Pandas: fill in NaN values with dictionary references another column

Question

I have a dictionary that looks like this

dict = {\'b\' : \'5\', \'c\' : \'4\'}

My dataframe looks something like this

   A  B
0          


        

Answer 1

Unfortunately, this isn't one of the options for a built-in function like pd.fillna().

Edit: Thanks for the correction. Apparently this is possible as illustrated in @Vaishali's answer.

However, you can subset the data frame first on the missing values and then apply the map with your dictionary.

df.loc[df['B'].isnull(), 'B'] = df['A'].map(dict)

Answer 2

You can map dict values inside fillna

df.B = df.B.fillna(df.A.map(dict))

print(df)

    A   B
0   a   2
1   b   5
2   c   4

Answer 3

This can be done simply

df['B'] = df['B'].fillna(df['A'].apply(lambda x: dict.get(x)))

This can work effectively for a bigger dataset as well.