How to replace all non-NaN entries of a dataframe with 1 and all NaN with 0

Question

I have a dataframe with 71 columns and 30597 rows. I want to replace all non-nan entries with 1 and the nan values with 0.

Initially I tried for-loop on each value of th

Answer 1

I'd advise making a new column rather than just replacing. You can always delete the previous column if necessary but its always helpful to have a source for a column populated via an operation on another.

e.g. if df['col1'] is the existing column

df['col2'] = df['col1'].apply(lambda x: 1 if not pd.isnull(x) else np.nan)

where col2 is the new column. Should also work if col2 has string entries.