Python 在pandas中使用多级索引连接两个数据帧
我有两个数据帧,如下所示,具有多级索引: df1: df2: 我尝试通过以下方式连接这两个数据帧:Python 在pandas中使用多级索引连接两个数据帧,python,pandas,Python,Pandas,我有两个数据帧,如下所示,具有多级索引: df1: df2: 我尝试通过以下方式连接这两个数据帧: l1=[df1,df2] pd.concat(l1) 但是我得到以下输出。为什么我得到df2数据帧的NaN?有没有一种方法可以将两个数据帧与多层次索引正确地连接在一起 Charging Capacity Total_Consumption 2010 2011 2012 2010 2011 2012 1 NaN
l1=[df1,df2]
pd.concat(l1)
但是我得到以下输出。为什么我得到df2数据帧的NaN?有没有一种方法可以将两个数据帧与多层次索引正确地连接在一起
Charging Capacity Total_Consumption
2010 2011 2012 2010 2011 2012
1 NaN NaN NaN 8544.357 5133.553 5279.884
2 NaN NaN NaN 8581.545 6091.454 4323.611
3 NaN NaN NaN 4479.319 2784.283 1948.262
4 NaN NaN NaN 5493.114 3633.187 3516.346
5 NaN NaN NaN 5582.544 3138.680 3995.311
6 NaN NaN NaN 9877.752 7798.371 8505.287
7 NaN NaN NaN 5137.488 4109.556 3301.129
8 NaN NaN NaN 13038.200 8853.721 8525.272
使用轴=1:
pd.concat([df1, df], axis=1)
输出:
Total_Consumption Charging Capacity
2010 2011 2012 2010 2011 2012
1 8544.357 5133.553 5279.884 7.989 4.752 5.801
2 8581.545 6091.454 4323.611 11.349 22.092 10.967
3 4479.319 2784.283 1948.262 6.968 6.803 9.760
4 5493.114 3633.187 3516.346 5.191 7.294 9.199
5 5582.544 3138.680 3995.311 0.201 -1.204 10.488
6 9877.752 7798.371 8505.287 14.598 13.077 17.004
7 5137.488 4109.556 3301.129 5.134 12.945 8.970
8 13038.200 8853.721 8525.272 44.680 23.607 24.395
pd.concat([df1, df], axis=1)
Total_Consumption Charging Capacity
2010 2011 2012 2010 2011 2012
1 8544.357 5133.553 5279.884 7.989 4.752 5.801
2 8581.545 6091.454 4323.611 11.349 22.092 10.967
3 4479.319 2784.283 1948.262 6.968 6.803 9.760
4 5493.114 3633.187 3516.346 5.191 7.294 9.199
5 5582.544 3138.680 3995.311 0.201 -1.204 10.488
6 9877.752 7798.371 8505.287 14.598 13.077 17.004
7 5137.488 4109.556 3301.129 5.134 12.945 8.970
8 13038.200 8853.721 8525.272 44.680 23.607 24.395