具有重复值的透视数据帧

2024-10-04 01:26:27 发布

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考虑下面的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

我试过pd.pivotpd.gropuby争吵,但由于重复条目,无法获得所需的输出。非常感谢您的帮助


Tags: dataframenp条目nantemplabelpdpivot
3条回答

你可以做fillna然后pivot

temp.fillna('NaN').pivot(*temp.columns).T
Out[251]: 
label_0    1    2
label_1          
NaN      NaN  NaN
a          0  NaN
b          2    5
c          4    8

另一种方法是使用set\ u index和unstack:

temp.set_index(['label_0','label_1'])['values'].unstack(0)

输出:

label_0    1    2
label_1          
NaN      NaN  NaN
a        0.0  NaN
b        2.0  5.0
c        4.0  8.0
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

或者

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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