如何按行将两个系列附加到数据帧中 [英] How to append two series into a dataframe Row wise

问题描述

我有两个系列

maxRow
Out[160]: 
var#0         2.175999
var#1         1.016451
var#2         0.705303
var#3         1.842707
var#4         1.196601
var#5         2.162564
var#6         1.350877
var#7         0.453014
var#8         2.144554
obj#0    445537.407762
Name: 9, dtype: float64

minRow
Out[161]: 
var#0        2.593331
var#1        1.990545
var#2        2.011221
var#3        1.349357
var#4        2.808741
var#5        0.890439
var#6        1.275528
var#7        1.658743
var#8        2.343061
obj#0    51386.375391
Name: 10, dtype: float64

我想做的是将它们按行结合起来.

What I would like to do is combine them row-wise.

因此第一行将从 2.175999 变为 445537.407762.

Thus the first row will go from 2.175999 to 445537.407762.

下一行将从 2.593331 变为 5.1386.375391.

The next row will go from 2.593331 to 5.1386.375391.

我提前知道系列长度将保持一致.我试图找到这个，但只能找到按列附加的示例.

I know ahead of time that the series length will be consistent. I tried finding this but could only find examples of appending column-wise.

谢谢！

推荐答案

你可以试试 concat 和 T:

You can try concat and T:

print pd.concat([maxRow,minRow], axis=1).T

       var#0     var#1     var#2     var#3     var#4     var#5     var#6  \
9   2.175999  1.016451  0.705303  1.842707  1.196601  2.162564  1.350877   
10  2.593331  1.990545  2.011221  1.349357  2.808741  0.890439  1.275528   

       var#7     var#8          obj#0  
9   0.453014  2.144554  445537.407762  
10  1.658743  2.343061   51386.375391  

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