diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index f2d9f582d8932..00f5117c9eb00 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -115,7 +115,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.api.types.is_dict_like PR07,SA01" \
         -i "pandas.api.types.is_file_like PR07,SA01" \
         -i "pandas.api.types.is_float PR01,SA01" \
-        -i "pandas.api.types.is_float_dtype SA01" \
         -i "pandas.api.types.is_hashable PR01,RT03,SA01" \
         -i "pandas.api.types.is_int64_dtype SA01" \
         -i "pandas.api.types.is_integer PR01,SA01" \
diff --git a/pandas/core/dtypes/common.py b/pandas/core/dtypes/common.py
index ff855f97a352b..b1fe9d17c67d7 100644
--- a/pandas/core/dtypes/common.py
+++ b/pandas/core/dtypes/common.py
@@ -1275,6 +1275,9 @@ def is_float_dtype(arr_or_dtype) -> bool:
     """
     Check whether the provided array or dtype is of a float dtype.
 
+    The function checks for floating-point data types, which represent real numbers
+    that may have fractional components.
+
     Parameters
     ----------
     arr_or_dtype : array-like or dtype
@@ -1285,6 +1288,15 @@ def is_float_dtype(arr_or_dtype) -> bool:
     boolean
         Whether or not the array or dtype is of a float dtype.
 
+    See Also
+    --------
+    api.types.is_numeric_dtype : Check whether the provided array or dtype is of
+        a numeric dtype.
+    api.types.is_integer_dtype : Check whether the provided array or dtype is of
+        an integer dtype.
+    api.types.is_object_dtype : Check whether an array-like or dtype is of the
+        object dtype.
+
     Examples
     --------
     >>> from pandas.api.types import is_float_dtype