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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)
df = pd.read_csv("referencefiles/badges.csv")
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)
val_file_name = f"referencefiles/{table_name}_validation.csv"
validation_df = pd.read_csv(val_file_name)
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 |