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| 1 | ###################################################################################################### | |
| 2 | data = pd.read_csv('data.csv')
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| 3 | ||
| 4 | data_grouped = data.groupby('income_type')['total_income'].mean()
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| 5 | ||
| 6 | def func(row): | |
| 7 | if pd.isna(row['total_income']): | |
| 8 | return data_grouped.loc[row['income_type']] | |
| 9 | return row['total_income'] | |
| 10 | ||
| 11 | data['total_income'] = data.apply(func, axis=1) | |
| 12 | ||
| 13 | ###################################################################################################### | |
| 14 | ||
| 15 | data = pd.read_csv('data.csv')
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| 16 | ||
| 17 | data_transformed = data.groupby('income_type')['total_income'].transform('mean')
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| 18 | ||
| 19 | data['total_income'] = data['total_income'].fillna(data_transformed) | |
| 20 | ||
| 21 | ###################################################################################################### | |
| 22 | ||
| 23 | data = pd.read_csv('data.csv')
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| 24 | ||
| 25 | data['total_income'] = data.groupby('income_type')['total_income'].apply(lambda s: s.fillna(s.mean()))
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| 26 | ###################################################################################################### |
