added see also sections

pandas-dev · Aug 8, 2024 · d71d430 · d71d430
1 parent d0cb205
commit d71d430
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diff --git a/ci/code_checks.sh b/ci/code_checks.sh
@@ -284,12 +284,9 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.api.types.is_iterator PR07,SA01" \
         -i "pandas.api.types.is_list_like SA01" \
         -i "pandas.api.types.is_named_tuple PR07,SA01" \
-        -i "pandas.api.types.is_numeric_dtype SA01" \
         -i "pandas.api.types.is_object_dtype SA01" \
-        -i "pandas.api.types.is_period_dtype SA01" \
         -i "pandas.api.types.is_re PR07,SA01" \
         -i "pandas.api.types.is_re_compilable PR07,SA01" \
-        -i "pandas.api.types.is_timedelta64_ns_dtype SA01" \
         -i "pandas.api.types.pandas_dtype PR07,RT03,SA01" \
         -i "pandas.arrays.ArrowExtensionArray PR07,SA01" \
         -i "pandas.arrays.BooleanArray SA01" \

diff --git a/pandas/core/dtypes/common.py b/pandas/core/dtypes/common.py
@@ -412,6 +412,13 @@ def is_period_dtype(arr_or_dtype) -> bool:
     boolean
         Whether or not the array-like or dtype is of the Period dtype.
 
+    See Also
+    --------
+    api.types.is_timedelta64_ns_dtype : Check whether the provided array or dtype is
+        of the timedelta64[ns] dtype.
+    api.types.is_timedelta64_dtype: Check whether an array-like or dtype
+        is of the timedelta64 dtype.
+
     Examples
     --------
     >>> from pandas.core.dtypes.common import is_period_dtype
@@ -1021,6 +1028,11 @@ def is_timedelta64_ns_dtype(arr_or_dtype) -> bool:
     boolean
         Whether or not the array or dtype is of the timedelta64[ns] dtype.
 
+    See Also
+    --------
+    api.types.is_timedelta64_dtype: Check whether an array-like or dtype
+        is of the timedelta64 dtype.
+
     Examples
     --------
     >>> from pandas.core.dtypes.common import is_timedelta64_ns_dtype
@@ -1140,6 +1152,15 @@ def is_numeric_dtype(arr_or_dtype) -> bool:
     boolean
         Whether or not the array or dtype is of a numeric dtype.
 
+    See Also
+    --------
+    api.types.is_integer_dtype: Check whether the provided array or dtype
+        is of an integer dtype.
+    api.types.is_unsigned_integer_dtype: Check whether the provided array
+        or dtype is of an unsigned integer dtype.
+    api.types.is_signed_integer_dtype: Check whether the provided array
+        or dtype is of an signed integer dtype.
+
     Examples
     --------
     >>> from pandas.api.types import is_numeric_dtype