[FIXED] Python Pandas: How to change all the values in the column where the value contains a specific word

Issue

New to python - I am trying to change all the values in one of the columns in my data frame where the text contains "employed or Employed" word. Should i use the lambda function to loop through the column? If no, then what's the most optimal way to do this?

df = pd.DataFrame([
    ['Self-employed',1,1],
    ['Self employed contract labour',1,1],
    ['Self Employed',1,0],
    ['N/A(Self employed)',1,0],
    ['SELF EMPLOYED',1,0]
], columns=['A', 'B', 'C'])
df

Expected Output:

    ['Self Employed',1,1],
    ['Self Employed',1,1],
    ['Self Employed',1,0],
    ['Self Employed',1,0],
    ['Self Employed',1,0]

Solution

Looks like str.contains and boolean indexing should do the trick:

df.loc[df['A'].str.contains('employed', case=False), 'A'] = 'Self Employed'

output:

               A  B  C
0  Self Employed  1  1
1  Self Employed  1  1
2  Self Employed  1  0
3  Self Employed  1  0
4  Self Employed  1  0

Answered By - mozway