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testing123/section_1_graph_export_module/nbs_analysis_script.py
2026-05-21 08:40:24 -04:00

226 lines
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Python

# FILE: nbs_analysis_script.py
# CREATED: 12/26/25
# AUTHOR: Vincent Allen
# PURPOSE: Script to generate New Business Starts (NBS) analysis graphs and datasets from prepared Neoserra data.
# Third party libraries
import pandas as pd
import sys
import os.path
import argparse
import json
# Custom modules
# Importing the functions from the library code provided
from section_1_graph_library_module import ( # pyright:ignore
make_nbs_attribution_network_wide,
make_attribution_rate_chart,
make_theoretical_attribution_rate_chart,
make_director_confirmed_graph
)
from milestone_attribution_dataset_module import sanitize_nbs_data
from constants_module import NEOSERRA_COLUMNS, OUT_COLUMNS
from shared_tools_module import csv_url_to_dataframe
def parse_args():
parser = argparse.ArgumentParser(description="Generate New Business Starts (NBS) Analysis Graphs")
dataset_group = parser.add_mutually_exclusive_group(required=True)
dataset_group.add_argument("--inputcsv",
type=str,
help="The path to the raw NBS analysis CSV dataset.")
dataset_group.add_argument("--exportmoduleurl",
type=str,
help="The url to the configured export module for the NBS milestones data in Neoserra.")
parser.add_argument("--outpath",
type=str,
required=True,
help="The base directory path to place generated files into.")
parser.add_argument("--fiscalyear",
required=True,
type=str,
help="The fiscal year tag to place at the end of graph titles.")
parser.add_argument("--mapping",
type=str,
required=False,
help="Path to a JSON file to override default column names mappings.")
# --- GRAPH 1: Network Wide Stacked Bar ---
parser.add_argument("--netwidefilename",
type=str,
default="nbsattributionnetworkwide",
help="Filename for the network-wide attribution stacked bar chart.")
parser.add_argument("--netwidetitle",
type=str,
default="New Business Start Attributions Per Center FY 25",
help="Title for the network-wide attribution graph.")
# --- GRAPH 2: Attribution Rate Chart ---
parser.add_argument("--ratefilename",
type=str,
default="nbsattributionrate",
help="Filename for the attribution rate bar chart.")
parser.add_argument("--ratedatafilename",
type=str,
default="nbs_attribution_rate_data.csv",
help="Filename for the intermediate dataset used for the attribution rate chart.")
# --- GRAPH 3: Theoretical Rate Chart ---
parser.add_argument("--theoreticalfilename",
type=str,
default="theoreticalnbsattributionrate",
help="Filename for the theoretical attribution rate bar chart.")
parser.add_argument("--theoreticaltitle",
type=str,
default="Documented Percentage if All NBS Milestones With an Attribution Source had an Affirmation FY 25",
help="Title for the theoretical attribution rate graph.")
parser.add_argument("--theoreticaldatafilename",
type=str,
default="theoretical_nbs_rate_data.csv",
help="Filename for the intermediate dataset used for the theoretical rate chart.")
# --- GRAPH 4: Director Confirmed Chart ---
parser.add_argument("--directorfilename",
type=str,
default="directorconfirmednbs",
help="Filename for the director confirmed NBS bar chart.")
parser.add_argument("--directortitle",
type=str,
default="Percentage of Director Confirmed NBS Attributions Per Center FY 25",
help="Title for the director confirmed graph.")
parser.add_argument("--directordatafilename",
type=str,
default="director_confirmed_nbs_data.csv",
help="Filename for the intermediate dataset used for the director confirmed chart.")
parser.add_argument("--report",
type=str,
required=False,
default="nbsanalysis",
help="The prefix used to name report files such that the word generation scripts can find them with the image registry")
return parser.parse_args()
if __name__ == "__main__":
args = parse_args()
# Handle optional JSON mapping override
if args.mapping:
NEOSERRA_COLUMNS.apply_json_mapping(args.mapping)
OUT_COLUMNS.apply_json_mapping(args.mapping)
# Ensure output directory exists
if not os.path.exists(args.outpath):
try:
os.makedirs(args.outpath)
except OSError as e:
print(f"Error creating output directory: {e}")
sys.exit(1)
print(f"Loading input data from {args.inputcsv}...\n")
if args.inputcsv:
try:
nbs_df = pd.read_csv(args.inputcsv)
except Exception as e:
print(f"Failed to read input CSV: {e}")
sys.exit(1)
elif args.exportmoduleurl:
try:
nbs_df = csv_url_to_dataframe(args.exportmoduleurl)
except Exception as e:
print("Failed to grab the csv data from the Neoserra export module")
print(f'Got={e}')
else:
raise RuntimeError("No input data source was defined, this should not be possible unless you have changed the code")
# Filter for reportable records only.
# This will fail with a KeyError if the column is missing, as required.
nbs_df = nbs_df[nbs_df[NEOSERRA_COLUMNS.reportable] == 1]
# Do the data cleaning on the dataset
nbs_df = sanitize_nbs_data(
nbs_df,
col_neo_center=NEOSERRA_COLUMNS.center,
col_neo_client_id=NEOSERRA_COLUMNS.client_id,
col_neo_milestone_date=NEOSERRA_COLUMNS.milestone_date,
col_neo_attribution_date=NEOSERRA_COLUMNS.attribution_date,
col_neo_attribution_source=NEOSERRA_COLUMNS.milestone_attribution_source,
col_neo_affirmation=NEOSERRA_COLUMNS.milestone_affirmation,
col_neo_milestone_type=NEOSERRA_COLUMNS.milestone_type_name,
col_out_documentation_level=OUT_COLUMNS.milestone_documentation_level,
col_neo_reportable=NEOSERRA_COLUMNS.reportable,
business_start_impact_val=NEOSERRA_COLUMNS.business_start_impact_val,
business_established_val=NEOSERRA_COLUMNS.business_established_val
)
"""
tag_documentation_level(
nbs_df,
col_neo_attribution_source=active_config["col_neo_attribution_source"],
col_neo_affirmation=active_config["col_neo_affirmation"],
col_out_documentation_level=active_config["col_out_documentation_level"]
)
"""
nbs_df.to_csv(os.path.join(args.outpath, f"cleaned_nbs_dataset_{args.fiscalyear}.csv"))
# 1. Network Wide Attribution
print("Generating Network Wide Attribution Graph...\n")
network_fig = make_nbs_attribution_network_wide(
nbs_df,
title=args.netwidetitle,
col_neo_center=NEOSERRA_COLUMNS.center,
col_documentation_level=OUT_COLUMNS.milestone_documentation_level
)
network_fig.write_image(os.path.join(args.outpath, f"{args.report}_{args.netwidefilename}_.png"))
# 2. Attribution Rate Chart
print("Generating Attribution Rate Chart and Dataset...\n")
rate_fig = make_attribution_rate_chart(
nbs_df,
fiscalyear=args.fiscalyear,
source_data_export_path=str(os.path.join(args.outpath, args.ratedatafilename)),
documented_tag=OUT_COLUMNS.val_documented,
col_neo_center=NEOSERRA_COLUMNS.center,
col_documentation_level=OUT_COLUMNS.milestone_documentation_level
)
rate_fig.write_image(os.path.join(args.outpath, f"{args.report}_{args.ratefilename}_.png"))
# 3. Theoretical Attribution Rate Chart
print("Generating Theoretical Attribution Rate Chart and Dataset...\n")
theoretical_fig = make_theoretical_attribution_rate_chart(
nbs_df,
title=args.theoreticaltitle,
source_data_export_path=str(os.path.join(args.outpath, args.theoreticaldatafilename)),
documented_tag=OUT_COLUMNS.val_documented,
affirmation_missing_tag=OUT_COLUMNS.val_affirmation_missing,
col_neo_center=NEOSERRA_COLUMNS.center,
col_documentation_level=OUT_COLUMNS.milestone_documentation_level
)
theoretical_fig.write_image(os.path.join(args.outpath, f"{args.report}_{args.theoreticalfilename}_.png"))
# 4. Director Confirmed Graph
print("Generating Director Confirmed Graph and Dataset...\n")
director_fig = make_director_confirmed_graph(
nbs_df,
title=args.directortitle,
source_data_export_path=str(os.path.join(args.outpath, args.directordatafilename)),
col_neo_center=NEOSERRA_COLUMNS.center,
col_neo_attribution_source=NEOSERRA_COLUMNS.milestone_attribution_source
)
director_fig.write_image(os.path.join(args.outpath, f"{args.report}_{args.directorfilename}_.png"))
print("DONE!")