diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 47a2cf93a4f89..e6c47250afaa4 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -423,7 +423,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         pandas.Categorical.ordered\
         pandas.Categorical.remove_unused_categories\
         pandas.Categorical.rename_categories\
-        pandas.CategoricalDtype\
         pandas.CategoricalDtype.categories\
         pandas.CategoricalDtype.ordered\
         pandas.CategoricalIndex.as_ordered\
diff --git a/pandas/core/dtypes/dtypes.py b/pandas/core/dtypes/dtypes.py
index 12dcd8b0d42af..10635edb5e244 100644
--- a/pandas/core/dtypes/dtypes.py
+++ b/pandas/core/dtypes/dtypes.py
@@ -157,6 +157,17 @@ class CategoricalDtype(PandasExtensionDtype, ExtensionDtype):
     """
     Type for categorical data with the categories and orderedness.
 
+    A categorical's type is fully described by
+    1. categories: a sequence of unique values and no missing values
+    2. ordered: a boolean
+    This information can be stored in a CategoricalDtype. The categories argument
+    is optional, which implies that the actual categories should be inferred from
+    whatever is present in the data when the pandas.Categorical is created.
+    The categories are assumed to be unordered by default.
+
+    A CategoricalDtype can be used in any place pandas expects a dtype. For example
+    pandas.read_csv(), pandas.DataFrame.astype(), or in the Series constructor.
+
     Parameters
     ----------
     categories : sequence, optional