CODEWITHSUNDEEP
pythonpandasdictionaryfillna
ric
ric

Reputation: 163

Fill missing values using a nested dictionary

Here is my sample dataframe:

df = pd.DataFrame(data=[[3, np.nan, np.nan],[5, np.nan, np.nan]], index=['country1', 'country2'], columns=[2021, 2022, 2023])

Here is my sample dictionary:

d = {'country1': {'key1': 'a', 'key2': 'assumed','key3': {2022: '10', 2023: ' 20'}}, 'country2': {'key1': 'b', 'key2': 'assumed', 'key3': {2022: '30', 2023: ' 40'}}}

I am aiming to use the dictionary d to replace the missing values in the dataframe df. I thought I'd use something like:

df.fillna(d2)

where d2 is a dictionary based on dictionary d:

d2 = {'country1': {2022: '10', 2023: ' 20'}, 'country2': {2022: '30', 2023: ' 40'}}

I don't know how to generate d2 but it doesn't work anyway.

The result would look like this:

pd.DataFrame(data=[[3, 10, 20],[5, 30, 40]], index=['country1', 'country2'], columns=[2021, 2022, 2023])

Upvotes: 3

Views: 647

Answers (2)

Shubham Sharma
Shubham Sharma

Reputation: 71687

We can still use fillna but before that we have to normalize/transform the dictionary in a format which is suitable for fillna

df.T.fillna({k: v['key3'] for k, v in d.items()}).T

Result

         2021 2022 2023
country1  3.0   10   20
country2  5.0   30   40

Upvotes: 3

OD1995
OD1995

Reputation: 1777

Rather than using df.fillna(d2), it looks like the best way of achieving this would be the following:

for country,country_dict in d.items():
    for year,value in country_dict['key3'].items():
        df.loc[country,year] = value

Upvotes: 1

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