Create dummy for missing values for variable in Python

Question

I have the following dataframe in:

  a
1 3
2 2
3 Nan
4 3
5 Nan

I need to recode this column so it looks like this:

  df_miss_a
1 0
2 0
3 1
4 0
5 1

I've tried:

df_miss_a = np.where(df['a'] == 'Nan', 1, 0)

and

df_miss_a = np.where(df['a'] == Nan, 1, 0)

The above outputs only 0s.

The format of the output is unimportant.

Answer 1

If you have NaNs in your column you can use pd.Series.isna():

df_miss_a = df["a"].isna().astype(int)
print(df_miss_a)

Prints:

1    0
2    0
3    1
4    0
5    1
Name: a, dtype: int64