Use fillna() and lambda function in Pandas to replace NaN values

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I'm trying to write fillna() or a lambda function in Pandas that checks if 'user_score' column is a NaN and if so, uses column's data from another DataFrame. I tried two options:

games_data['user_score'].fillna(
    genre_score[games_data['genre']]['user_score']
    if np.isnan(games_data['user_score'])
    else games_data['user_score'],
    inplace = True
)

# but here is 'ValueError: The truth value of a Series is ambiguous'

and

games_data['user_score'] = games_data.apply(
    lambda row: 
    genre_score[row['genre']]['user_score'] 
    if np.isnan(row['user_score'])
    else row['user_score'],
    axis=1
)

# but here is 'KeyError' with another column from games_data

My dataframes:

games_data

enter image description here

genre_score

enter image description here

I will be glad for any help!



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