Question

我正在进行不同的查询，我从中获得3个不同的列（date_1，date_2，date_3）。我需要在一个Dataframe中使用它们，所以我使用concat函数。我得到了这个：

resultado = pd.concat([date_1, date_2, date_3], axis=1)

     date_1            date_2            date_3
01/01/2009 0:00  01/01/2009 00:00   01/01/2009 0:00
01/01/2009 0:10  01/01/2009 00:10   01/01/2009 0:10
01/01/2009 0:20  01/01/2009 00:20   01/01/2009 0:30
01/01/2009 0:30  01/01/2009 00:30   01/01/2009 0:40
01/01/2009 0:40  01/01/2009 00:50   01/01/2009 0:50
01/01/2009 0:50               NaT               NaT

但我想要/需要的是这样的。根据索引

添加列值

     date_1            date_2            date_3
01/01/2009 0:00  01/01/2009 00:000  01/01/2009 0:00
01/01/2009 0:10  01/01/2009 00:10   01/01/2009 0:10
01/01/2009 0:20  01/01/2009 00:20               NaT
01/01/2009 0:30  01/01/2009 00:30   01/01/2009 0:30
01/01/2009 0:40               NaT   01/01/2009 0:40
01/01/2009 0:50  01/01/2009 00:50   01/01/2009 0:50

Answer 1

您可以按DatetimeIndex：

对齐数据

#get all columns in list
sers = [date_1['date_1'], date_2['date_2'], date_3['date_3']]
#convert data to datetime
sers = [pd.to_datetime(x) for x in sers]
#create DatetimeIndex for align Series, remove NaNs rows and last remove Index
resultado = pd.concat([x.to_frame().set_index(x) for x in sers], axis=1)
resultado = resultado.dropna(how='all').reset_index(drop=True)
print (resultado)
               date_1              date_2              date_3
0 2009-01-01 00:00:00 2009-01-01 00:00:00 2009-01-01 00:00:00
1 2009-01-01 00:10:00 2009-01-01 00:10:00 2009-01-01 00:10:00
2 2009-01-01 00:20:00 2009-01-01 00:20:00                 NaT
3 2009-01-01 00:30:00 2009-01-01 00:30:00 2009-01-01 00:30:00
4 2009-01-01 00:40:00                 NaT 2009-01-01 00:40:00
5 2009-01-01 00:50:00 2009-01-01 00:50:00 2009-01-01 00:50:00

使用pandas为要索引的列添加值

1 个答案: