python - 如何根据其值的频率将行转换为列

Question

如何在不使用客户索引的情况下将行值转换为包含购买次数的列

数据:

customer    fruits  veggies grocery
A   apple   carrot  brush
A   apple   carrot  brush
A   apple   onion   soap
A   banana  onion   soap
B   mango   onion   soap
B   mango   carrot  brush
B   banana  tomato  powder
B   banana  tomato  powder
C   apple   carrot  powder
C   mango   carrot  soap
C   mango   tomato  soap
C   banana  tomato  brush
D   banana  carrot  brush
D   banana  onion   soap
D   apple   tomato  powder
D   apple   tomato  powder

预期输出:

customer    apple   mango   banana  carrot  onion   tomato  brush   soap    powder
A   3   0   1   2   2   0   2   2   0
B   0   2   2   1   1   2   1   1   2
C   1   2   1   2   0   2   1   2   1
D   2   0   2   1   1   2   1   1   2

Answer 1

选项 1
使用set_index + stack + get_dummies:

df.set_index('customer').stack().str.get_dummies().sum(level=0)

          apple  banana  brush  carrot  mango  onion  powder  soap  tomato
customer                                                                  
A             3       1      2       2      0      2       0     2       0
B             0       2      1       1      2      1       2     1       2
C             1       1      1       2      2      0       1     2       2
D             2       2      1       1      0      1       2     1       2

---

选项 2
另一种，稍微干净一些，使用 pd.crosstab:

v = df.set_index('customer').stack()
pd.crosstab(v.index.get_level_values(0), v.values)

col_0  apple  banana  brush  carrot  mango  onion  powder  soap  tomato
row_0                                                                  
A          3       1      2       2      0      2       0     2       0
B          0       2      1       1      2      1       2     1       2
C          1       1      1       2      2      0       1     2       2
D          2       2      1       1      0      1       2     1       2

crosstab 是 pivot_table 的专门版本，非常适合此类制表操作。