如何根据条件在熊猫数据框的多列上分配值

Question

I have a dtaframe df as below

df = pd.DataFrame({ 
  'A': [20,30,40,-50,60,-70 ], 
  'B': [21, -19, 20, 18, 17, -21], 
  'C': [1,12,-13,14,15,16], 
  'D': [-88, 92, 9, 70, -6, 78]})

I want every value on column ['C','D'] to be zero where the value is between -10 and 10, rest of the values should remain same.

is there something similar to data.series.between , which can be applied to a data frame df[(df[['C','D']].between(-10,10,inclusive=True)]=0

output should be :

    A   B   C   D
0  20  21   0 -88
1  30 -19  12  92
2  40  20 -13   0
3 -50  18  14  70
4  60  17  15   0
5 -70 -21  16  78

Answer 1

You can use df.mask() here after comparing by df.ge and df.le :

df[['C','D']]=df[['C','D']].mask(df[['C','D']].ge(-10)&df[['C','D']].le(10),0)

Or np.where() :

df[['C','D']]=np.where(df[['C','D']].ge(-10)&df[['C','D']].le(10),0,df[['C','D']])

---

    A   B   C   D
0  20  21   0 -88
1  30 -19  12  92
2  40  20 -13   0
3 -50  18  14  70
4  60  17  15   0
5 -70 -21  16  78