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# 1. Open a "Terminal" by: View --> Terminal OR just the "Terminal" through the hamburger menu
# 2. run in terminal with: streamlit run app.py
# 3. click the "Open in Browser" link that pops up OR click on "Ports" and copy the URL
# 4. Open a Simple Browswer with View --> Command Palette --> Simple Browser: Show
# 5. use the URL from prior steps as intput into this simple browser
import re
import streamlit as st
import altair as alt
from vega_datasets import data
import pandas as pd
st.title('Final Project')
st.text("The URL for this app is: https://huggingface.co/spaces/445final/final2.moved")
df = pd.read_csv('State_Employee_Pay.csv')
df_copy = df.copy()
df['Period Pay Rate'] = df['Period Pay Rate'].str.replace(",", "")
df['YTD Gross'] = df['YTD Gross'].str.replace(",", "")
df['Period Pay Rate'] = df['Period Pay Rate'].astype(int)
df['YTD Gross'] = df['YTD Gross'].astype(int)
df = df.dropna()
df = df[df['YTD Gross']!= 0]
df['Agency'] = df['Agency'].str.lower()
df['Agency Division'] = df['Agency Division'].str.lower()
df['Employee Name'] = df['Employee Name'].str.lower()
df['Position Title'] = df['Position Title'].str.lower()
df_c = df[df['Agency'] == 'corrections']
df_t = df[df['Agency'] == 'transportation']
df1 = df_t
#agency_division_list = df1['Agency Division'].value_counts().tolist()
agency_division_list = df1['Agency Division'].unique().tolist()
selected_division = st.selectbox('Agency Division:',
options=agency_division_list,
index=0)
# horizontal bar chart
def division_positions(selected_division):
df_db = df1[df1['Agency Division'] == selected_division]
bar_chart_data = df_db.groupby('Position Title').agg(
employeeCount=('Employee Name', 'count'),
meanYTDGross=('YTD Gross', 'mean')).reset_index()
bar_chart_data = bar_chart_data.sort_values('meanYTDGross', ascending=False)
chart_bar = alt.Chart(bar_chart_data).mark_bar().encode(
x=alt.X('employeeCount', title = '# of Employees'),
y=alt.Y('Position Title:O'),
tooltip=['Position Title', 'employeeCount', alt.Tooltip(
'meanYTDGross:Q', format='$,.0f', title='Avg YTD Gross')]
).properties(title=f'Employee Count by Position in: {selected_division}',
height=alt.Step(20)).interactive()
return chart_bar
if selected_division:
final_chart = division_positions(selected_division)
st.altair_chart(final_chart, use_container_width=True)
st.text('Overall Future Edits: Figure out what to do with positions with 1 employee (if anything), Decide whether to use transportation or corrections data, Re-capitalize agency departments')
st.text('Chart A Future Edits: Order bars by mean YTD Gross, Make all position titles readable, add title')
#im just going to relaod the data frame in to clean up the text on the bottomo charts
df_j = pd.read_csv('State_Employee_Pay.csv')
df_jcopy = df_j.copy()
df_jcopy['Period Pay Rate'] = df_jcopy['Period Pay Rate'].str.replace(",", "").astype(int)
df_jcopy['YTD Gross'] = df_jcopy['YTD Gross'].str.replace(",", "").astype(int)
df_jcopy = df_jcopy.dropna()
df_jcopy = df_jcopy[df_jcopy['YTD Gross'] != 0]
# df_jcopy['Agency'] = df_jcopy['Agency'].str.lower()
# df_jcopy['Agency Division'] = df_jcopy['Agency Division'].str.lower()
# df_jcopy['Employee Name'] = df_jcopy['Employee Name'].str.lower()
# df_jcopy['Position Title'] = df_jcopy['Position Title'].str.lower()
df_jcopy['Agency'] = df_jcopy['Agency'].str.replace(r'^(il |ill |illinois )', '', flags=re.IGNORECASE, regex=True)
df_jcopy.columns = df_jcopy.columns.str.strip()
df_top25=df_jcopy.sort_values("YTD Gross", ascending=False.head(50))
alt.data_transformers.disable_max_rows()
df_small=df[['Agency','YTD Gross']].copy()
select_bar = alt.selection_point(
fields=["Agency"],
on="click",
clear="true"
)
#summing the barchart but the human services and transit departments are so large you cannot click on the other agencies
# bar_chart = (
# alt.Chart(df_small)
# .mark_bar()
# .encode(
# y=alt.Y("Agency:N", sort="-x"),
# x=alt.X("sum(YTD Gross):Q", title="Total Personale Expense"), # <-- take the mean
# tooltip=[
# "Agency:N",
# alt.Tooltip("mean(YTD Gross):Q", title="Avg YTD Gross", format="$,.0f")
# ],
# color=alt.condition(select_bar, alt.value("#4C78A8"), alt.value("#CCCCCC"))
# )
# .add_params(select_bar)
# .properties(width=500, height=800)
# )
# bar_chart = (
# alt.Chart(df_small)
# .mark_bar()
# .encode(
# y=alt.Y("Agency:N", sort="-x"),
# x=alt.X("mean(YTD Gross):Q", title="Average Personale Expense"), # <-- take the mean
# tooltip=[
# "Agency:N",
# alt.Tooltip("mean(YTD Gross):Q", title="Avg YTD Gross", format="$,.0f")
# ],
# color=alt.condition(select_bar, alt.value("#4C78A8"), alt.value("#CCCCCC"))
# )
# .add_params(select_bar)
# .properties(width=500, height=800)
# )
bar_chart = (
alt.Chart(df_top25)
.mark_bar()
.encode(
y=alt.Y("Agency:N", sort="-x"),
x=alt.X("mean(YTD Gross):Q", title="Total Personale Expense"),
tooltip=[
"Agency:N",
alt.Tooltip("mean(YTD Gross):Q", title="Avg YTD Gross", format="$,.00f")
],
color=alt.condition(select_bar, alt.value("#4C78A8"), alt.value("#CCCCCC"))
)
.add_params(select_bar)
.properties(width=500, height=800)
)
# box = (
# alt.Chart(df_small)
# .mark_boxplot(size=40)
# .encode(
# x=alt.X("Agency:N", title=""),
# y=alt.Y("YTD Gross:Q", title="Salary Distribution"),
# opacity=alt.condition(select_bar,alt.value(1),alt.value(0)),
# color=alt.value("#4C78A8")
# )
# .properties(width=1000, height=800)
# )
# hist = (
# alt.Chart(df_small)
# .mark_bar(opacity=0.7)
# .encode(
# x=alt.X("YTD Gross:Q", bin=True, title="YTD Gross (binned)"),
# y=alt.Y("count()", title="Count"),
# color=alt.value("#4C78A8"),
# tooltip=[alt.Tooltip("YTD Gross:Q",title="Range"),alt.Tooltip("count():Q",title="Count")]
# )
# .transform_filter(select_bar)
# .properties(width=400, height=300)
# )
strip = (
alt.Chart(df_jcopy)
.mark_circle(size=60, opacity=0.6)
.encode(
x=alt.X("YTD Gross:Q", title="YTD Gross"),
y=alt.Y("Agency:N", title=""),
color=alt.Color("Agency:N",title='Agency'),
tooltip=[
alt.Tooltip("Position Title:O"),
alt.Tooltip("YTD Gross:Q", format="$,.0f")
]
)
.transform_filter(select_bar)
.transform_calculate(
jitter="0.4 * (random() - 0.5)"
)
.encode(
y=alt.Y("jitter:Q", title="", axis=None)
)
.properties(width=400, height=200)
)
dashboard = bar_chart & strip
dashboard
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