diff --git a/doc/source/whatsnew/v0.24.0.txt b/doc/source/whatsnew/v0.24.0.txt
index d836ef3441e89..ec5b496278184 100644
--- a/doc/source/whatsnew/v0.24.0.txt
+++ b/doc/source/whatsnew/v0.24.0.txt
@@ -239,6 +239,7 @@ Other Enhancements
 - :meth:`Timestamp.tz_localize`, :meth:`DatetimeIndex.tz_localize`, and :meth:`Series.tz_localize` have gained the ``nonexistent`` argument for alternative handling of nonexistent times. See :ref:`timeseries.timezone_nonexistent` (:issue:`8917`)
 - :meth:`read_excel()` now accepts ``usecols`` as a list of column names or callable (:issue:`18273`)
 - :meth:`MultiIndex.to_flat_index` has been added to flatten multiple levels into a single-level :class:`Index` object.
+- :meth:`DataFrame.to_stata` and :class:` pandas.io.stata.StataWriter117` can write mixed sting columns to Stata strl format (:issue:`23633`)
 
 .. _whatsnew_0240.api_breaking:
 
diff --git a/pandas/io/stata.py b/pandas/io/stata.py
index 66e996075f1ed..215391bbf217a 100644
--- a/pandas/io/stata.py
+++ b/pandas/io/stata.py
@@ -2558,6 +2558,8 @@ def generate_table(self):
         for o, (idx, row) in enumerate(selected.iterrows()):
             for j, (col, v) in enumerate(col_index):
                 val = row[col]
+                # Allow columns with mixed str and None (GH 23633)
+                val = '' if val is None else val
                 key = gso_table.get(val, None)
                 if key is None:
                     # Stata prefers human numbers
diff --git a/pandas/tests/io/test_stata.py b/pandas/tests/io/test_stata.py
index c6b6f6cab9ddd..47293e8765d26 100644
--- a/pandas/tests/io/test_stata.py
+++ b/pandas/tests/io/test_stata.py
@@ -1505,3 +1505,20 @@ def test_unicode_dta_118(self):
         expected = pd.DataFrame(values, columns=columns)
 
         tm.assert_frame_equal(unicode_df, expected)
+
+    def test_mixed_string_strl(self):
+        # GH 23633
+        output = [
+            {'mixed': 'string' * 500,
+             'number': 0},
+            {'mixed': None,
+             'number': 1}
+        ]
+
+        output = pd.DataFrame(output)
+        with tm.ensure_clean() as path:
+            output.to_stata(path, write_index=False, version=117)
+            reread = read_stata(path)
+            expected = output.fillna('')
+            expected.number = expected.number.astype('int32')
+            tm.assert_frame_equal(reread, expected)