medical,1,254,3,Male,61,4,5,Research Director,2,Single,18722,13339,8,Y,No,11,3,4,80,0,36,3,3,24,15,2,15 +34.0,No,Travel_Rarely,1333.0,Sales,10.0,4,Life Sciences,1,1055,3,Female,87,3,1,Sales Representative,3,Married,2220,18410,1,Y,Yes,19,3,4,80,1,1,2,3,1,1,0,0 +30.0,Yes,Travel_Frequently,334.0,Sales,26.0,4,Marketing,1,299,3,Female,52,2,2,Sales Executive,1,Single,6696,22967,5,Y,No,15,3,3,80,0,9,5,2,6,3,0,1 +,Yes,Travel_Rarely,1204.0,Sales,4.0,3,Technical Degree,1,1100,4,Male,86,3,3,Sales Executive,1,Single,9582,10333,0,Y,Yes,22,4,1,80,0,9,2,3,8,7,4,7 +54.0,No,Travel_Frequently,1050.0,Research & Development,11.0,4,Medical,1,1520,2,Female,87,3,4,Manager,4,Divorced,16032,24456,3,Y,No,20,4,1,80,1,26,2,3,14,9,1,12 +42.0,No,Non-Travel,179.0,Human Resources,2.0,5,Medical,1,1231,4,Male,79,4,2,Human Resources,1,Married,6272,12858,7,Y,No,16,3,1,80,1,10,3,4,4,3,0,3 +29.0,No,Travel_Rarely,738.0,Research & Development,9.0,5,Other,1,455,2,Male,30,2,1,Laboratory Technician,4,Single,3983,7621,0,Y,No,17,3,3,80,0,4,2,3,3,2,2,2 +47.0,No,Travel_Rarely,955.0,Sales,4.0,2,Life Sciences,1,1003,4,Female,83,3,2,Sales Executive,4,Single,4163,8571,1,Y,Yes,17,3,3,80,0,9,0,3,9,0,0,7 +42.0,No,Travel_Frequently,555.0,Sales,26.0,3,Marketing,1,404,3,Female,77,3,4,Sales Executive,2,Married,13525,14864,5,Y,No,14,3,4,80,1,23,2,4,20,4,4,8 +31.0,Yes,Travel_Rarely,202.0,Research & Development,8.0,3,Life Sciences,1,1433,1,Female,34,2,1,Research Scientist,2,Single,1261,22262,1,Y,No,12,3,3,80,0,1,3,4,1,0,0,0 +51.0,No,Travel_Rarely,942.0,Research & Development,,3,Technical Degree,1,1786,1,Female,53,3,3,Manager,3,Married,13116,22984,2,Y,No,11,3,4,80,0,15,2,3,2,2,2,2 +33.0,No,Travel_Rarely,922.0,Research & Development,1.0,5,Medical,1,612,1,Female,95,4,4,Research Director,3,Divorced,16184,22578,4,Y,No,19,3,3,80,1,10,2,3,6,1,0,5 +39.0,No,Travel_Rarely,,Research & Development,6.0,1,Medical,1,2062,4,Male,42,2,3,Healthcare Representative,1,Married,9991,21457,4,Y,No,15,3,1,80,1,9,5,3,7,7,1,7 +21.0,No,Travel_Rarely,984.0,Research & Development,1.0,1,Technical Degree,1,1131,4,Female,70,2,1,Research Scientist,2,Single,2070,25326,1,Y,Yes,11,3,3,80,0,2,6,4,2,2,2,2 +36.0,No,Travel_Rarely,1403.0,Research & Development,6.0,3,Life Sciences,1,373,4,Male,47,3,1,Laboratory Technician,4,Married,3210,20251,0,Y,No,11,3,3,80,1,16,4,3,15,13,10,11 +43.0,No,Travel_Rarely,930.0,Research & Development,6.0,3,Medical,1,1402,1,Female,73,2,2,Research Scientist,3,Single,4081,20003,1,Y,Yes,14,3,1,80,0,20,3,1,20,7,1,8 +49.0,No,Non-Travel,1002.0,Research & Development,18.0,4,Life Sciences,1,275,4,Male,92,3,2,Manufacturing Director,4,Divorced,6804,23793,1,Y,Yes,15,3,1,80,2,7,0,3,7,7,1,7 +27.0,No,Non-Travel,691.0,Research & Development,9.0,3,Medical,1,218,4,Male,57,3,1,Research Scientist,2,Divorced,2024,5970,6,Y,No,18,3,4,80,1,6,1,1,2,2,2,2 +,No,Travel_Rarely,583.0,Research & Development,25.0,4,Medical,1,1014,3,Female,57,3,3,Healthcare Representative,3,Divorced,10388,6975,1,Y,Yes,11,3,3,80,1,16,3,2,16,10,10,1 +56.0,No,Travel_Frequently,,Sales,6.0,3,Life Sciences,1,532,3,Female,86,4,4,Sales Executive,1,Married,13212,18256,9,Y,No,11,3,4,80,3,36,0,2,7,7,7,7 +30.0,No,Travel_Rarely,231.0,Sales,8.0,2,Other,1,982,3,Male,62,3,3,Sales Executive,3,Divorced,7264,9977,5,Y,No,11,3,1,80,1,10,2,4,8,4,7,7 +42.0,No,Travel_Rarely,1059.0,Research & Development,9.0,2,Other,1,1595,4,Male,93,2,5,Manager,4,Single,19613,26362,8,Y,No,22,4,4,80,0,24,2,3,1,0,0,1 +23.0,No,Travel_Rarely,310.0,Research & Development,10.0,1,Medical,1,784,1,Male,79,4,1,Research Scientist,3,Single,3505,19630,1,Y,No,18,3,4,80,0,2,3,3,2,2,0,2 +,Yes,Travel_Rarely,383.0,Sales,9.0,2,Life Sciences,1,1439,1,Male,68,2,1,Sales Representative,1,Married,4400,15182,3,Y,No,12,3,1,80,0,6,2,3,3,2,2,2 +24.0,No,Travel_Rarely,1476.0,Sales,4.0,1,Medical,1,1445,4,Female,42,3,2,Sales Executive,3,Married,4162,15211,1,Y,Yes,12,3,3,80,2,5,3,3,5,4,0,3 +29.0,No,Travel_Rarely,598.0,Research & Development,9.0,3,Life Sciences,1,1558,3,Male,91,4,1,Research Scientist,3,Married,2451,22376,6,Y,No,18,3,1,80,2,5,2,2,1,0,0,0 +29.0,Yes,Travel_Rarely,121.0,Sales,27.0,3,Marketing,1,283,2,Female,35,3,3,Sales Executive,4,Married,7639,24525,1,Y,No,22,4,4,80,3,10,3,2,10,4,1,9 +24.0,Yes,Travel_Rarely,813.0,Research & Development,1.0,3,Medical,1,45,2,Male,61,3,1,Research Scientist,4,Married,2293,3020,2,Y,Yes,16,3,1,80,1,6,2,2,2,0,2,0 +43.0,No,Travel_Rarely,415.0,Sales,25.0,3,Medical,1,1076,3,Male,79,2,3,Sales Executive,4,Divorced,10798,5268,5,Y,No,13,3,3,80,1,18,5,3,1,0,0,0 +,No,Travel_Rarely,1017.0,Research & Development,6.0,4,Life Sciences,1,691,2,Male,82,1,2,Research Scientist,4,Single,6646,19368,1,Y,No,13,3,2,80,0,17,3,3,17,11,11,8 +34.0,No,Travel_Rarely,704.0,Sales,28.0,3,Marketing,1,2035,4,Female,95,2,2,Sales Executive,3,Married,6712,8978,1,Y,No,21,4,4,80,2,8,2,3,8,7,1,7 +,Yes,Travel_Rarely,1404.0,Research & Development,17.0,3,Technical Degree,1,1960,3,Male,32,2,1,Laboratory Technician,4,Divorced,2367,18779,5,Y,No,12,3,1,80,1,6,2,2,4,1,0,3 +51.0,No,Travel_Rarely,632.0,Sales,21.0,4,Marketing,1,120,3,Male,71,3,2,Sales Executive,4,Single,5441,8423,0,Y,Yes,22,4,4,80,0,11,2,1,10,7,1,0 +33.0,No,Travel_Rarely,217.0,Sales,10.0,4,Marketing,1,1924,2,Male,43,3,2,Sales Executive,3,Single,5487,10410,1,Y,No,14,3,2,80,0,10,2,2,10,4,0,9 +59.0,No,Travel_Rarely,326.0,Sales,,3,Life Sciences,1,1254,3,Female,48,2,2,Sales Executive,4,Single,5171,16490,5,Y,No,17,3,4,80,0,13,2,3,6,1,0,5 +45.0,No,Travel_Rarely,954.0,Sales,2.0,2,Technical Degree,1,783,2,Male,46,1,2,Sales Representative,3,Single,6632,12388,0,Y,No,13,3,1,80,0,9,3,3,8,7,3,1 +,Yes,Travel_Rarely,1475.0,Sales,13.0,2,Marketing,1,1933,4,Female,84,3,2,Sales Executive,3,Single,9854,23352,3,Y,Yes,11,3,4,80,0,6,0,3,2,0,2,2 +20.0,Yes,Travel_Frequently,769.0,Sales,9.0,3,Marketing,1,1077,4,Female,54,3,1,Sales Representative,4,Single,2323,17205,1,Y,Yes,14,3,2,80,0,2,3,3,2,2,0,2 +32.0,No,Non-Travel,976.0,Sales,26.0,4,Marketing,1,333,3,Male,100,3,2,Sales Executive,4,Married,4465,12069,0,Y,No,18,3,1,80,0,4,2,3,3,2,2,2 +34.0,No,Travel_Rarely,1346.0,Research & Development,19.0,2,Medical,1,18,2,Male,93,3,1,Laboratory Technician,4,Divorced,2661,8758,0,Y,No,11,3,3,80,1,3,2,3,2,2,1,2 +43.0,No,Travel_Frequently,185.0,Research & Development,10.0,4,Life Sciences,1,430,3,Female,33,3,1,Laboratory Technician,4,Single,2455,10675,0,Y,No,19,3,1,80,0,9,5,3,8,7,1,7 +32.0,No,Travel_Rarely,859.0,Research & Development,4.0,3,Life Sciences,1,830,3,Female,98,2,2,Manufacturing Director,3,Married,6162,19124,1,Y,No,12,3,3,80,1,14,3,3,14,13,6,8 +40.0,No,Travel_Rarely,759.0,Sales,2.0,2,Marketing,1,516,4,Female,46,3,2,Sales Executive,2,Divorced,5715,22553,7,Y,No,12,3,3,80,2,8,5,3,5,4,1,3 +,Yes,Travel_Rarely,920.0,Human Resources,20.0,2,Medical,1,1818,4,Female,69,3,1,Human Resources,2,Married,2148,6889,0,Y,Yes,11,3,3,80,0,6,3,3,5,1,1,4 +41.0,No,Travel_Rarely,465.0,Research & Development,14.0,3,Life Sciences,1,227,1,Male,56,3,1,Research Scientist,3,Divorced,2451,4609,4,Y,No,12,3,1,80,1,13,2,3,9,8,1,8 +,No,Travel_Rarely,982.0,Research & Development,1.0,4,Medical,1,1172,4,Male,58,2,1,Laboratory Technician,3,Married,2258,16340,6,Y,No,12,3,2,80,1,10,2,3,8,0,1,7 +24.0,No,Non-Travel,673.0,Research & Development,11.0,2,Other,1,26,1,Female,96,4,2,Manufacturing Director,3,Divorced,4011,8232,0,Y,No,18,3,4,80,1,5,5,2,4,2,1,3 +53.0,No,Travel_Rarely,868.0,Sales,8.0,3,Marketing,1,897,1,Male,73,3,4,Sales Executive,4,Married,11836,22789,5,Y,No,14,3,3,80,1,28,3,3,2,0,2,2 +47.0,No,Travel_Rarely,1176.0,Human Resources,26.0,4,Life Sciences,1,1625,4,Female,98,3,5,Manager,3,Married,19658,5220,3,Y,No,11,3,3,80,1,27,2,3,5,2,1,0 +31.0,Yes,Travel_Frequently,874.0,Research & Development,15.0,3,Medical,1,1160,3,Male,72,3,1,Laboratory Technician,3,Married,2610,6233,1,Y,No,12,3,3,80,1,2,5,2,2,2,2,2 +34.0,No,Non-Travel,1375.0,Sales,10.0,3,Life Sciences,1,1774,4,Male,87,3,2,Sales Executive,3,Divorced,4001,12313,1,Y,Yes,14,3,3,80,1,15,3,3,15,14,0,7 +33.0,Yes,Travel_Rarely,527.0,Research & Development,1.0,4,Other,1,780,4,Male,63,3,1,Research Scientist,4,Single,2686,5207,1,Y,Yes,13,3,3,80,0,10,2,2,10,9,7,8 +32.0,No,Travel_Rarely,801.0,Sales,1.0,4,Marketing,1,2016,3,Female,48,3,3,Sales Executive,4,Married,10422,24032,1,Y,No,19,3,3,80,2,14,3,3,14,10,5,7 +41.0,No,Travel_Rarely,263.0,Research & Development,6.0,3,Medical,1,957,4,Male,59,3,1,Laboratory Technician,1,Single,4721,3119,2,Y,Yes,13,3,3,80,0,20,3,3,18,13,2,17 +40.0,No,Non-Travel,458.0,Research & Development,16.0,2,Life Sciences,1,1340,3,Male,74,3,1,Research Scientist,3,Divorced,3544,8532,9,Y,No,16,3,2,80,1,6,0,3,4,2,0,0 +51.0,No,Travel_Rarely,313.0,Research & Development,,3,Medical,1,258,4,Female,98,3,4,Healthcare Representative,2,Single,13734,7192,3,Y,No,18,3,3,80,0,21,6,3,7,7,1,0 +55.0,Yes,Travel_Rarely,267.0,Sales,13.0,4,Marketing,1,1372,1,Male,85,4,4,Sales Executive,3,Single,13695,9277,6,Y,Yes,17,3,3,80,0,24,2,2,19,7,3,8 +52.0,No,Travel_Rarely,1053.0,Research & Development,1.0,2,Life Sciences,1,976,4,Male,70,3,4,Manager,4,Married,17099,13829,2,Y,No,15,3,2,80,1,26,2,2,9,8,7,8 +54.0,No,Travel_Rarely,397.0,Human Resources,19.0,4,Medical,1,698,3,Male,88,3,3,Human Resources,2,Married,10725,6729,2,Y,No,15,3,3,80,1,16,1,4,9,7,7,1 +23.0,No,Travel_Rarely,507.0,Research & Development,20.0,1,Life Sciences,1,1533,1,Male,97,3,2,Laboratory Technician,3,Single,2272,24812,0,Y,No,14,3,2,80,0,5,2,3,4,3,1,2 +24.0,No,Travel_Rarely,691.0,Research & Development,23.0,3,Medical,1,639,2,Male,89,4,1,Research Scientist,4,Married,2725,21630,1,Y,Yes,11,3,2,80,2,6,3,3,6,5,1,4 +20.0,No,Travel_Rarely,805.0,Research & Development,,3,Life Sciences,1,1198,1,Male,87,2,1,Laboratory Technician,3,Single,3033,12828,1,Y,No,12,3,1,80,0,2,2,2,2,2,1,2 +38.0,No,Travel_Rarely,1035.0,Sales,,4,Life Sciences,1,1036,2,Male,42,3,2,Sales Executive,4,Single,6861,4981,8,Y,Yes,12,3,3,80,0,19,1,3,1,0,0,0 +29.0,No,Travel_Rarely,665.0,Research & Development,15.0,3,Life Sciences,1,346,3,Male,60,3,1,Research Scientist,4,Single,2340,22673,1,Y,No,19,3,1,80,0,6,1,3,6,5,1,5 +36.0,Yes,Travel_Rarely,1218.0,Sales,9.0,4,Life Sciences,1,27,3,Male,82,2,1,Sales Representative,1,Single,3407,6986,7,Y,No,23,4,2,80,0,10,4,3,5,3,0,3 +,No,Travel_Rarely,1172.0,Sales,,3,Medical,1,1875,2,Female,78,3,1,Sales Representative,2,Married,2856,3692,1,Y,No,19,3,4,80,1,1,3,3,1,0,0,0 +41.0,No,Non-Travel,509.0,Research & Development,2.0,4,Other,1,616,1,Female,62,2,2,Healthcare Representative,3,Single,6811,2112,2,Y,Yes,17,3,1,80,0,10,3,3,8,7,0,7 +54.0,No,Travel_Rarely,584.0,Research & Development,22.0,5,Medical,1,1665,2,Female,91,3,4,Manager,3,Married,17426,18685,3,Y,No,25,4,3,80,1,36,6,3,10,8,4,7 +,No,Travel_Rarely,1315.0,Research & Development,22.0,3,Life Sciences,1,381,2,Female,71,4,3,Manager,2,Divorced,11996,19100,7,Y,No,18,3,2,80,1,10,6,2,7,7,6,2 +55.0,No,Travel_Rarely,282.0,Research & Development,2.0,2,Medical,1,1336,4,Female,58,1,5,Manager,3,Married,19187,6992,4,Y,No,14,3,4,80,1,23,5,3,19,9,9,11 +,No,Travel_Frequently,146.0,Research & Development,2.0,4,Medical,1,1704,1,Male,79,2,1,Research Scientist,4,Single,4930,13970,0,Y,Yes,14,3,3,80,0,6,2,4,5,4,1,4 +30.0,Yes,Travel_Frequently,464.0,Research & Development,4.0,3,Technical Degree,1,514,3,Male,40,3,1,Research Scientist,4,Single,2285,3427,9,Y,Yes,23,4,3,80,0,3,4,3,1,0,0,0 +45.0,No,Non-Travel,1050.0,Sales,9.0,4,Life Sciences,1,1117,2,Female,65,2,2,Sales Executive,3,Married,5593,17970,1,Y,No,13,3,4,80,1,15,2,3,15,10,4,12 +39.0,No,Non-Travel,105.0,Research & Development,9.0,3,Life Sciences,1,2022,4,Male,87,3,5,Manager,4,Single,19431,15302,2,Y,No,13,3,3,80,0,21,3,2,6,0,1,3 +29.0,No,Travel_Rarely,144.0,Sales,10.0,1,Marketing,1,463,4,Female,39,2,2,Sales Executive,2,Divorced,8268,11866,1,Y,Yes,14,3,1,80,2,7,2,3,7,7,1,7 +,No,Travel_Frequently,921.0,Research & Development,1.0,1,Medical,1,1068,1,Female,66,2,1,Research Scientist,3,Divorced,2007,25265,1,Y,No,13,3,3,80,2,5,5,3,5,3,1,3 +29.0,Yes,Travel_Frequently,459.0,Research & Development,24.0,2,Life Sciences,1,1868,4,Male,73,2,1,Research Scientist,4,Single,2439,14753,1,Y,Yes,24,4,2,80,0,1,3,2,1,0,1,0 +43.0,No,Travel_Frequently,957.0,Research & Development,28.0,3,Medical,1,171,2,Female,72,4,1,Research Scientist,3,Single,4739,16090,4,Y,No,12,3,4,80,0,18,2,3,3,2,1,2 +24.0,Yes,Travel_Rarely,984.0,Research & Development,17.0,2,Life Sciences,1,1219,4,Female,97,3,1,Laboratory Technician,2,Married,2210,3372,1,Y,No,13,3,1,80,1,1,3,1,1,0,0,0 +,No,Travel_Rarely,670.0,Research & Development,10.0,4,Medical,1,1587,1,Female,51,3,2,Healthcare Representative,3,Single,6142,4223,3,Y,Yes,16,3,3,80,0,10,4,3,5,2,0,4 +53.0,Yes,Travel_Rarely,1168.0,Sales,24.0,4,Life Sciences,1,1968,1,Male,66,3,3,Sales Executive,1,Single,10448,5843,6,Y,Yes,13,3,2,80,0,15,2,2,2,2,2,2 +51.0,No,Travel_Rarely,432.0,Research & Development,9.0,4,Life Sciences,1,116,4,Male,96,3,1,Laboratory Technician,4,Married,2075,18725,3,Y,No,23,4,2,80,2,10,4,3,4,2,0,3 +43.0,No,Travel_Frequently,559.0,Research & Development,10.0,4,Life Sciences,1,448,3,Female,82,2,2,Laboratory Technician,3,Divorced,5257,6227,1,Y,No,11,3,2,80,1,9,3,4,9,7,0,0 +23.0,No,Travel_Rarely,160.0,Research & Development,4.0,1,Medical,1,1735,3,Female,51,3,1,Laboratory Technician,2,Single,3295,12862,1,Y,No,13,3,3,80,0,3,3,1,3,2,1,2 +41.0,No,Travel_Rarely,1276.0,Sales,2.0,5,Life Sciences,1,625,2,Female,91,3,4,Manager,1,Married,16595,5626,7,Y,No,16,3,2,80,1,22,2,3,18,16,11,8 +33.0,No,Non-Travel,750.0,Sales,22.0,2,Marketing,1,160,3,Male,95,3,2,Sales Executive,2,Married,6146,15480,0,Y,No,13,3,1,80,1,8,2,4,7,7,0,7 +49.0,No,Travel_Rarely,1495.0,Research & Development,,4,Technical Degree,1,1473,1,Male,96,3,2,Healthcare Representative,3,Married,6651,21534,2,Y,No,14,3,2,80,1,20,0,2,3,2,1,2 +33.0,No,Travel_Rarely,589.0,Research & Development,28.0,4,Life Sciences,1,1549,2,Male,79,3,2,Laboratory Technician,3,Married,5207,22949,1,Y,Yes,12,3,2,80,1,15,3,3,15,14,5,7 +,No,Travel_Rarely,750.0,Research & Development,28.0,3,Life Sciences,1,1596,2,Male,46,4,2,Laboratory Technician,3,Married,3407,25348,1,Y,No,17,3,4,80,2,10,3,2,10,9,6,8 +41.0,No,Travel_Rarely,447.0,Research & Development,,3,Life Sciences,1,1814,2,Male,85,4,2,Healthcare Representative,2,Single,6870,15530,3,Y,No,12,3,1,80,0,11,3,1,3,2,1,2 +22.0,Yes,Travel_Frequently,1256.0,Research & Development,,4,Life Sciences,1,1203,3,Male,48,2,1,Research Scientist,4,Married,2853,4223,0,Y,Yes,11,3,2,80,1,1,5,3,0,0,0,0 +29.0,No,Travel_Rarely,1378.0,Research & Development,13.0,2,Other,1,2053,4,Male,46,2,2,Laboratory Technician,2,Married,4025,23679,4,Y,Yes,13,3,1,80,1,10,2,3,4,3,0,3 +50.0,No,Travel_Rarely,264.0,Sales,9.0,3,Marketing,1,1591,3,Male,59,3,5,Manager,3,Married,19331,19519,4,Y,Yes,16,3,3,80,1,27,2,3,1,0,0,0 diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..62af2b87cfa0ef00e6d04f9225a0c9fb27e5dc56 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,13 @@ +Flask==3.0.0 +Flask_Bootstrap==3.3.7.1 +langchain==0.0.281 +openai==0.27.8 +pandas==1.3.5 +plotly==5.14.1 +pyodbc==4.0.32 +python-dotenv==0.21.1 +Requests==2.31.0 +SQLAlchemy==1.4.42 +urllib3==1.26.14 +waitress==2.1.2 +tabulate==0.9.0 diff --git a/static/css/chat_style.css b/static/css/chat_style.css new file mode 100644 index 0000000000000000000000000000000000000000..fa963b201f225b1630982aaeff1ee8d01102ef43 --- /dev/null +++ b/static/css/chat_style.css @@ -0,0 +1,191 @@ +.sidechatpanel { + width: 400px; + position: fixed; + top: 56px; + opacity: 0.98; + z-index: 3; + right: -400px; + padding-bottom: 60px; + height: calc(100vh - 55px); + background-color: #2e2e2e; + transition: right 0.3s ease-in-out; + overflow: hidden; + display: flex; + flex-direction: column; + scroll-behavior: auto; + box-shadow: -5px 4px 8px 0 rgba(0, 0, 0, 0.2); +} + +.sidechatpanel.show { + right: 0; +} + +.msger-header { + background-color: revert; + color: cornsilk; + text-align: center; + margin-top: -5px; + padding: 12px 5px 5px 20px; + /* font-weight: bolder; */ + border-radius: 15px; + box-shadow: 0px 4px 4px 0 rgba(22, 0, 0, 0.2); + font-style: oblique; + padding-top: -5px; +} + +.msger-send-btn { + background-color: transparent; + border: none; + padding: 10px; + width: 24px; + height: 24px; + background-image: url('/static/images/send5.png'); + background-size: cover; + background-repeat: no-repeat; +} + +.msger-inputarea { + position: absolute; + bottom: 0; + left: 0; + width: 100%; + padding: 6px; + background-color: #000000; +} + +.msger-input { + display: flex; + align-items: center; + border: 1px solid #ccc; + border-radius: 5px; + background-color: #cdcdca; + overflow: hidden; +} + +.msger-input input { + flex: 1; + padding: 10px; + border: none; + background-color: transparent; + width: 100%; +} + +.msger-input button { + border: none; + margin: 0; + padding: 0; +} + + +.chat-container { + padding-left: 15px; + padding-right: 15px; + padding-top: 10px; + display: flex; + flex-direction: column; + max-height: calc(100vh - 110px); + max-width: auto; + margin: 10 auto; + scroll-behavior: auto; + overflow-y: auto; +} + +.chat-container::-webkit-scrollbar { + width: 5px; +} + +.chat-container::-webkit-scrollbar-thumb { + background-color: #888; + border-radius: 5px; +} + +/* Hide the scrollbar track */ +.chat-container::-webkit-scrollbar-track { + display: none; +} + +.user-message { + display: flex; + font-size: 500; + margin-bottom: 10px; + color: gold; + border-radius: 5px; +} + +.bot-message { + display: flex; + color: rgb(209, 243, 244); + margin-bottom: 10px; +} + +.user-icon { + margin-top: 8px; + justify-content: center; + width: 24px; + height: 24px; + color: white; + text-align: center; + line-height: 40px; + background-image: url('/static/images/user6.png'); + background-size: cover; + margin-right: 10px; +} + +.bot-icon { + margin-top: 8px; + justify-content: center; + width: 24px; + height: 24px; + color: white; + text-align: center; + line-height: 40px; + background-image: url('/static/images/bot.png'); + background-size: cover; + margin-right: 10px; +} + +.bot-message-bubble { + flex: 1; + font-size: small; + font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; + background-color: transparent; + padding: 10px; + border-radius: 10px; + box-shadow: #1f2b37; + box-shadow: -4px 4px 8px 0 rgba(0, 0, 0, 0.2); +} + +.user-message-bubble { + flex: 1; + font-size: small; + font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; + background-color: transparent; + padding: 10px; + border-radius: 10px; + box-shadow: #1f2b37; + box-shadow: -4px 4px 8px rgba(0, 0, 0, 0.2); +} + +.closebtn { + cursor: pointer; + color: darkgrey; + font-size: 20px; + font-weight: bold; +} + +.closebtn:hover { + color: coral; +} + +.toggle-button { + position: fixed; + top: 65px; + height: 37px; + right: -10px; + background-color: #8fadc7; + color: white; + /* padding: 10px 10px; */ + border: none; + border-radius: 10px; + cursor: pointer; +} \ No newline at end of file diff --git a/static/css/data_style.css b/static/css/data_style.css new file mode 100644 index 0000000000000000000000000000000000000000..3523c5d1fc07365eadb3acece8497fbcc04d65a1 --- /dev/null +++ b/static/css/data_style.css @@ -0,0 +1,72 @@ +.tab { + position: relative; + overflow: hidden; + background-color: #f1f1f1; +} + +.tab button { + background-color: inherit; + font-weight: bolder; + color:darkslategray; + float: left; + border: none; + outline: none; + cursor: pointer; + padding: 14px 12px; + transition: background-color 0.3s ease; +} + +.tab button:hover { + background-color: #ddd; +} + +.tab button.active { + background-color: #ccc; +} + +div.dataTables_wrapper { + margin: 0 auto; +} + +.page-item.active .page-link { + z-index: 1; + color: #fff; + background-color: #84888d; + border-color: #929ba4; +} + +.fixed-button { + position: fixed; + bottom: 0; + left: 0; + width: 100%; + /* margin-top: 50px; */ + padding: 15px; + padding-right: 50px; + background-color: #f8f9fa; + box-shadow: 0 -2px 6px rgba(0, 0, 0, 0.1); + z-index: 2; +} + +/* Define your custom button color */ +.btn-custom-color { + background-color: rgb(17, 67, 86); /* Replace 'specific-color' with your desired color */ + color: rgb(168, 167, 167); /* Set text color to white to ensure readability on colored backgrounds */ + border-color: rgb(17, 67, 86); /* Set border color to match the background color */ +} + +/* If you want to change the color of the button on hover and active states as well */ +.btn-custom-color:hover, +.btn-custom-color:active, +.btn-custom-color:focus { + background-color: rgb(17, 67, 86); /* Replace 'specific-hover-color' with the desired hover color */ + color: rgb(209, 212, 214); + border-color: rgb(38, 144, 185); +} + +.content { + padding-left: 0px; + padding-right: 0px; +} + + diff --git a/static/css/home_style.css b/static/css/home_style.css new file mode 100644 index 0000000000000000000000000000000000000000..66de749ba3f15ff57507f6c8d30386825eaeb640 --- /dev/null +++ b/static/css/home_style.css @@ -0,0 +1,32 @@ +/* body { + font-family: Arial, sans-serif; +} */ +.container { + max-width: 1100px; + margin: 0 auto; + padding: 0 auto; +} + +.row { + margin-bottom: 20px; +} + +.left-column { + background-color: #f8f9fa; + padding: 20px; + position: relative; +} + +.right-column { + padding: 20px; +} + +h1 { + text-align: center; + margin-bottom: 30px; +} + +form { + margin-bottom: 20px; +} + diff --git a/static/css/layout_style.css b/static/css/layout_style.css new file mode 100644 index 0000000000000000000000000000000000000000..5a207000df5d9ee512ac0ded936dc995dfaa8ec4 --- /dev/null +++ b/static/css/layout_style.css @@ -0,0 +1,50 @@ +/* .navbar { + background-color: black; +} */ + +/* .navbar-toggler { + border-color: rgba(255, 255, 255, 0.5); +} + +.navbar-toggler-icon { + background-image: url("data:image/svg+xml,%3Csvg viewBox='0 0 30 30' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath stroke='rgba(255, 255, 255, 0.5)' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3E%3C/svg%3E"); +} + +*/ + +/* .navbar-toggler { + border-color: rgba(255, 18, 18, 0.5); +} */ + +/* .navbar-nav .nav-link { + padding: 0.5rem 0.75rem; + margin-left: 10px; + color: rgb(221, 234, 239); +} */ + +/* .navbar-nav .nav-link:hover { + color: rgb(234, 128, 41); +} */ + +/* .navbar-nav .nav-link.active { + font-weight: bold; +} */ +/* +.navbar-nav .nav-link.active { + font-weight: bold !important; + color: rgb(235, 80, 13) !important; + background-color: red; + } */ + +/* .navbar-brand { + padding-left: 100px; +} */ + +#navbarNav { + padding-right: 110px; +} + +.disabled { + pointer-events: none; /* Disable click events */ + opacity: 0.6; /* Visually indicate disabled state */ +} \ No newline at end of file diff --git a/static/css/validate_style.css b/static/css/validate_style.css new file mode 100644 index 0000000000000000000000000000000000000000..8acb0a4a5eac830eafdd0751a3a070239b3a2b71 --- /dev/null +++ b/static/css/validate_style.css @@ -0,0 +1,78 @@ +.tab { + position: relative; + overflow: hidden; + background-color: #f1f1f1; +} + +.tab button { + background-color: inherit; + float: left; + border: none; + outline: none; + cursor: pointer; + padding: 14px 16px; + transition: background-color 0.3s ease; +} + +.tab button:hover { + background-color: #ddd; +} + +.tab button.active { + background-color: #ccc; +} + +body { + background-color: #f0f0f0; + } + + .left_tblsidebar { + background-color:cadetblue; + height: 100vh; + position: fixed; + top: 0; + left: 0px; + width: 100px; + display: flex; + flex-direction: column; + align-items: center; + padding-top: 80px; + z-index:0; + } + + /* .nav-link { */ + .val_leftsidebarcls { + color: #fff; + display: flex; + flex-direction: column; + align-items: center; + text-decoration:none; + padding-top: 10px; + padding-bottom: 10px; + } + + /* .nav-link span { */ + .val_leftsidebarcls span{ + display: block; + width: 0; + text-align: center; + overflow: hidden; + white-space: nowrap; + } + + /* .nav-link:hover span{ */ + .val_leftsidebarcls:hover span{ + display: block; + width:fit-content; + } + + .dashboard-content{ + margin-left: 20px; + } + + div.headstats{ + text-align: center; + margin-left: 10px; + margin-right: 10px; + /* background-color: floralwhite; */ + } \ No newline at end of file diff --git a/static/images/aichat.png b/static/images/aichat.png new file mode 100644 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(i = 0; i < tabcontent.length; i++) { + tabcontent[i].style.display = "none"; + } + + // Remove "active" class from all buttons + tablinks = document.getElementsByClassName("tablinks"); + for (i = 0; i < tablinks.length; i++) { + tablinks[i].className = tablinks[i].className.replace(" active", ""); + } + + // Show the selected content and mark the button as active + document.getElementById(tabName).style.display = "block"; + evt.currentTarget.className += " active"; + }; + +function redirecttovalidation() { + window.location.href = '/validate_' + req_tables; +} + +// chat function which loads user message and gets bot response by invoking the URI +document.addEventListener("DOMContentLoaded", function () { + const msgerForm = document.querySelector(".msger-inputarea"); + const msgerInput = document.querySelector("#textInput"); + const msgerChat = document.querySelector(".chat-container"); + + msgerForm.addEventListener("submit", function (event) { + event.preventDefault(); + const msgText = msgerInput.value; + if (!msgText) return; + + appendMessage(msgText); + msgerInput.value = ""; + botResponse(msgText); + }); + + function appendMessage(text) { + const msgHTML = ` +
+
+
+ ${text} +
+
+ `; + msgerChat.insertAdjacentHTML("beforeend", msgHTML); + msgerChat.scrollTop += 500; + } + + function botResponse(rawText) { + const selectElement = document.getElementById("table-dropdown"); + const desiredValue = document.getElementById("table-dropdown").value; + let selected_tbl_name = ''; + for (let i = 0; i < selectElement.options.length; i++) { + const option = selectElement.options[i]; + if (option.value === desiredValue) { + // Found a match, get the innerHTML + selected_tbl_name = option.innerHTML.toLowerCase(); + break; // Exit the loop since we found a match + } + } + + + $.get("/get_llmresponse", { msg: rawText, table_selected: selected_tbl_name }).done(function (data) { + console.log(rawText); + console.log(data); + const msgHTML = ` +
+
+
+ ${data} +
+
+ `; + msgerChat.insertAdjacentHTML("beforeend", msgHTML); + msgerChat.scrollTop += 500; + }); + } +}); diff --git a/static/js/home_script.js b/static/js/home_script.js new file mode 100644 index 0000000000000000000000000000000000000000..5204e15e90ead433fa8287557a8f27d87ce2e86f --- /dev/null +++ b/static/js/home_script.js @@ -0,0 +1,47 @@ +$(function() { + var start = moment().subtract(29, 'days'); + var end = moment(); + function cb(start, end) { + $('#reportrange span').html(start.format('MMM D, YYYY') + ' - ' + end.format('MMM D, YYYY')); + $('input[name="calendar_value"]').val(start.format('YYYY-MM-DD') + ':' + end.format('YYYY-MM-DD')); + } + // Set the value for the calendar_value input field + $('#reportrange').daterangepicker({ + startDate: start, + endDate: end, + ranges: { + // 'Today': [moment(), moment()], + // 'Yesterday': [moment().subtract(1, 'days'), moment().subtract(1, 'days')], + 'Last 7 Days': [moment().subtract(6, 'days'), moment()], + 'Last 30 Days': [moment().subtract(29, 'days'), moment()], + 'This Month': [moment().startOf('month'), moment().endOf('month')], + 'Last Month': [moment().subtract(1, 'month').startOf('month'), moment().subtract(1, 'month').endOf('month')], + 'This Quarter': [moment().startOf('quarter'), moment().endOf('quarter')], + 'Last Quarter': [moment().subtract(1, 'quarter').startOf('quarter'), moment().subtract(1, 'quarter').endOf('quarter')] + } + }, cb); + cb(start, end); +}); + +function toggleFormElements() { + var toggleSwitch = document.getElementById('toggleSwitch'); + var dropdowns = document.querySelectorAll('form select'); + var textbox = document.querySelector('form textarea'); + var submitButton = document.querySelector('form button[type="submit"]'); + + if (toggleSwitch.checked) { + for (var i = 0; i < dropdowns.length; i++) { + dropdowns[i].disabled = true; + } + //reportrange.disabled = true; + textbox.disabled = false; + submitButton.disabled = false; + } else { + for (var i = 0; i < dropdowns.length; i++) { + dropdowns[i].disabled = false; + } + //reportrange.disabled = false; + textbox.disabled = true; + submitButton.disabled = false; + } +}; \ No newline at end of file diff --git a/static/js/mytest.js b/static/js/mytest.js new file mode 100644 index 0000000000000000000000000000000000000000..a4ecda15ed7d13c938851c1388775fb3d50fb286 --- /dev/null +++ b/static/js/mytest.js @@ -0,0 +1,79 @@ +function openTab(evt, tabName) { + var i, tabcontent, tablinks; + + // Hide all content + tabcontent = document.getElementsByClassName("content"); + for (i = 0; i < tabcontent.length; i++) { + tabcontent[i].style.display = "none"; + } + + // Remove "active" class from all buttons + tablinks = document.getElementsByClassName("tablinks"); + for (i = 0; i < tablinks.length; i++) { + tablinks[i].className = tablinks[i].className.replace(" active", ""); + } + + // Show the selected content and mark the button as active + document.getElementById(tabName).style.display = "block"; + evt.currentTarget.className += " active"; + }; + +// document.getElementById('slssl').value = "option8";; + +$(function() { + var start = moment().subtract(29, 'days'); + var end = moment(); + function cb(start, end) { + $('#reportrange span').html(start.format('MMM D, YYYY') + ' - ' + end.format('MMM D, YYYY')); + $('input[name="calendar_value"]').val(start.format('YYYY-MM-DD') + ':' + end.format('YYYY-MM-DD')); + } + // Set the value for the calendar_value input field + $('#reportrange').daterangepicker({ + startDate: start, + endDate: end, + ranges: { + // 'Today': [moment(), moment()], + // 'Yesterday': [moment().subtract(1, 'days'), moment().subtract(1, 'days')], + 'Last 7 Days': [moment().subtract(6, 'days'), moment()], + 'Last 30 Days': [moment().subtract(29, 'days'), moment()], + 'This Month': [moment().startOf('month'), moment().endOf('month')], + 'Last Month': [moment().subtract(1, 'month').startOf('month'), moment().subtract(1, 'month').endOf('month')], + 'This Quarter': [moment().startOf('quarter'), moment().endOf('quarter')], + 'Last Quarter': [moment().subtract(1, 'quarter').startOf('quarter'), moment().subtract(1, 'quarter').endOf('quarter')] + } + }, cb); + cb(start, end); +}); + +function downloadTableData() { + window.location.href = "/downloaddata"; + }; + +function toggleFormElements() { + var toggleSwitch = document.getElementById('toggleSwitch'); + var dropdowns = document.querySelectorAll('form select'); + var textbox = document.querySelector('form textarea'); + var submitButton = document.querySelector('form button[type="submit"]'); + + if (toggleSwitch.checked) { + for (var i = 0; i < dropdowns.length; i++) { + dropdowns[i].disabled = true; + } + //reportrange.disabled = true; + textbox.disabled = false; + submitButton.disabled = false; + } else { + for (var i = 0; i < dropdowns.length; i++) { + dropdowns[i].disabled = false; + } + //reportrange.disabled = false; + textbox.disabled = true; + submitButton.disabled = false; + } +}; + +function redirecttovalidation() { + window.location.href = '/validation'; +} + +document.getElementById("tab1").click(); diff --git a/static/js/validate_script.js b/static/js/validate_script.js new file mode 100644 index 0000000000000000000000000000000000000000..37ec65f0d520e2576824a087ea07de78b30d6230 --- /dev/null +++ b/static/js/validate_script.js @@ -0,0 +1,723 @@ +// Chart js | script to populate stacked horizontal bar chart for validation results +document.addEventListener('DOMContentLoaded', function() { + var labels = []; + var pct_pattern_mismatch = []; + var pct_null_values = []; + var pct_good_data = []; + var pct_column_notfound = []; + var pct_dtype_issue = []; + var pct_neg_values = []; + var pct_value_notdatetime = []; + var pct_value_unknown = []; + + // Extract data from JSON + jsonData.forEach(function(item) { + labels.push(item.column); + pct_pattern_mismatch.push(item.pct_pattern_mismatch); + pct_null_values.push(item.pct_null_values); + pct_good_data.push(item.pct_good_data); + pct_column_notfound.push(item.pct_column_notfound); + pct_dtype_issue.push(item.pct_dtype_issue); + pct_neg_values.push(item.pct_neg_values); + pct_value_notdatetime.push(item.pct_value_notdatetime); + pct_value_unknown.push(item.pct_value_unknown); + }); + + new Chart( + document.getElementById('validationbar'), { + type: 'bar', + data: { + labels: labels, + datasets: [{ + label: 'Pattern Issue', + data: pct_pattern_mismatch, + backgroundColor: "rgba(152, 134, 123, 0.75)", // Maroon shade + hoverBackgroundColor: "rgba(152, 134, 123, 1)", + barPercentage:0.65, + }, { + label: 'Null Values', + data: pct_null_values, + backgroundColor: "rgba(109, 104, 117, 0.75)", // Gray shade + hoverBackgroundColor: "rgba(109, 104, 117, 1)", + barPercentage:0.65, + }, { + label: "Good Data", + data: pct_good_data, + backgroundColor: "rgba(40, 75, 99, 0.75)", // Blue shade + hoverBackgroundColor: "rgba(40, 75, 99, 1)", + barPercentage:0.65, + }, { + label: "Column_unavailable", + data: pct_column_notfound, + backgroundColor: "rgba(255, 205, 178, 0.75)", // Light Maroon shade + hoverBackgroundColor: "rgba(255, 205, 178, 1)", + barPercentage:0.65, + }, { + label: "DataType Issue", + data: pct_dtype_issue, + backgroundColor: "rgba(111, 67, 76,0.75)", // The original color + hoverBackgroundColor: "rgba(111, 67, 76,1)", + barPercentage:0.65, + }, { + label: "Found Negative Values", + data: pct_neg_values, + backgroundColor: "rgba(255, 180, 162, 0.75)", // Reddish shade + hoverBackgroundColor: "rgba(255, 180, 162, 1)", + barPercentage:0.65, + }, { + label: "Not Datetime", + data: pct_value_notdatetime, + backgroundColor: "rgba(229, 152, 155, 0.75)", // Reddish shade + hoverBackgroundColor: "rgba(229, 152, 155, 1)", + barPercentage:0.65, + }, { + label: "Unknown value", + data: pct_value_unknown, + backgroundColor: "rgba(235, 152, 155, 0.75)", // Reddish shade + hoverBackgroundColor: "rgba(235, 152, 155, 1)", + barPercentage:0.65, + }] + + }, + options: { + indexAxis: 'y', + scales: { + x: { + stacked: true + }, + y: { + stacked: true + } + }, + plugins: { + legend: { + display: true, + position: 'top', // Place the legend to the top + align: 'end', // Place the legend to the right end + labels: { + // Use 'dataset' to display dataset labels instead of 'undefined' + generateLabels: function (chart) { + var datasets = chart.data.datasets; + var labels = chart.data.labels; + var legends = []; + + datasets.forEach(function (dataset, datasetIndex) { + // Check if any non-zero value is present in the dataset + var hasNonZeroValue = dataset.data.some(function(value) { + return value !== 0; + }); + + if (hasNonZeroValue) { + legends.push({ + text: dataset.label, + fillStyle: dataset.backgroundColor, + hidden: !chart.isDatasetVisible(datasetIndex), + lineCap: dataset.borderCapStyle, + lineDash: dataset.borderDash, + lineDashOffset: dataset.borderDashOffset, + lineJoin: dataset.borderJoinStyle, + lineWidth: dataset.borderWidth, + strokeStyle: dataset.borderColor, + pointStyle: dataset.pointStyle, + rotation: dataset.rotation, + datasetIndex: datasetIndex + }); + } + }); + return legends; + } + }, + } + }, + }, + }) +}); + +// Chart js | script to populate doughnut chart +document.addEventListener('DOMContentLoaded', function() { + + var data = { + labels: ['Structured', 'Unstructured'], + datasets: [{ + data: [58, 42], + backgroundColor: ['rgba(63,103,126,1)', 'rgba(163,103,126,1)', 'rgba(63,203,226,1)', 'rgba(90,34,21,1)', 'rgba(200,150,50,1)', 'rgba(235,91,56,1)', 'rgba(137,196,244,1)', 'rgba(245,203,83,1)', 'rgba(142,69,173,1)', 'rgba(76,175,80,1)'], + hoverBackgroundColor: ['rgba(50,90,100,1)', 'rgba(140,85,100,1)', 'rgba(46,185,235,1)', 'rgba(45,21,231,1)', 'rgba(190,120,40,1)', 'rgba(205,80,47,1)', 'rgba(101,154,204,1)', 'rgba(221,183,60,1)', 'rgba(110,49,147,1)', 'rgba(60,136,63,1)'] + }] + }; + + new Chart(document.getElementById('doughnutchart_strvsunstr'), { + type: 'doughnut', + data: data, + options: { + plugins: { + legend: { + display: true, + position: 'bottom', + align: 'center', + } + }, + tooltips: { + callbacks: { + label: function (context) { + var label = context.label || ''; + var value = context.formattedValue; + return label + ': ' + value; + } + } + } + } + }); +}); + +// Chart js | script to populate doughnut chart +document.addEventListener('DOMContentLoaded', function() { + var ranks = []; + var cnt_rank_employee = []; + + // Extract data from JSON + json_rankwise_empdist.forEach(function(item) { + ranks.push(item.Rank); + cnt_rank_employee.push(item.count_rank); + }); + + + var data = { + labels: ranks, + datasets: [{ + data: cnt_rank_employee, + backgroundColor: ['rgba(63,103,126,1)', 'rgba(163,103,126,1)', 'rgba(63,203,226,1)', 'rgba(90,34,21,1)', 'rgba(200,150,50,1)', 'rgba(235,91,56,1)', 'rgba(137,196,244,1)', 'rgba(245,203,83,1)', 'rgba(142,69,173,1)', 'rgba(76,175,80,1)'], + hoverBackgroundColor: ['rgba(50,90,100,1)', 'rgba(140,85,100,1)', 'rgba(46,185,235,1)', 'rgba(45,21,231,1)', 'rgba(190,120,40,1)', 'rgba(205,80,47,1)', 'rgba(101,154,204,1)', 'rgba(221,183,60,1)', 'rgba(110,49,147,1)', 'rgba(60,136,63,1)'] + }] + }; + + new Chart(document.getElementById('doughnutChart'), { + type: 'doughnut', + data: data, + options: { + plugins: { + legend: { + display: true, + position: 'bottom', + align: 'center', + } + }, + tooltips: { + callbacks: { + label: function (context) { + var label = context.label || ''; + var value = context.formattedValue; + return label + ': ' + value; + } + } + } + } + }); +}); + +// Badges | Doughnut chart script for pillar distribution +document.addEventListener('DOMContentLoaded', function() { + var pillar = []; + var pct_gui = []; + json_pillar_data.forEach(function(item) { + pillar.push(item.Pillar); + pct_gui.push(item.pct_gui); + }); + + var data = { + labels: pillar, + datasets: [{ + data: pct_gui, + backgroundColor: ['rgba(63,103,126,1)', 'rgba(163,103,126,1)', 'rgba(63,203,226,1)', 'rgba(90,34,21,1)', 'rgba(200,150,50,1)'], + hoverBackgroundColor: ['rgba(50,90,100,1)', 'rgba(140,85,100,1)', 'rgba(46,185,235,1)', 'rgba(45,21,231,1)', 'rgba(190,120,40,1)'] + }] + }; + + new Chart(document.getElementById('doughnutChart2'), { + type: 'doughnut', + data: data, + options: { + plugins: { + legend: { + display: true, + position: 'bottom', + align: 'center', + } + }, + tooltips: { + callbacks: { + label: function (context) { + var label = context.label || ''; + var value = context.formattedValue; + return label + ': ' + value; + } + } + } + } + }); +}); + +// Badges | Bar chart for badge earned per month +document.addEventListener('DOMContentLoaded', function() { + var month = []; + var cnt_gui_badgeinitiated = []; + var cnt_gui_badgeawarded = []; + + json_badgecompletion_data.forEach(function(item) { + month.push(item.Month); + cnt_gui_badgeinitiated.push(item.cnt_gui_badgeinitiated); + cnt_gui_badgeawarded.push(item.cnt_gui_badgeawarded); + }); + + new Chart(document.getElementById('barchart_badgecompletionpermonth'), { + type: 'line', + data: { + labels: month, + datasets: [{ + label: 'BadgeInitiated', + data: cnt_gui_badgeinitiated, + borderColor: 'rgba(154, 59, 59, 0.55)', + backgroundColor: 'rgba(154, 59, 59, 0.2)', + borderWidth: 7, + pointRadius: 4, + pointHoverRadius: 7, + fill:true, + + },{ + label: 'BadgeAwarded', + data: cnt_gui_badgeawarded, + borderColor: 'rgba(38,87,124, 0.55)', + backgroundColor: 'rgba(38,87,124,0.2)', + borderWidth: 7, + pointRadius: 4, + pointHoverRadius: 7, + fill:true, + }, + ] + }, + options: { + scales: { + y: { + beginAtZero: true + } + }, + }, + + }); +}); + +document.addEventListener('DOMContentLoaded', function() { + new Chart(document.getElementById('doughnutChart4'), { + type: 'doughnut', + data: data, + options: { + plugins: { + legend: { + display: true, + position: 'top', + align: 'right', + } + }, + tooltips: { + callbacks: { + label: function (context) { + var label = context.label || ''; + var value = context.formattedValue; + return label + ': ' + value; + } + } + } + } + }); +}); + +document.addEventListener('DOMContentLoaded', function() { + // Chart js | populating the line chart across each month with their rank + // Get the canvas element and context for the line chart + var labels = []; + var dist_staff = []; + var dist_senior = []; + var dist_manager = []; + var dist_seniormanager = []; + var dist_director = []; + var dist_partner = []; + + // Extract data from JSON + jsonEmpDist.forEach(function(item) { + labels.push(item.Month); + dist_staff.push(item.Staff); + dist_senior.push(item.Senior); + dist_manager.push(item.Manager); + dist_seniormanager.push(item.SeniorManager); + dist_director.push(item.Director); + dist_partner.push(item.Partner); + }); + + var canvas = document.getElementById('line_rankdistribution'); + var ctx = canvas.getContext('2d'); + // Data for the multiple line charts + var data = { + labels: labels, + datasets: [ + { + label: 'Staff', + data: dist_staff, + borderColor: 'rgba(0, 102, 153, 0.5)', + backgroundColor: 'rgba(0, 102, 153, 0.2)', + borderWidth: 7, + pointRadius: 7, + pointHoverRadius: 8, + // fill:true, + }, + { + label: 'Senior', + data: dist_senior, + borderColor: 'rgba(0, 204, 204, 0.5)', + backgroundColor: 'rgba(0, 204, 204,0.2)', + borderWidth: 7, + pointRadius: 7, + pointHoverRadius: 8, + // fill: true, + }, + // { + // label: 'Manager', + // data: dist_manager, + // borderColor: 'rgba(204, 102, 0, 0.5)', + // // backgroundColor: 'rgba(77, 255, 255,0.2)', + // borderWidth: 5, + // pointRadius: 5, + // // pointHoverRadius: 6, + // }, + { + label: 'Senior Manager', + data: dist_seniormanager, + borderColor: 'rgba(255, 204, 102, 0.5)', + backgroundColor: 'rgba(255, 204, 102,0.2)', + borderWidth: 7, + pointRadius: 7, + pointHoverRadius: 8, + // fill:true, + }, + { + label: 'Total Count', + data: [55, 60, 65, 50, 60, 61, 50], + backgroundColor: 'rgba(63,103,126,0.8)', + borderWidth: 1, + barPercentage: 0.6, + categoryPercentage: 0.8, + type: 'bar' + }, + ] + }; + + // Create the line chart + var lineChart = new Chart(ctx, { + type: 'line', + data: data, + options: { + elements: { + line: { + tension: 0.4, // Adjust the tension for smooth curves + }, + }, + scales: { + x: { + display: true, + title: { + display: true, + }, + }, + y: { + beginAtZero: true, // Begin y-axis at zero + display: true, + title: { + display: true, + text: 'Employee Count', + }, + }, + }, + } + }); +}); + +// Calculate cumulative percentage +document.addEventListener('DOMContentLoaded', function() { + var data = { + labels: ['Bengaluru', 'Mumbai', 'Kolkata', 'Hyderabad', 'Gurgaon', 'Noida', 'Pune'], + datasets: [ + { + label: 'Employee Count', + data: [2541, 1965, 1809, 1592, 1294, 762, 147], + backgroundColor: 'rgba(0, 68, 102, 0.7)', + yAxisID: 'primary', + barPercentage: 0.6, + }, + { + label: 'Cumulative Percentage', + data: [25,44,62, 78, 91, 99, 100], + borderColor: 'rgba(163,103,126,0.7)', + backgroundColor: 'transparent', + borderWidth: 4, + pointRadius: 5, + yAxisID: 'secondary', + type: 'line', + }, + ], + }; + + // Get the canvas context + var ctx = document.getElementById('pareto_citydistribution').getContext('2d'); + + // Create the multi-axis Pareto diagram with options + var pareto_citydistribution = new Chart(ctx, { + type: 'bar', + data: data, + options: { + scales: { + x: { + display: true, + title: { + display: true, + text: 'City', + }, + }, + primary: { + type: 'linear', + position: 'left', + beginAtZero: true, + display: true, + title: { + display: true, + text: 'Employee Count', + }, + }, + secondary: { + type: 'linear', + position: 'right', + beginAtZero: true, + display: true, + title: { + display: true, + text: 'Cumulative Percentage', + }, + }, + }, + plugins: { + legend: { + display: true, + }, + }, + }, + }); +}); + +// chat function which loads user message and gets bot response by invoking the URI +document.addEventListener("DOMContentLoaded", function () { + const msgerForm = document.querySelector(".msger-inputarea"); + const msgerInput = document.querySelector("#textInput"); + const msgerChat = document.querySelector(".chat-container"); + + msgerForm.addEventListener("submit", function (event) { + event.preventDefault(); + const msgText = msgerInput.value; + if (!msgText) return; + + appendMessage(msgText); + msgerInput.value = ""; + botResponse(msgText); + }); + + function appendMessage(text) { + const msgHTML = ` +
+
+
+ ${text} +
+
+ `; + + msgerChat.insertAdjacentHTML("beforeend", msgHTML); + msgerChat.scrollTop += 500; + + setTimeout(function() { + const loadHTML = ` +
+ + +
+ `; + msgerChat.insertAdjacentHTML("beforeend", loadHTML); + msgerChat.scrollTop += 500; + }, 1000); + } + + function botResponse(rawText) { + + // const table_selected = document.getElementById("table-dropdown").value; + const url = window.location.href; + const parts = url.split('/'); + const lastPart = parts[parts.length - 1]; + // Remove any query parameters (e.g., '?foo=bar') by splitting at '?' + const withoutQuery = lastPart.split('?')[0]; + // Assign the substring to table_selected + table_selected = withoutQuery.replace('validate_', '');; + + $.get("/get_val_llmresponse", { msg: rawText, table_selected: table_selected }).done(function (data) { + // Create a new Date object to represent the current date and time + const currentDate = new Date(); + // Get various components of the current date and time + const year = currentDate.getFullYear(); // Get the current year (e.g., 2023) + const month = currentDate.getMonth() + 1; // Get the current month (0-11, add 1 for January to December) + const day = currentDate.getDate(); // Get the current day of the month (1-31) + const hours = currentDate.getHours(); // Get the current hour (0-23) + const minutes = currentDate.getMinutes(); // Get the current minute (0-59) + const seconds = currentDate.getSeconds(); // Get the current second (0-59) + const milliseconds = currentDate.getMilliseconds(); // Get the current millisecond (0-999) + const timestamp_now = `${year}${month}${day}-${hours}${minutes}${seconds}${milliseconds}` + const canvasid = "canvasid_" + timestamp_now + + var responseData = JSON.parse(data); + + var issuccess = responseData.success; + var chart_type = responseData.chart_type; + var chart_label = responseData.chart_label; + var text_to_display = responseData.text_to_display; + + if (chart_type === 'text') { + if (text_to_display === null || text_to_display === '') { + text_to_display = 'Error Please try modifying the prompt with more details.'; + } + } + + var chart_data = JSON.parse(responseData.chart_json_data); + + // clear the loading icon + // Get the element by its ID + var element = document.getElementById("loading-div"); + // Check if the element exists before attempting to remove it + if (element) { + element.remove(); // Remove the element + } else { + console.log("Loading div not found"); + } + + const msgHTML = ` +
+
+
+ ${chart_type !=='text' ? `` : text_to_display} +
+
+ `; + msgerChat.insertAdjacentHTML("beforeend", msgHTML); + msgerChat.scrollTop += 500; + + // Create the chart for this message + new Chart(document.getElementById(canvasid), { + // type: 'line', + data: chart_data, + options: { + scales: { + y: { + beginAtZero: true + } + }, + plugins: { + legend: { + display: true, + position: 'bottom', + align: 'center', + }, + }, + } + }); + }); + } + }); + + +// Miscellanous | Bar chart count of GUI matching with +document.addEventListener('DOMContentLoaded', function() { + var tableinconsideration = ['Workforce', 'GTE', 'TR', 'Badges', 'Learning', 'LAT', 'WorkExperience']; + var pct_commongui = [100, 98, 73, 89, 75, 70, 78]; + + // json_badgecompletion_data.forEach(function(item) { + // month.push(item.Month); + // cnt_gui_badgeinitiated.push(item.cnt_gui_badgeinitiated); + // cnt_gui_badgeawarded.push(item.cnt_gui_badgeawarded); + // }); + + new Chart(document.getElementById('alltable_matchbar'), { + type: 'bar', + data: { + labels: tableinconsideration, + datasets: [{ + label: 'Percentage of GUIs matching with other tables', + data: pct_commongui, + borderColor: 'rgba(0, 68, 102, 0.8)', + backgroundColor: pct_commongui.map(value => value < 75 ? '#EE9322' : 'rgba(0, 68, 102, 0.6)'), + barPercentage: 0.65 + }] + }, + options: { + indexAxis: 'y', + scales: { + x: { + beginAtZero: true + } + }, + plugins: { + verticalLine: { + x: 75, // The x-coordinate where you want to draw the line + borderColor: '#FF9B50', // Line color + borderWidth: 4, // Line width + label: { + text: '75%', // Label text + position: 'top', // Label position + backgroundColor: 'white', // Label background color + }, + } + }, + }, + + plugins: [{ + beforeDraw: (chart) => { + const line = chart.options.plugins.verticalLine; + if (line) { + const ctx = chart.ctx; + const x = chart.scales.x.getPixelForValue(line.x); + // Set the line to be dotted + ctx.setLineDash([10, 5]); // Adjust the numbers to change the dash pattern + + // Draw the vertical line + ctx.save(); + ctx.beginPath(); + ctx.strokeStyle = line.borderColor; + ctx.lineWidth = line.borderWidth; + ctx.moveTo(x, chart.chartArea.top); + ctx.lineTo(x, chart.chartArea.bottom); + ctx.stroke(); + ctx.restore(); + + // Draw the label + if (line.label) { + const labelX = x + 5; // Adjust the label's x-coordinate for proper positioning + const labelY = chart.chartArea.top + 145; // Adjust the label's y-coordinate for proper positioning + + ctx.fillStyle = line.label.backgroundColor; + ctx.fillRect(labelX, labelY, 25, 15); + + ctx.textAlign = 'left'; + ctx.font = '12px Arial'; + ctx.fillStyle = 'black'; + ctx.fillText(line.label.text, labelX + 5, labelY + 12); + } + } + } + }], +}); +}) \ No newline at end of file diff --git a/templates/chatfile8.html b/templates/chatfile8.html new file mode 100644 index 0000000000000000000000000000000000000000..9f9408e0cb350249c8f3da2ea7f638e83cf86758 --- /dev/null +++ b/templates/chatfile8.html @@ -0,0 +1,63 @@ + + + + + + + + + Collapsible Chat Panel + + + + +
+
+
+ LaborEconomicsBot + + + +
+
+
+
+
+ Ask any question related to labor ecomomics Data! +
+
+
+ +
+
+ + + + +
+
+
+ +
+ + + + + + + + \ No newline at end of file diff --git a/templates/data.html b/templates/data.html new file mode 100644 index 0000000000000000000000000000000000000000..c941292985434c23230f68a247011effe880eccd --- /dev/null +++ b/templates/data.html @@ -0,0 +1,114 @@ +{% extends 'lay_side.html' %} + +{% block css %} + + + +{% endblock %} + +{% block content %} +
+ + +
+
+ + +
+
+ + +
+
+ + +
+
+ + +
+ {% for _, table_html in table_htmls.items() %} +
+ {{ table_html | safe }} +
+ {% endfor %} +
+
+ +
+ +
+ +
+
+
+ {% include 'chatfile8.html' %} +
+ +{% endblock %} + +{% block javascript %} + + + + + + + + + + +{% endblock %} diff --git a/templates/home.html b/templates/home.html new file mode 100644 index 0000000000000000000000000000000000000000..40d5f2229a3edcc8fe90665c8fc7ded8534cd61c --- /dev/null +++ b/templates/home.html @@ -0,0 +1,72 @@ +{% extends 'lay_side.html' %} + +{% block css %} + + + +{% endblock %} + +{% block content %} + +
+
+
+
+
+

User Input Page

+

Please select below filters. Please note that GPNs extracted from workforce data would be used to get other datasets.

+
+
+ +
+   + + + +
+
+ +
+ + +
+ +
+ + +
+ + +
+
+
+
+{% endblock %} + +{% block javascript %} + + + + + + + + +{% endblock %} diff --git a/templates/index.html b/templates/index.html new file mode 100644 index 0000000000000000000000000000000000000000..868e9547f458e83147a0d42711a83e8ee129ba34 --- /dev/null +++ b/templates/index.html @@ -0,0 +1,179 @@ + + + + + Laboreconomics_allinone + + + + + + + + + + + + +
+
+
+
+ +
+
+ +
+
+ +
+ +
+   + + +
+
+ +
+ + +
+ +
+
+ +
+
+ +
+
+ +
+
+
+ +
+ {% if show_table %} +
+ + + + +
+ + +
+ + +
+
+
+
+ {{ form_data | safe}} + +
+
+
+
+
+
Stats
+

Table Name: Table 1

+

Number of Records: 100

+

No of Columns: 24

+

DataTypes: String

+

Table values: 99

+

Possible: Yes

+

DataVolume: Yes

+
+
+
+ +
+
+
+ +
+
+ {{ form_data | safe }} +
+
+ +
+
+ {{ form_data | safe }} +
+
+ +
+
+ +
+
+ {% endif %} + + + + + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/templates/lay_side.html b/templates/lay_side.html new file mode 100644 index 0000000000000000000000000000000000000000..99accd1cfa2745a4229b6883e2986e63596ef495 --- /dev/null +++ b/templates/lay_side.html @@ -0,0 +1,130 @@ + + + + + + {% block title %}LE_Web{% endblock %} + + + + + + + + + + {% block css %} + {% endblock %} + + +
+ + +
+ +
+
+ {% if show_sidebar %} + +
+
+ + + +
+
+ {% endif %} + + +
+ {% block content %} + + {% endblock %} +
+
+ +
+ + + + + + + + + {% block javascript %} + {% endblock %} + + diff --git a/templates/survey_display.html b/templates/survey_display.html new file mode 100644 index 0000000000000000000000000000000000000000..5ed88c1ac2c1e145ce5804d5c6bd48529b514c92 --- /dev/null +++ b/templates/survey_display.html @@ -0,0 +1,93 @@ + + + + + + + + +
+ +
+ + + + diff --git a/templates/validate_badges.html b/templates/validate_badges.html new file mode 100644 index 0000000000000000000000000000000000000000..105702a2597b3f720c30cf9134c818af581448bc --- /dev/null +++ b/templates/validate_badges.html @@ -0,0 +1,156 @@ +{% extends 'lay_side.html' %} + +{% block css %} + + +{% endblock %} + + +{% block content %} +
+ +
+
+
+
+
+
+
Employee Count
+

{{ table_info['unique_gui'] }}

+
+
+
+
+
+
+
Record Count
+

{{ table_info['n_rows'] }}

+
+
+
+ +
+
+
+
# Features
+

{{ table_info['n_cols'] }}

+
+
+
+ +
+
+
+
Placeholder
+

Yes

+
+
+
+
+
+ + +
+
+
+
+

Data Validation for badges

+

All entries have undergone thorough validation and have been meticulously categorized into specific groups. + The Y-axis of the input data table lists the columns against which validation checks were conducted. These + validations have culminated in a visually informative bar chart, offering a clear representation of the + percentage distribution across each validated category. +

+ +
+
+
+
+
+
+
+
+
+
+
Badge Earned month over month
+

The data shows a monthly trend in badge initiation and awarding, + with the highest initiation count in February (56) and the highest award count in January (38). + Overall, badge activity remains consistent, with variations in each month.

+ + +
+
+
+
+
+
+
Pillar distribution across badges
+

The chart below shows the distribution of pillars across badges

+ +
+
+
+
+
+
+
+
+
+
+
+
Structured vs Unstructured
+ + + +
+
+
+
+
+
+
Badge Title Distribution
+

+ {% for item in lst_topfive_badgetitle %} + {{ item }} + {% endfor %} +

+

The most interest lies in Agile Learning and Data Integration, with a strong focus on skill + develop ment. Data Visualization and Cloud Learning are also popular, reflecting a growing interest + in data presentation and cloud technologies. Robotic Process Automation badges signify a commitment + to automation skills, while Data Science Learning badges show an emerging interest in data science. + These badges offer valuable opportunities for personal and professional growth.

+
+
+
+
+
+
+ +
+ {% include 'chatfile8.html' %} +
+ + {% endblock %} + + {% block javascript %} + + + + + + + + + + + + + {% endblock %} + + \ No newline at end of file diff --git a/templates/validate_learning.html b/templates/validate_learning.html new file mode 100644 index 0000000000000000000000000000000000000000..77b24fdf4e51c3ba4615863869ef260174133bb0 --- /dev/null +++ b/templates/validate_learning.html @@ -0,0 +1,124 @@ +{% extends 'lay_side.html' %} + +{% block css %} + + + +{% endblock %} + +{% block content %} +
+ + +
+
+
+
+
+
+
Employee Count
+

{{ table_info['unique_gui'] }}

+
+
+
+
+
+
+
Record Count
+

{{ table_info['n_rows'] }}

+
+
+
+ +
+
+
+
# Features
+

{{ table_info['n_cols'] }}

+
+
+
+ +
+
+
+
Placeholder
+

Yes

+
+
+
+
+
+
+
+
+
+

Data Validation for Learning

+

We have done the validations on data given and we have categorized the data into various categories. + which shows good data which is displayed on right against each columns and bad data which should be either + processed + or discarded on left side against the column. Here are the results. +

+ +
+
+
+
+
+
+
+

Employee variation over cities for Learning

+

The pareto diagram shows the distribution of employees over different cities. +

+ +
+
+
+
+
+
+
+
+ {{ bar_chart_html | safe }} +
+
+ +
+
+
+
+
+
+
+

Employee variation for badges

+

The line chart below shows the variation of employees based on Rank and their count. +

+ +
+
+
+
+ + {% endblock %} + + {% block javascript %} + + + + + + + + + + + + + {% endblock %} \ No newline at end of file diff --git a/templates/validate_miscellaneous.html b/templates/validate_miscellaneous.html new file mode 100644 index 0000000000000000000000000000000000000000..ab388208b22039c840515f73d339306b31c10f33 --- /dev/null +++ b/templates/validate_miscellaneous.html @@ -0,0 +1,47 @@ +{% extends 'lay_side.html' %} + +{% block css %} + + +{% endblock %} + +{% block content %} + +
+
+
+
+
+

Data Completeness Stats

+

The graph illustrates the percentage of GUI matching with various tables, + offering valuable statistics to guide dataset selection decisions. This information is + beneficial as it aids in assessing dataset suitability, ensuring that the chosen dataset + aligns with specific project requirements and objectives. Additionally, + it streamlines decision-making processes and enhances data quality and project outcomes. +

+ +
+
+
+
+ {% endblock %} + + {% block javascript %} + + + + + + + + + + + + + + {% endblock %} \ No newline at end of file diff --git a/templates/validate_workforce.html b/templates/validate_workforce.html new file mode 100644 index 0000000000000000000000000000000000000000..bb109045667e8fbdc3fb35773f01e4fe71ee1533 --- /dev/null +++ b/templates/validate_workforce.html @@ -0,0 +1,153 @@ +{% extends 'lay_side.html' %} + +{% block css %} + + +{% endblock %} + +{% block content %} +
+ + +
+
+
+
+
+
+
Employee Count
+

{{ table_info['unique_gui'] }}

+
+
+
+
+
+
+
Record Count
+

{{ table_info['n_rows'] }}

+
+
+
+ +
+
+
+
# Features
+

{{ table_info['n_cols'] }}

+
+
+
+ +
+
+
+
Placeholder
+

Yes

+
+
+
+
+
+
+
+
+
+

Data Validation Stats

+

Each entry has been validated and categorized into one of the designated groups. + The columns against which validation was performed in the input data are depicted on the Y-axis. + The validation statistics are represented as a bar chart, displaying the percentage for each category. +

+ +
+
+
+
+
+
+
+
+
+
Gender Analysis
+ +

{{ aicontent_genderanalysis }}

+
+
+ +
+
+
Department Analysis
+

There are 402 distinct departments in the datasets and below are top ten departments based on number of employees.

+ +

+ {% for item in lst_topfive_dept %} + {{ item }} + {% endfor %} +

+ +
+
+ +
+ +
+
+
+
Rank Distribution
+ + +
+
+
+ +
+
+
+
+
+
+

Visualizing Employee Count Over Time

+

This chart displays the employee count over time, month by month. + The bars represent the total employee count, while the lines show counts specific to different ranks. + Dive into the insights about our workforce's evolution. +

+ +
+
+
+
+
+
+
+

Employee Distribution across cities

+

Explore the Pareto diagram below to see how our employees are distributed across different cities. + The bars represent each city's employee count, with the highest counts on the left. + This visual insight helps you quickly identify our key workforce locations. +

+ +
+
+
+
+ {% include 'chatfile8.html' %} +
+ {% endblock %} + + {% block javascript %} + + + + + + + + + + + + + + {% endblock %} \ No newline at end of file diff --git a/utilities/plotting.py b/utilities/plotting.py new file mode 100644 index 0000000000000000000000000000000000000000..bbce622dbd8f323fbe171a4475a0b34eeea08580 --- /dev/null +++ b/utilities/plotting.py @@ -0,0 +1,99 @@ +import pandas as pd +import sqlite3 + +def badges_get_pillar_dougnutdata(): + con = sqlite3.connect("database.db") + df = pd.read_sql_query(f"SELECT * from badges", con) + sdf = df.drop_duplicates()[['GUI', 'Pillar']] + sdf = sdf[(sdf.Pillar.notna()) | (sdf.Pillar != 'null')] + pillar_dist = sdf.groupby('Pillar').count().reset_index().rename(columns={'GUI':'cnt_gui'}) + sum_validrecords = pillar_dist.cnt_gui.sum() + pillar_dist['pct_gui'] = pillar_dist['cnt_gui'] / sum_validrecords + badges_pillar_doughnut_json = pillar_dist.to_json(orient='records') + return badges_pillar_doughnut_json + +def badges_get_badgecompletion_monthwise(): + df = pd.DataFrame( + { + 'Month':['Nov-23', 'Dec-23', 'Jan-23', 'Feb-23', 'Mar-23', 'Apr-23', 'May-23', 'Jun-23'], + 'cnt_gui_badgeinitiated':[45,40,30,56, 50,32,37,25], + 'cnt_gui_badgeawarded': [23,34,38,40, 31, 40,23,28], + }, + ) + print(df) + badgecompletion_monthwise_json = df.to_json(orient='records') + return badgecompletion_monthwise_json + +def get_validation_json(table_name, run_required=False): + ## Dummy data for workforce + con = sqlite3.connect("database.db") + validation_df = pd.read_sql_query(f"SELECT * from {table_name}_validation", con) + json_data = validation_df.to_json(orient='records') + return json_data + +def get_wfrankwise_countmom(df=None): + data = [ + ('Jan', 9, 15, 3, 30, 25, 23, 110), + ('Feb', 7, 14, 2, 32, 40, 35, 106), + ('Mar', 6, 13, 4, 36, 34, 20, 105), + ('Apr', 8, 15, 3, 21, 30, 25, 112), + ('May', 9, 19, 4, 25, 35, 30, 121), + ('Jun', 7, 14, 3, 20, 25, 35, 113), + ('Jul', 10, 11, 3, 41, 27, 25, 113) + ] + columns = ['Month', 'Director', 'Manager', 'Partner', 'Senior', 'SeniorManager', 'Staff', 'Grand Total'] + df = pd.DataFrame(data, columns=columns) + json_df = df.to_json(orient='records') + + return json_df + +def get_lst_topdepartment(): + lst_dept = [ + 'D&A-BI&R-FS-GDS_S-BLR (138)', + 'D&A-BI&R-FS-GDS_NS-CCU (128)', + 'IntA-IntAut-NF-GDS_S-BLR (88)', + 'IntA-IntAut-NF-GDS_NS-GGN (75)', + 'D&A-BI&R-FS-GDS_NS-HYD (70)', + 'D&A-InMg-FS-GDS_S-BLR (70)', + 'INTA-INTAUT-NF (67)', + 'D&A-BI&R-FS-GDS_S-COK-L (59)', + 'D&A-BI&R-FS-GDS_S-MAA (58)', + 'D&A-InMg-NF-GDS_S-BLR (49)' + ] + return lst_dept + +def get_wfrankwise_count(): + + #write the logic to create pandas dataframe like below + data = { + "Rank": [ + "Contractor", + "Director(Exec./Asst.)", + "Manager", + "null", + "Senior", + "Senior Manager", + "Staff/Intern" + ], + "count_rank": [10, 10, 253, 322, 1391, 92, 1020] + } + + df = pd.DataFrame(data) + json_rankwise_count = df.to_json(orient='records') + return json_rankwise_count + + +def get_topfive_badgetitle(): + lstbadges = [ + 'Agile Learning Badge (479)', + 'Data Integration Bronze Badge (362)', + 'Data Integration Learning Badge (339)', + 'Data Visualization Bronze Badge (306)', + 'Data Visualization Learning Badge (295)', + 'Cloud Learning Badge (291)', + 'Robotic Process Automation Learning Badge (212)', + 'Robotic Process Automation Bronze Badge (191)', + 'Data Visualization Bronze Learning Badge (166)', + 'Data Science Learning Badge (165)' + ] + return lstbadges \ No newline at end of file