Pivot Dataframe With Duplicate Values

consider the below 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 labe

Solution 1:

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

pd.DataFrame.from_dict(d, orient='index')12
a    0.0NaN
b    2.05.0c4.08.0NaNNaNNaN

OR

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

  label_1    120       a  0.0NaN1       b  2.05.02c4.08.03NaNNaNNaN

Solution 2:

Another way is to use set_index and unstack:

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

Output:

label_0    12
label_1          
NaNNaNNaN
a        0.0NaN
b        2.05.0c4.08.0

Solution 3:

You can do fillna then pivot

temp.fillna('NaN').pivot(*temp.columns).T
Out[251]: 
label_0    12
label_1          
NaNNaNNaN
a          0NaN
b          25c48

Solution 4:

Seems like a straightforward pivot works:

temp.pivot(columns='label_0', index='label_1', values='values')

Output:

label_0     12
label_1         
NaNNaNNaN
a           0.0NaN
b           2.05.0c4.08.0