Accept empty dataframes in DataFrame.to_parquet

pandas/io/parquet.py

@@ -55,7 +55,7 @@ def validate_dataframe(df):
             raise ValueError("to_parquet only supports IO with DataFrames")
 
         # must have value column names (strings only)
-        if df.columns.inferred_type not in {"string", "unicode"}:
+        if df.columns.inferred_type not in {"string", "unicode", "empty"}:
             raise ValueError("parquet must have string column names")
 
         # index level names must be strings

pandas/tests/io/test_parquet.py

@@ -471,6 +471,10 @@ 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_empty_dataframe(self, pa):
+        df = pd.DataFrame()
+        check_round_trip(df, pa)
+
 
 class TestParquetFastParquet(Base):
     @td.skip_if_no("fastparquet", min_version="0.2.1")
@@ -566,3 +570,9 @@ def test_error_on_using_partition_cols_and_partition_on(self, fp, df_full):
                     partition_on=partition_cols,
                     partition_cols=partition_cols,
                 )
+
+    def test_empty_dataframe(self, fp):
+        df = pd.DataFrame()
+        expected = df.copy()
+        expected.index.name = "index"
+        check_round_trip(df, fp, expected=expected)