fix: unify description classes

src/ydata_profiling/model/pandas/var_description/counts_pandas.py

@@ -1,71 +1,53 @@
-from dataclasses import dataclass
-
 import pandas as pd
 
 from ydata_profiling.config import Settings
 from ydata_profiling.model.var_description.counts import VarCounts
 
 
-@dataclass
-class VarCountsPandas(VarCounts):
-    value_counts_without_nan: pd.Series
-    """Counts of values in the series without NaN."""
-    value_counts_index_sorted: pd.Series
-    """Sorted counts of values in the series without NaN."""
+def get_counts_pandas(config: Settings, series: pd.Series) -> VarCounts:
+    """Get a VarCounts object for a pandas series."""
+    length = len(series)
 
-    def __init__(self, config: Settings, series: pd.Series):
-        """Counts the values in a series (with and without NaN, distinct).
+    try:
+        value_counts_with_nan = series.value_counts(dropna=False)
+        _ = set(value_counts_with_nan.index)
+        hashable = True
+    except:  # noqa: E722
+        hashable = False
 
-        Args:
-            config: report Settings object
-            series: Series for which we want to calculate the values.
-            summary: series' summary
+    value_counts_without_nan = None
+    value_counts_index_sorted = None
+    if hashable:
+        value_counts_with_nan = value_counts_with_nan[value_counts_with_nan > 0]
 
-        Returns:
-            A dictionary with the count values (with and without NaN, distinct).
-        """
-        length = len(series)
+        null_index = value_counts_with_nan.index.isnull()
+        if null_index.any():
+            n_missing = value_counts_with_nan[null_index].sum()
+            value_counts_without_nan = value_counts_with_nan[~null_index]
+        else:
+            n_missing = 0
+            value_counts_without_nan = value_counts_with_nan
 
         try:
-            value_counts_with_nan = series.value_counts(dropna=False)
-            _ = set(value_counts_with_nan.index)
-            hashable = True
-        except:  # noqa: E722
-            hashable = False
-
-        value_counts_without_nan = None
-        value_counts_index_sorted = None
-        if hashable:
-            value_counts_with_nan = value_counts_with_nan[value_counts_with_nan > 0]
-
-            null_index = value_counts_with_nan.index.isnull()
-            if null_index.any():
-                n_missing = value_counts_with_nan[null_index].sum()
-                value_counts_without_nan = value_counts_with_nan[~null_index]
-            else:
-                n_missing = 0
-                value_counts_without_nan = value_counts_with_nan
-
-            try:
-                value_counts_index_sorted = value_counts_without_nan.sort_index(
-                    ascending=True
-                )
-                ordering = True
-            except TypeError:
-                ordering = False
-        else:
-            n_missing = series.isna().sum()
+            value_counts_index_sorted = value_counts_without_nan.sort_index(
+                ascending=True
+            )
+            ordering = True
+        except TypeError:
             ordering = False
-
-        super().__init__(
-            hashable=hashable,
-            value_counts_without_nan=value_counts_without_nan,
-            value_counts_index_sorted=value_counts_index_sorted,
-            ordering=ordering,
-            n_missing=n_missing,
-            n=length,
-            p_missing=series.isna().sum() / length if length > 0 else 0,
-            count=length - series.isna().sum(),
-            memory_size=series.memory_usage(deep=config.memory_deep),
-            value_counts=None,
-        )
+    else:
+        n_missing = series.isna().sum()
+        ordering = False
+
+    return VarCounts(
+        hashable=hashable,
+        value_counts_without_nan=value_counts_without_nan,
+        value_counts_index_sorted=value_counts_index_sorted,
+        ordering=ordering,
+        n_missing=n_missing,
+        n=length,
+        p_missing=series.isna().sum() / length if length > 0 else 0,
+        count=length - series.isna().sum(),
+        memory_size=series.memory_usage(deep=config.memory_deep),
+        value_counts=None,
+    )

src/ydata_profiling/model/pandas/var_description/default_pandas.py

@@ -1,55 +1,27 @@
 from __future__ import annotations
 
-from dataclasses import dataclass
-
 import pandas as pd
 
 from ydata_profiling.config import Settings
-from ydata_profiling.model.pandas.var_description.counts_pandas import VarCountsPandas
+from ydata_profiling.model.pandas.var_description.counts_pandas import get_counts_pandas
 from ydata_profiling.model.var_description.default import (
     VarDescription,
     VarDescriptionHashable,
 )
 
 
-@dataclass
-class VarDescriptionPandas(VarDescription):
-    """Default description for pandas columns."""
-
-    @classmethod
-    def from_var_counts(
-        cls, var_counts: VarCountsPandas, init_dict: dict
-    ) -> VarDescriptionPandas:
-        """Get a default description from a VarCountsPandas object."""
-        return VarDescriptionPandas(
-            n=var_counts.n,
-            count=var_counts.count,
-            n_missing=var_counts.n_missing,
-            p_missing=var_counts.p_missing,
-            hashable=var_counts.hashable,
-            memory_size=var_counts.memory_size,
-            ordering=var_counts.ordering,
-            value_counts_index_sorted=var_counts.value_counts_index_sorted,
-            value_counts_without_nan=var_counts.value_counts_without_nan,
-            var_specific=init_dict,
-        )
-
-
-@dataclass
-class VarDescriptionPandasHashable(VarDescriptionHashable):
-    """Default description for pandas columns that are hashable (common types)."""
+def get_default_pandas_description(
+    config: Settings, series: pd.Series, init_dict: dict
+) -> VarDescription | VarDescriptionHashable:
+    var_counts = get_counts_pandas(config, series)
 
-    @classmethod
-    def from_var_counts(
-        cls, var_counts: VarCountsPandas, init_dict: dict
-    ) -> VarDescriptionPandasHashable:
-        """Get a default description for a hashable column from a VarCountsPandas object."""
-        _count = var_counts.count
+    if var_counts.hashable:
+        count = var_counts.count
         value_counts = var_counts.value_counts_without_nan
         distinct_count = len(value_counts)
         unique_count = value_counts.where(value_counts == 1).count()
 
-        return VarDescriptionPandasHashable(
+        return VarDescriptionHashable(
             n=var_counts.n,
             count=var_counts.count,
             n_missing=var_counts.n_missing,
@@ -60,19 +32,11 @@ def from_var_counts(
             value_counts_index_sorted=var_counts.value_counts_index_sorted,
             value_counts_without_nan=var_counts.value_counts_without_nan,
             n_distinct=distinct_count,
-            p_distinct=distinct_count / _count if _count > 0 else 0,
-            is_unique=unique_count == _count and _count > 0,
+            p_distinct=distinct_count / count if count > 0 else 0,
+            is_unique=unique_count == count and count > 0,
             n_unique=unique_count,
-            p_unique=unique_count / _count if _count > 0 else 0,
+            p_unique=unique_count / count if count > 0 else 0,
+            value_counts=None,
             var_specific=init_dict,
-            value_counts=var_counts.value_counts,
         )
-
-
-def get_default_pandas_description(
-    config: Settings, series: pd.Series, init_dict: dict
-) -> VarDescriptionPandas | VarDescriptionPandasHashable:
-    _var_counts = VarCountsPandas(config, series)
-    if _var_counts.hashable:
-        return VarDescriptionPandasHashable.from_var_counts(_var_counts, init_dict)
-    return VarDescriptionPandas.from_var_counts(_var_counts, init_dict)
+    return VarDescription.from_var_counts(var_counts, init_dict)

src/ydata_profiling/model/var_description/counts.py

@@ -22,3 +22,6 @@ class VarCounts:
     """Sorted counts of values in the series without NaN. Sorted by counts."""
     ordering: Union[bool, list]
     memory_size: Union[int, list]
+
+    value_counts: Any
+    """Counts of values in original series type. Values as index, counts as values."""

src/ydata_profiling/model/var_description/default.py

@@ -38,6 +38,23 @@ def __iter__(self) -> Iterator:
         """To support old dict like interface."""
         return self.var_specific.__iter__()
 
+    @classmethod
+    def from_var_counts(cls, var_counts: VarCounts, init_dict: dict) -> VarDescription:
+        """Get a default description from a VarCounts object."""
+        return VarDescription(
+            n=var_counts.n,
+            count=var_counts.count,
+            n_missing=var_counts.n_missing,
+            p_missing=var_counts.p_missing,
+            hashable=var_counts.hashable,
+            memory_size=var_counts.memory_size,
+            ordering=var_counts.ordering,
+            var_specific=init_dict,
+            value_counts_index_sorted=var_counts.value_counts_index_sorted,
+            value_counts_without_nan=var_counts.value_counts_without_nan,
+            value_counts=var_counts.value_counts,
+        )
+
 
 @dataclass
 class VarDescriptionHashable(VarDescription):