remove usage of hold_integer, keep .inferred_type

Author: Terji Petersen

pandas/core/dtypes/common.py

@@ -1591,13 +1591,6 @@ def infer_dtype_from_object(dtype) -> type:
     return infer_dtype_from_object(np.dtype(dtype))
 
 
-def holds_integer(value) -> bool:
-    """
-    Whether the type is an integer type.
-    """
-    return lib.infer_dtype(value) in ["integer", "mixed-integer"]
-
-
 def _validate_date_like_dtype(dtype) -> None:
     """
     Check whether the dtype is a date-like dtype. Raises an error if invalid.

pandas/core/indexes/base.py

@@ -88,7 +88,6 @@
     ensure_int64,
     ensure_object,
     ensure_platform_int,
-    holds_integer,
     is_bool_dtype,
     is_categorical_dtype,
     is_complex_dtype,
@@ -99,6 +98,7 @@
     is_float_dtype,
     is_hashable,
     is_integer,
+    is_integer_dtype,
     is_interval_dtype,
     is_iterator,
     is_list_like,
@@ -2477,7 +2477,7 @@ def holds_integer(self) -> bool:
             FutureWarning,
             stacklevel=find_stack_level(),
         )
-        return holds_integer(self._values)
+        return self.inferred_type in ["integer", "mixed-integer"]
 
     @cache_readonly
     def inferred_type(self) -> str_t:
@@ -5522,7 +5522,7 @@ def _should_fallback_to_positional(self) -> bool:
         """
         Should an integer key be treated as positional?
         """
-        return not holds_integer(self)
+        return self.inferred_type not in ["integer", "mixed-integer"]
 
     _index_shared_docs[
         "get_indexer_non_unique"

pandas/plotting/_core.py

@@ -16,8 +16,8 @@
 )
 
 from pandas.core.dtypes.common import (
-    holds_integer,
     is_integer,
+    is_integer_dtype,
     is_list_like,
 )
 from pandas.core.dtypes.generic import (
@@ -940,15 +940,15 @@ def __call__(self, *args, **kwargs):
                         f"{kind} requires either y column or 'subplots=True'"
                     )
                 if y is not None:
-                    if is_integer(y) and not holds_integer(data.columns):
+                    if is_integer(y) and not is_integer_dtype(data.columns):
                         y = data.columns[y]
                     # converted to series actually. copy to not modify
                     data = data[y].copy()
                     data.index.name = y
         elif isinstance(data, ABCDataFrame):
             data_cols = data.columns
             if x is not None:
-                if is_integer(x) and not holds_integer(data.columns):
+                if is_integer(x) and not is_integer_dtype(data.columns):
                     x = data_cols[x]
                 elif not isinstance(data[x], ABCSeries):
                     raise ValueError("x must be a label or position")
@@ -957,7 +957,7 @@ def __call__(self, *args, **kwargs):
                 # check if we have y as int or list of ints
                 int_ylist = is_list_like(y) and all(is_integer(c) for c in y)
                 int_y_arg = is_integer(y) or int_ylist
-                if int_y_arg and not holds_integer(data.columns):
+                if int_y_arg and not is_integer_dtype(data.columns):
                     y = data_cols[y]
 
                 label_kw = kwargs["label"] if "label" in kwargs else False

pandas/plotting/_matplotlib/core.py

@@ -27,7 +27,6 @@
 from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import (
-    holds_integer,
     is_categorical_dtype,
     is_extension_array_dtype,
     is_float,
@@ -1136,9 +1135,9 @@ def __init__(self, data, x, y, **kwargs) -> None:
         MPLPlot.__init__(self, data, **kwargs)
         if x is None or y is None:
             raise ValueError(self._kind + " requires an x and y column")
-        if is_integer(x) and not holds_integer(self.data.columns):
+        if is_integer(x) and not is_integer_dtype(self.data.columns):
             x = self.data.columns[x]
-        if is_integer(y) and not holds_integer(self.data.columns):
+        if is_integer(y) and not is_integer_dtype(self.data.columns):
             y = self.data.columns[y]
 
         # Scatter plot allows to plot objects data
@@ -1195,7 +1194,7 @@ def __init__(self, data, x, y, s=None, c=None, **kwargs) -> None:
         elif is_hashable(s) and s in data.columns:
             s = data[s]
         super().__init__(data, x, y, s=s, **kwargs)
-        if is_integer(c) and not holds_integer(self.data.columns):
+        if is_integer(c) and not is_integer_dtype(self.data.columns):
             c = self.data.columns[c]
         self.c = c
 
@@ -1287,7 +1286,7 @@ def _kind(self) -> Literal["hexbin"]:
 
     def __init__(self, data, x, y, C=None, **kwargs) -> None:
         super().__init__(data, x, y, **kwargs)
-        if is_integer(C) and not holds_integer(self.data.columns):
+        if is_integer(C) and not is_integer_dtype(self.data.columns):
             C = self.data.columns[C]
         self.C = C