Resolved: Using lamda to compare two columns

Question:

My dataframe is like this: df = pd.DataFrame({'A': [1,2,3], 'B': [1,4,5]})
If column A has the same value as column B, output 1, else 0.
I want to output like this:
I figured out df['is_equal'] = np.where((df['A'] == df['B']), 1, 0) worked fine.
But I want to use lambda here because I used a similar line in another case before. df['is_equals'] = df.apply(lambda x: 1 if df['A']==1 else 0, axis=1) won’t work. It threw the error ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all(). Why did this error happen and how can I fix the code.
Thank you in advance.

Answer:

I also agree with DYZ’s opinion. But if you want to use .apply anyway, I can suggest something like this.

If you have better answer, please add a comment about this, thank you!