diff --git a/pandas/arrays/__init__.py b/pandas/arrays/__init__.py
index b5c1c98da1c78..7302e4acf85d4 100644
--- a/pandas/arrays/__init__.py
+++ b/pandas/arrays/__init__.py
@@ -4,6 +4,41 @@
 See :ref:`extending.extension-types` for more.
 """
 
+# Explanations for the ExtensionArrays listed below:
+#
+# ArrowExtensionArray: Wraps an Apache Arrow array for high-performance data handling.
+#
+# ArrowStringArray:    A specific version for string data backed by Apache Arrow.
+#
+# BooleanArray:        Stores boolean data (True, False) but with the
+#                      ability to hold missing values (NA).
+#
+# Categorical:         For data that belongs to a fixed, finite set of
+#                      categories. Very memory efficient.
+#
+# DatetimeArray:       Handles timezone-aware or timezone-naive date and time data.
+#
+# FloatingArray:       For floating-point (decimal) numbers, with support
+#                      for missing values.
+#
+# IntegerArray:        For integer (whole) numbers, with support for missing values.
+#
+# IntervalArray:       Stores data representing intervals or ranges (e.g., 1-5, 6-10).
+#
+# NumpyExtensionArray: A wrapper around a standard NumPy array, for compatibility
+#                      within the extension system.
+#
+# PeriodArray:         For data representing regular time periods (e.g., months,
+#                      quarters, years).
+#
+# SparseArray:         Memory-efficient array for data that is mostly zero or NA.
+#
+# StringArray:         Dedicated array for handling string data, with support
+#                      for missing values.
+#
+# TimedeltaArray:      For data representing durations or differences in time
+#                      (e.g., 2 days, 5 hours).
+
 from pandas.core.arrays import (
     ArrowExtensionArray,
     ArrowStringArray,