python - 在 pandas 中使用不同类型的 elif 创建数据框列

Question

这是 question 的扩展.

我想做一些 if/elif/else 逻辑来创建数据框列，伪代码示例:

if Col1 = 'A' and Col2 = 1 then Col3 = 'A1'
else if Col1 = 'A' and Col2 = 0 then Col3 = 'A0'
else Col3 = 'XX'

可以混合使用类型吗？我收到此错误:

TypeError: cannot compare a dtyped [int64] array with a scalar of type [bool]

Answer 1

我认为你可以使用:

df['Col3'] = 'XX'
df.loc[(df.Col1 == 'A') & (df.Col2 == 1), 'Col3'] = 'A1'
df.loc[(df.Col1 == 'A') & (df.Col2 == 0), 'Col3'] = 'A0'

带双 numpy.where :

df["Col3"] = np.where((df.Col1 == 'A') & (df.Col2 == 1) , "A1", 
             np.where((df.Col1 == 'A') & (df.Col2 == 0), 'A0', 'XX'))

示例:

df = pd.DataFrame({'Col1':['A','B','A','B'],
                   'Col2':[1,1,0,0]})

print (df)
  Col1  Col2
0    A     1
1    B     1
2    A     0
3    B     0

df['Col3'] = 'XX'
df.loc[(df.Col1 == 'A') & (df.Col2 == 1), 'Col3'] = 'A1'
df.loc[(df.Col1 == 'A') & (df.Col2 == 0), 'Col3'] = 'A0'

df["Col4"] = np.where((df.Col1 == 'A') & (df.Col2 == 1) , "A1", 
             np.where((df.Col1 == 'A') & (df.Col2 == 0), 'A0', 'XX'))

print (df)
  Col1  Col2 Col3 Col4
0    A     1   A1   A1
1    B     1   XX   XX
2    A     0   A0   A0
3    B     0   XX   XX