Replace existing column with same condition for multiple columns-CodePudding

The below is my pandas dataframe, each column contains either 0 or 1. I am trying to replace the existing 'toxic' with 1 if at least one of the other columns (severe_toxic, ..., identity hate) contains 1.

I tried the below code but it gives error.

Code I tried:

# a1 - above dataframe's name
a1['toxic'] = [1 if any(a1[[severe_toxic','obscene','threat','insult','identity_hate']]) ==1]

CodePudding user response：

Use:

df['toxic'] = np.where((df[df.columns[1:]]==1).any(axis=1), 1, df['toxic'])

Input:

   toxic  severe_toxic  obscene  threat  insult  identity_hate
0      0             0        0       0       0              0
1      0             0        0       0       0              0
2      0             0        0       0       0              1
3      0             0        0       0       0              1
4      0             0        0       0       0              0

Output:

   toxic  severe_toxic  obscene  threat  insult  identity_hate
0      0             0        0       0       0              0
1      0             0        0       0       0              0
2      1             0        0       0       0              1
3      1             0        0       0       0              1
4      0             0        0       0       0              0

Setup:

df = pd.DataFrame(data={'toxic':[0]*5,
                        'severe_toxic':[0]*5,
                        'obscene':[0]*5,
                        'threat':[0]*5,
                        'insult':[0]*5,
                        'identity_hate':[0,0,1,1,0]})

CodePudding user response：

Use any from Pandas and not from Python:

cols = ['severe_toxic', 'obscene', 'threat', 'insult', 'identity_hate']
a1['toxic'] = a1[cols].any(axis=1).astype(int)