分类数据帧从长到宽

Question

通常，当我们想在Pandas中将数据帧从长到宽转换时，我们使用pivot或pivot\u table，或unstack，或groupby，但当存在可聚合元素时，这种方法很有效。我们如何以同样的方式转换分类数据帧

例如：

d = {'Fruit':['Apple', 'Apple', 'Apple', 'Kiwi'], 
'Color1':['Red', 'Yellow', 'Red', 'Green'],
'Color2':['Red', 'Red', 'Green', 'Brown'],'Color3':[np.nan,np.nan,'Red',np.nan]}

pd.DataFrame(d)

    Fruit   Color1  Color2  Color3
0   Apple   Red     Red     NaN
1   Apple   Yellow  Red     NaN
2   Apple   Red     Green   Red
3   Kiwi    Green   Brown   NaN

应该变成这样：

d = {'Fruit':['Apple','Kiwi'], 
     'Color1':['Red','Green'],
     'Color1_1':['Yellow',np.nan],
     'Color1_2':['Red',np.nan],
     'Color2':['Red', 'Brown'],
     'Color2_1':['Red',np.nan],
     'Color2_2':['Green',np.nan],
     'Color3':[np.nan,np.nan],
     'Color3_1':[np.nan,np.nan],
     'Color3_2':['Red',np.nan]
    }

pd.DataFrame(d)

    Fruit   Color1  Color1_1    Color1_2    Color2  Color2_1    Color2_2    Color3  Color3_1    Color3_2
0   Apple   Red     Yellow      Red         Red     Red         Green       NaN     NaN         Red
1   Kiwi    Green   NaN         NaN         Brown   NaN         NaN         NaN     NaN         NaN

Answer 1

尝试使用^{}和^{}获取计数，然后将^{}作为列，然后设置列名，使用：

df = df.assign(idx=df.groupby('Fruit').cumcount()).pivot(index='Fruit',columns='idx')
print(df.set_axis([f'{x}_{y}' if y != 0 else x for x, y in df.columns], axis=1).reset_index())

输出：

   Fruit Color1 Color1_1 Color1_2 Color2 Color2_1 Color2_2 Color3 Color3_1 Color3_2
0  Apple    Red   Yellow      Red    Red      Red    Green    NaN      NaN      Red
1   Kiwi  Green      NaN      NaN  Brown      NaN      NaN    NaN      NaN      NaN

完全匹配您的输出