diff --git a/doc/source/whatsnew/v1.0.0.rst b/doc/source/whatsnew/v1.0.0.rst
index 29060a93923eb..4f4ace502d443 100644
--- a/doc/source/whatsnew/v1.0.0.rst
+++ b/doc/source/whatsnew/v1.0.0.rst
@@ -204,6 +204,7 @@ Other enhancements
 - Roundtripping DataFrames with nullable integer or string data types to parquet
   (:meth:`~DataFrame.to_parquet` / :func:`read_parquet`) using the `'pyarrow'` engine
   now preserve those data types with pyarrow >= 1.0.0 (:issue:`20612`).
+- The ``partition_cols`` argument in :meth:`DataFrame.to_parquet` now accepts a string (:issue:`27117`)
 
 Build Changes
 ^^^^^^^^^^^^^
diff --git a/pandas/io/parquet.py b/pandas/io/parquet.py
index a044cfcdf6a01..51eac8d481231 100644
--- a/pandas/io/parquet.py
+++ b/pandas/io/parquet.py
@@ -234,7 +234,7 @@ def to_parquet(
 
         .. versionadded:: 0.24.0
 
-    partition_cols : list, optional, default None
+    partition_cols : str or list, optional, default None
         Column names by which to partition the dataset
         Columns are partitioned in the order they are given
 
@@ -243,6 +243,8 @@ def to_parquet(
     kwargs
         Additional keyword arguments passed to the engine
     """
+    if isinstance(partition_cols, str):
+        partition_cols = [partition_cols]
     impl = get_engine(engine)
     return impl.write(
         df,
diff --git a/pandas/tests/io/test_parquet.py b/pandas/tests/io/test_parquet.py
index a98c93c250070..251548e7caaab 100644
--- a/pandas/tests/io/test_parquet.py
+++ b/pandas/tests/io/test_parquet.py
@@ -499,6 +499,19 @@ def test_partition_cols_supported(self, pa, df_full):
             assert len(dataset.partitions.partition_names) == 2
             assert dataset.partitions.partition_names == set(partition_cols)
 
+    def test_partition_cols_string(self, pa, df_full):
+        # GH #27117
+        partition_cols = "bool"
+        partition_cols_list = [partition_cols]
+        df = df_full
+        with tm.ensure_clean_dir() as path:
+            df.to_parquet(path, partition_cols=partition_cols, compression=None)
+            import pyarrow.parquet as pq
+
+            dataset = pq.ParquetDataset(path, validate_schema=False)
+            assert len(dataset.partitions.partition_names) == 1
+            assert dataset.partitions.partition_names == set(partition_cols_list)
+
     def test_empty_dataframe(self, pa):
         # GH #27339
         df = pd.DataFrame()
@@ -595,6 +608,23 @@ def test_partition_cols_supported(self, fp, df_full):
             actual_partition_cols = fastparquet.ParquetFile(path, False).cats
             assert len(actual_partition_cols) == 2
 
+    def test_partition_cols_string(self, fp, df_full):
+        # GH #27117
+        partition_cols = "bool"
+        df = df_full
+        with tm.ensure_clean_dir() as path:
+            df.to_parquet(
+                path,
+                engine="fastparquet",
+                partition_cols=partition_cols,
+                compression=None,
+            )
+            assert os.path.exists(path)
+            import fastparquet  # noqa: F811
+
+            actual_partition_cols = fastparquet.ParquetFile(path, False).cats
+            assert len(actual_partition_cols) == 1
+
     def test_partition_on_supported(self, fp, df_full):
         # GH #23283
         partition_cols = ["bool", "int"]