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⚡️ Speed up function apply_function by 1,957% #71

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⚡️ Speed up function apply_function by 1,957% #71

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10 changes: 5 additions & 5 deletions src/numpy_pandas/dataframe_operations.py
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Original file line number Diff line number Diff line change
Expand Up @@ -66,14 +66,17 @@ def pivot_table(

def agg_func(values):
return sum(values) / len(values)

elif aggfunc == "sum":

def agg_func(values):
return sum(values)

elif aggfunc == "count":

def agg_func(values):
return len(values)

else:
raise ValueError(f"Unsupported aggregation function: {aggfunc}")
grouped_data = {}
Expand All @@ -97,11 +100,8 @@ def agg_func(values):


def apply_function(df: pd.DataFrame, column: str, func: Callable) -> List[Any]:
result = []
for i in range(len(df)):
value = df.iloc[i][column]
result.append(func(value))
return result
# Use vectorized map for better performance
return list(df[column].map(func))


def fillna(df: pd.DataFrame, column: str, value: Any) -> pd.DataFrame:
Expand Down