[FIXED] Create a new column==1 when another column is NaN

Issue

I try to create a new column displaying 1 if another column is a missing value.

I have the following dataframe

Col1	Col2
NaN	5.5
2.5	1.6
NaN	2.0

I want to get the following result :

Col1	Col2	new_col
NaN	5.5	1.0
2.5	1.6	0.0
NaN	2.0	1.0

I tried the following code :

df['new_col']=[1 if (pd.isnull(df['col1'])==True) else 0 for i in range(len(df))]

I got the following error :

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

Solution

If you want to match any missing value per row:

df['new_col'] = df.isna().any(axis=1).astype(int)

output:

   Col1  Col2  new_col
0   5.5   NaN        1
1   2.5   1.6        0
2   NaN   2.0        1

Answered By - mozway