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March 9, 2023 16:49
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Perform both a normalized and regular value_counts on a columns (`col`) in a dataframe (`df`).
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| def value_counts(df: pd.DataFrame, | |
| col: str, | |
| *args, **kwargs) -> pd.DataFrame: | |
| """ | |
| For a DataFrame (`df`): display normalized (percentage) | |
| `value_counts(normalize=True)` and regular counts | |
| `value_counts()` for a given `col`. | |
| """ | |
| count = df[col].value_counts(*args, **kwargs).to_frame(name='count') | |
| perc = df[col].value_counts(normalize=True, *args, **kwargs) \ | |
| .to_frame(name='percentage') | |
| return pd.concat([count, perc], axis=1) |
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This is what it looks like when used:
