如何基于公用日期对齐单个数据表中两个数据表的数据[重复]

Question

我有两个csv文件，从它们中我创建了一个单独的DataFrame。问题是它首先添加了“tatasteel”的数据，然后添加了“tataMotors”的数据。我想要的是按日期订购。例如，首先是Tatasteel在9:15的数据，然后是Tatamotors在9:15的数据，等等。

代码如下：

import pandas as pd
import datetime as dt
from datetime import timedelta
import os
import glob


exclude_days = [dt.datetime(2019, 1, 5), dt.datetime(2019, 1, 6), dt.datetime(2019, 1, 12), dt.datetime(2019, 1, 13), dt.datetime(2019, 1, 19), dt.datetime(2019, 1, 20),
dt.datetime(2019, 1, 26), dt.datetime(2019, 1, 27) ]
backtest_start = dt.datetime(2019, 1, 1)
backtest_end = dt.datetime(2019, 1, 2)

path = os.getcwd()
path = os.path.join(path,"2019/*")
dat=[]
data3 =[]
stock_list = glob.glob(path)
for stock in stock_list:
   rdata= pd.read_csv(stock, parse_dates=['Date'])
   dat.append(rdata)
data = pd.concat(dat, ignore_index=True)

   
curr_day = backtest_start

while curr_day < backtest_end:
   if curr_day not in exclude_days:
      day_start = dt.datetime(curr_day.year,curr_day.month,curr_day.day, 9, 15)
      day_end = dt.datetime(curr_day.year,curr_day.month,curr_day.day, 15, 15)
      data2 =  data[data['Date'].between(day_start,day_end)]
      data2 = data2.reset_index(drop=True)
      data2 = pd.DataFrame(data2)
      print(data2)         
        
  curr_day += timedelta(days=1)

Answer 1

使用sort_values:

df = df.sort_values('Date')

或者如果希望date列作为索引：

df = df.set_index('Date').sort_index()