Medical_code/paper_code_2/CHARLS_NL.py

import pandas as pd

years = [2011, 2013,2015, 2018, 2020]
#读取夜光数据
pollutants_data = pd.read_csv("night_light_result.csv", encoding="utf-8")
#读取CHARLS数据
CHARLS_data = pd.read_csv("Medical_code/paper_code_2/CHARLS_data_pollutants.csv")
print(CHARLS_data.info())
for year in years:
    #新增两列，分别为year的去年和前年的环境值
    # CHARLS_data[['last_year_pm2.5', "before_last_pm2.5"]]=''
    #开始筛选出year的数据
    CHARLS_data_year = CHARLS_data[CHARLS_data['wave']==year]
    #两个表合并
    table_merge = pd.merge(CHARLS_data_year, pollutants_data, left_on="city", right_on="ext_name", how='left')
    # table_merge_last.to_csv("123.csv",index=False)
    #更新CHARLS表
    CHARLS_data.loc[CHARLS_data['wave']==year, 'cur_year_nl'] = table_merge[str(year)].values
    CHARLS_data.loc[CHARLS_data['wave']==year, 'last_year_nl'] = table_merge[str(year-1)].values
    CHARLS_data.loc[CHARLS_data['wave']==year, 'before_last_nl'] = table_merge[str(year-2)].values
    print(year)
CHARLS_data.to_csv("Medical_code/paper_code_2/CHARLS_data_p_n.csv",index=False)