具有重复值的数据透视表 [英] pivot dataframe with duplicate values

问题描述

考虑以下pd.DataFrame

temp = pd.DataFrame({'label_0':[1,1,1,2,2,2],'label_1':['a','b','c',np.nan,'c','b'], 'values':[0,2,4,np.nan,8,5]})

print(temp)
        label_0 label_1 values
    0   1           a   0.0
    1   1           b   2.0
    2   1           c   4.0
    3   2          NaN  NaN
    4   2           c   8.0
    5   2           b   5.0

我想要的输出是

     label_1    1   2
  0     a      0.0  NaN
  1     b      2.0  5.0
  2     c      4.0  8.0
  3     NaN    NaN  NaN

我尝试了pd.pivot并与pd.gropuby纠缠不清，但由于条目重复而无法获得所需的输出.任何最感激的帮助.

I have tried pd.pivot and wrangling around with pd.gropuby but cannot get to the desired output due to duplicate entries. any help most appreciated.

推荐答案

d = {}
for _0, _1, v in zip(*map(temp.get, temp)):
    d.setdefault(_1, {})[_0] = v

pd.DataFrame.from_dict(d, orient='index')

       1    2
a    0.0  NaN
b    2.0  5.0
c    4.0  8.0
NaN  NaN  NaN

OR

pd.DataFrame.from_dict(d, orient='index').rename_axis('label_1').reset_index()

  label_1    1    2
0       a  0.0  NaN
1       b  2.0  5.0
2       c  4.0  8.0
3     NaN  NaN  NaN

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