按日期顺序组织数据行 Pandas Python

Question

我将如何用 pandas 组织 csv 文件，以便它组织从最旧到最新日期的行。 data.csv 中的日期值是杂乱无章的，我可以实现哪些代码以便获得下面的预期输出？

代码：

data = pd.read_csv('data.csv')
dates= pd.to_datetime(data['Date'].to_list())

data.csv 文件内容：

Unix Timestamp,Date,Symbol,Open,High,Low,Close,Volume
1635686100,2021-10-31 13:15:00,BTCUSD,60620.0,60633.0,60565.0,60568.0,1.3977284440628714
1635686220,2021-10-31 13:17:00,BTCUSD,60638.0,60640.0,60636.0,60638.0,0.4357009185659157
1635686160,2021-10-31 13:16:00,BTCUSD,60568.0,60640.0,60568.0,60638.0,3.9771881707839967

预期输出：

Unix Timestamp,Date,Symbol,Open,High,Low,Close,Volume
1635686220,2021-10-31 13:17:00,BTCUSD,60638.0,60640.0,60636.0,60638.0,0.4357009185659157
1635686160,2021-10-31 13:16:00,BTCUSD,60568.0,60640.0,60568.0,60638.0,3.9771881707839967
1635686100,2021-10-31 13:15:00,BTCUSD,60620.0,60633.0,60565.0,60568.0,1.3977284440628714

Answer 1

先通过参数parse_dates将Date列转换为datetimes再使用DataFrame.sort_values：

data = pd.read_csv('data.csv', parse_dates=['Date'])

data = data.sort_values('Date', ascending=False, ignore_index=True)
print (data)
   Unix Timestamp                Date  Symbol     Open     High      Low  \
0      1635686220 2021-10-31 13:17:00  BTCUSD  60638.0  60640.0  60636.0   
1      1635686160 2021-10-31 13:16:00  BTCUSD  60568.0  60640.0  60568.0   
2      1635686100 2021-10-31 13:15:00  BTCUSD  60620.0  60633.0  60565.0   

     Close    Volume  
0  60638.0  0.435701  
1  60638.0  3.977188  
2  60568.0  1.397728