How to wrap cell value in a dict maintaining value without using apply

Question

I have a Pandas dataframe with a colum with some string and some NaN values.

df['column'] = ['a', 'b', NaN, 'c']

What I want to achieve is to transform the value in dicts, maintaining the original value:

df['column'] = [{'key': 'a'}, {'key': 'b'} , {'key': None}, {'key': 'c'}]

I successfully got it with an apply:

df['column'] = df['column'].apply(lambda value: {"value": None} if type(value) == pd._libs.missing.NAType or pd.isna(value) or pd.isnull(value) or value == '' else {"value": value})

But i'd like to reach the same result using the vectorized approach if possibile.

Answer 1

Vectorization is not possible since you are using complex object types like dictionaries having said that here is a slightly more efficient and concise approach than apply:

df['column'].replace(['', np.nan], None).map(lambda k: {'key': k})

Result

0     {'key': 'a'}
1     {'key': 'b'}
2    {'key': None}
3     {'key': 'c'}
Name: column, dtype: object