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updated docstring for data_summary func #19

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Jan 23, 2025
Merged

updated docstring for data_summary func #19

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8 changes: 3 additions & 5 deletions src/pyeda/data_summary.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,8 +4,8 @@ def get_summary_statistics(df, col = None):
"""
Generate summary statistics for specified columns or all columns if none are provided.

This function will return the important statistics (e.g. mean, min, std) for numeric columns, as well as
some key metrics (e.g. count, unique) for non-numeric columns.
This function will return the important statistics (including mean, min, max, median, mode, and range) for numeric columns, as well as
key metrics (including number of unique values, the most frequent value, and its corresponding frequency) for non-numeric columns.

Parameters
----------
Expand All @@ -18,7 +18,7 @@ def get_summary_statistics(df, col = None):
Returns
----------
pd.DataFrame
A DataFrame with summary statistics for the specified columns.
A DataFrame with summary statistics for the specified columns, including mean, min, max, median, mode, and range for numeric columns, as well as number of unique values, the most frequent value, and its corresponding frequency) for non-numeric columns.
"""
if col is None:
col = df.columns.tolist()
Expand All @@ -34,15 +34,13 @@ def get_summary_statistics(df, col = None):
"mean": df[column].mean(),
"min": df[column].min(),
"max": df[column].max(),
"std": df[column].std(),
"median": df[column].median(),
"mode": df[column].mode().iloc[0] if not df[column].mode().empty else None,
"range": df[column].max() - df[column].min(),
}

else:
summary_stats[column] = {
"unique_values": df[column].unique(),
"num_unique_values": df[column].nunique(),
"most_frequent_value": df[column].value_counts().idxmax() if not df[column].value_counts().empty else None,
"frequency_of_most_frequent_value": df[column].value_counts().max() if not df[column].value_counts().empty else None,
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3 changes: 1 addition & 2 deletions tests/test_data_summary.py
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Expand Up @@ -17,9 +17,8 @@ def test_for_all_columns(sample_df):

assert isinstance(result, pd.DataFrame)
assert "mean" in result.index
assert "std" in result.index
assert "median" in result.index
assert "unique_values" in result.index
assert "num_unique_values" in result.index
assert "most_frequent_value" in result.index
assert result.loc["mean", "numeric"] == 3
assert result.loc["most_frequent_value", "categorical"] == "a"
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