Question

我有以下数据框：

df1  = pd.DataFrame.from_dict({'A':[3,5,1,7], 'DateTime' : pd.date_range("11:00", "14:00", freq="60min")}).set_index('DateTime')
df2  = pd.DataFrame.from_dict({'B':[13,15,1,17], 'DateTime' : pd.date_range("12:00", "15:00", freq="60min")}).set_index('DateTime')

我正在尝试以下方法：

pd.concat([df1, df2], join='outer')
                       A     B
DateTime                      
2017-04-19 11:00:00  3.0   NaN
2017-04-19 12:00:00  5.0   NaN
2017-04-19 13:00:00  1.0   NaN
2017-04-19 14:00:00  7.0   NaN
2017-04-19 12:00:00  NaN  13.0
2017-04-19 13:00:00  NaN  15.0
2017-04-19 14:00:00  NaN   1.0
2017-04-19 15:00:00  NaN  17.0

如何获得以下内容：

                       A     B
DateTime                      
2017-04-19 11:00:00  3.0   NaN
2017-04-19 12:00:00  5.0   13.0
2017-04-19 13:00:00  1.0   15.0
2017-04-19 14:00:00  7.0   1.0
2017-04-19 15:00:00  NaN   17.0

Answer 1

您需要将轴设置为1.

pd.concat([df1, df2], join='outer', axis=1)


                       A     B
DateTime                      
2017-04-19 11:00:00  3.0   NaN
2017-04-19 12:00:00  5.0  13.0
2017-04-19 13:00:00  1.0  15.0
2017-04-19 14:00:00  7.0   1.0
2017-04-19 15:00:00  NaN  17.0

查看pandas数据帧

1 个答案: