Completion Time Series

As an intern to do the project encountered a problem today, is the lack of individual dates of the existence of time sequence, so the need for completion date, and then search the Internet to a blog, you can solve this problem, but this blog post code exists a place where there is a small bug, so in this record, the original Bowen address: https://blog.csdn.net/leo_sheng/article/details/83316285
code corrections are:

import pandas as pd
import datetime
def load_Data():
    #加载数据
    df0 = pd.read_csv("Path/power.csv",index_col='user_id')
    df0['record_date'] = pd.to_datetime(df0['record_date'])
    return df0
 
#把datetime转成字符串
def datetime_toString(dt):
    return dt.strftime("%Y-%m-%d")
 
#把字符串转成datetime
def string_toDatetime(string):
    return datetime.strptime(string, "%Y-%m-%d")
 
#缺失值处理，插值替换
def data_Full():
    df1 = load_Data()   #加载数据
    date_start = df1.iloc[0, 0] #初始时间
    df1_date = df1['record_date'].tolist()  #数据日期转为列表
    df1_data = df1[ 'value'].tolist()   #数据值转为列表
    act = 365       #实际期望日期序列长度
    date0 = date_start
    date_s = datetime_toString(date0)   #日期转换为字符串类型，使日期可进行逻辑比较
    for j in range(0, len(df1_date)):
        if len(df1_date) < act:
            
            date_i = df1_date[j]    #顺序选取数据中日期列表里对应各日期
            date_is = datetime_toString(date_i)
            while date_is != date_s:    #如数据中日期列表与期望日期序列不相等，即存在缺失值执行while程序
                nada = (df1_data[j] + df1_data[j+1]) / 2    #计算缺失处左右相邻插值，然后对value进行补全，此处可进行相应的修改。
                adda = [date0, nada]    
                date_da = pd.DataFrame(adda).T
                date_da.columns = df1.columns
                df1 = pd.concat([df1, date_da]) #将缺失日期加入数据列表中
                date0 += datetime.timedelta(days=1) #日期加一
                date_s = datetime_toString(date0)   #日期字符串转日期时间类型
            date0 += datetime.timedelta(days=1) #日期加一
            date_s = datetime_toString(date0)   #日期字符串转日期时间类型
    df1 = df1.sort_values(by=['record_date'])
    return df1

So can you! ! ! The bloggers also thanks for sharing it!