如何在pandas中互相替换多列

Question

现在，我正在做一个分析项目。实际上，我发现有些行数据混乱了。像那样：

  Data in 'Direction' column should be in 'Size' column

  Data in 'Size' column should be in 'Floor' column

  Data in 'Renovation' column should be in 'Direction' 

结果，我需要修改它，即我修改'Direction'和'Renovation'，如下所示：

direction = modify_house.Renovation
modify_house.loc[:, 'Direction'] = direction

但是，它会引发错误警告：

/anaconda3/lib/python3.6/site-packages/pandas/core/indexing.py:543: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

那么，如何解决呢？或者在正确的地方制作这些数据的任何方法？谢谢！

Answer 1

使用qazxsw poi by dictionary with new和new column names：

rename

编辑：如果想要创建新列或覆盖现有列使用

modify_house= pd.DataFrame({'A':list('abcdef'),
                           'Size':[4,5,4,5,5,4],
                           'Direction':[7,8,9,4,2,3],
                           'Renovation':[1,3,5,7,1,0],
                           'E':[5,3,6,9,2,4],
                           'F':list('aaabbb')})

print (modify_house)
   A  Size  Direction  Renovation  E  F
0  a     4          7           1  5  a
1  b     5          8           3  3  a
2  c     4          9           5  6  a
3  d     5          4           7  9  b
4  e     5          2           1  2  b
5  f     4          3           0  4  b

d = {'Direction':'Size', 'Size':'Floor','Renovation':'Direction'}
modify_house = modify_house.rename(columns=d)
print (modify_house)
   A  Floor  Size  Direction  E  F
0  a      4     7          1  5  a
1  b      5     8          3  3  a
2  c      4     9          5  6  a
3  d      5     4          7  9  b
4  e      5     2          1  2  b
5  f      4     3          0  4  b

：

assign