summarize_progress.py

import pandas as pd
import json
import sys

all_df = pd.read_csv('public/data/all.csv')
arealist_df = pd.read_csv('arealist.csv')

# 各地域
status_counts = all_df.groupby('area').apply(
    lambda x: ( 
        (
            (x['status'] == 1).sum() + #完了
            (x['status'] == 2).sum() + #異常
            (x['status'] == 4).sum() + #要確認
            (x['status'] == 5).sum() + #異常対応中
            (x['status'] == 6).sum() #削除
        ) / len(x)
    ) 
).reset_index(name='progress')

# 全体
overall_progress = (
    (all_df['status'] == 1).sum()  + 
    (all_df['status'] == 2).sum()  + 
    (all_df['status'] == 4).sum()  + 
    (all_df['status'] == 5).sum()  + 
    (all_df['status'] == 6).sum()
) / len(all_df)

area_mapping = dict(zip(arealist_df['area_name'], arealist_df['area_id']))
all_areas = pd.DataFrame(area_mapping.items(), columns=['area', 'area_id'])

merged_df = all_areas.merge(status_counts, on='area', how='left')
merged_df['progress'] = merged_df['progress'].fillna(0)
merged_df = merged_df[['area_id', 'progress']].sort_values(by='area_id')

result_dict = {int(row['area_id']): round(row['progress'], 5) for _, row in merged_df.iterrows()}
result_dict['total'] = round(overall_progress, 5)

output_file_path = sys.argv[1]

with open(output_file_path, 'w', encoding='utf-8') as f:
    json.dump(result_dict, f, ensure_ascii=False, indent=2)

print(f"Results have been written to {output_file_path}")