finish updates

dataprofiler/profilers/numerical_column_stats.py

@@ -1924,6 +1924,10 @@ def _get_skewness(
         ):
             return
 
+        if self._greater_than_64_bit and type(df_series) is pd.Series:
+            df_series = df_series.to_numpy(dtype=float)
+        else:
+            df_series = pl.from_pandas(df_series, nan_to_null=False)
         batch_biased_skewness = profiler_utils.biased_skew(df_series)
         subset_properties["biased_skewness"] = batch_biased_skewness
         batch_count = subset_properties["match_count"]
@@ -1968,6 +1972,10 @@ def _get_kurtosis(
         ):
             return
 
+        if self._greater_than_64_bit and type(df_series) is pd.Series:
+            df_series = df_series.to_numpy(dtype=float)
+        else:
+            df_series = pl.from_pandas(df_series, nan_to_null=False)
         batch_biased_kurtosis = profiler_utils.biased_kurt(df_series)
         subset_properties["biased_kurtosis"] = batch_biased_kurtosis
         batch_count = subset_properties["match_count"]

dataprofiler/profilers/profiler_utils.py

@@ -29,7 +29,8 @@
 import polars as pl
 import psutil
 import scipy
-from pandas import DataFrame, Series
+from pandas import DataFrame
+from polars import Series
 
 from ..labelers.data_labelers import DataLabeler
 
@@ -321,7 +322,7 @@ def add_nested_dictionaries(first_dict: dict, second_dict: dict) -> dict:
     return merged_dict
 
 
-def biased_skew(df_series: Series) -> np.float64:
+def biased_skew(df_series: Series | np.ndarray) -> np.float64:
     """
     Calculate the biased estimator for skewness of the given data.
 
@@ -332,7 +333,6 @@ def biased_skew(df_series: Series) -> np.float64:
     :return: biased skewness
     :rtype: np.float64
     """
-    df_series = pl.from_pandas(df_series, nan_to_null=False)
     n = len(df_series)
     if n < 1:
         return np.float64(np.nan)
@@ -360,7 +360,7 @@ def biased_skew(df_series: Series) -> np.float64:
     return skew
 
 
-def biased_kurt(df_series: Series) -> np.float64:
+def biased_kurt(df_series: Series | np.ndarray) -> np.float64:
     """
     Calculate the biased estimator for kurtosis of the given data.
 
@@ -371,7 +371,6 @@ def biased_kurt(df_series: Series) -> np.float64:
     :return: biased kurtosis
     :rtype: np.float64
     """
-    df_series = pl.from_pandas(df_series, nan_to_null=False)
     n = len(df_series)
     if n < 1:
         return np.float64(np.nan)
@@ -678,6 +677,8 @@ def get_memory_size(data: list | np.ndarray | DataFrame, unit: str = "M") -> flo
     :type unit: string
     :return: memory size of the input data
     """
+    if type(data) is DataFrame:
+        data = pl.from_pandas(data)
     unit_map: dict = collections.defaultdict(B=0, K=1, M=2, G=3)
     if unit not in unit_map:
         raise ValueError(