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⚡️ Speed up function drop_duplicates by 485% #4

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⚡️ Speed up function drop_duplicates by 485% #4

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15 changes: 5 additions & 10 deletions src/numpy_pandas/dataframe_operations.py
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Original file line number Diff line number Diff line change
Expand Up @@ -113,16 +113,11 @@ def fillna(df: pd.DataFrame, column: str, value: Any) -> pd.DataFrame:


def drop_duplicates(df: pd.DataFrame, subset: List[str] = None) -> pd.DataFrame:
if subset is None:
subset = df.columns.tolist()
seen = set()
keep_indices = []
for i in range(len(df)):
values = tuple(df.iloc[i][col] for col in subset)
if values not in seen:
seen.add(values)
keep_indices.append(i)
return df.iloc[keep_indices].reset_index(drop=True)
"""
Drops duplicate rows from the DataFrame based on the provided subset of columns.
"""
# Use pandas built-in drop_duplicates, which is optimized for performance
return df.drop_duplicates(subset=subset).reset_index(drop=True)


def sort_values(df: pd.DataFrame, by: str, ascending: bool = True) -> pd.DataFrame:
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