python - 如何基于两个或多个其他变量创建 Pandas 数据框变量/列？

Question

我有一个 Pandas 数据框，例如:

Col1 Col2
A     1 
B     2
C     3

我了解如何根据 Col2 的值创建 Col3:

df['Col3'] = (df['Col2'] <= 1).astype(int)

但是......如果新列基于两个变量，如(此处为伪代码):

if Col2=1 and Col3=1 then Col4='X'
else if Col2=1 and Col3=2 then Col4='Y'
else Col4='Z'

如何实现？非常感谢

Answer 1

你可以试试双numpy.where :

df['Col4'] = np.where((df['Col2'] == 1) & (df['Col3'] == 1), 'X', 
             np.where((df['Col2'] == 1) & (df['Col3'] == 2), 'Y', 'Z'))

示例:

import pandas as pd

df = pd.DataFrame({'Col2': {0: 1, 1: 1, 2: 3}, 
                   'Col1': {0: 'A', 1: 'B', 2: 'C'}, 
                   'Col3': {0: 1, 1: 2, 2: 4}})
print (df)

  Col1  Col2  Col3
0    A     1     1
1    B     1     2
2    C     3     4

df['Col4'] = np.where( (df['Col2'] == 1) & (df['Col3'] == 1), 'X', 
             np.where((df['Col2'] == 1) & (df['Col3'] == 2), 'Y', 'Z'))

print (df)
  Col1  Col2  Col3 Col4
0    A     1     1    X
1    B     1     2    Y
2    C     3     4    Z

---

另一种解决方案 loc和 fillna用于填充 NaN 所有其他值:

df.loc[ (df['Col2'] == 1) & (df['Col3'] == 1) , 'Col4'] =  'X'
df.loc[ (df['Col2'] == 1) & (df['Col3'] == 2) , 'Col4'] =  'Y'
df['Col4'] = df['Col4'].fillna('Z')

print (df)
  Col1  Col2  Col3 Col4
0    A     1     1    X
1    B     1     2    Y
2    C     3     4    Z