ENH: Let to_feather accept index and non string column names

pandas-dev · mroeschke · Mar 6, 2023 · Mar 4, 2023 · Mar 4, 2023 · Mar 4, 2023
commit 88dec566605eb7373bfbecf29230567cb18ad5b7
diff --git a/doc/source/whatsnew/v2.1.0.rst b/doc/source/whatsnew/v2.1.0.rst
@@ -29,7 +29,7 @@ enhancement2
 Other enhancements
 ^^^^^^^^^^^^^^^^^^
 - Improve error message when setting :class:`DataFrame` with wrong number of columns through :meth:`DataFrame.isetitem` (:issue:`51701`)
--
+- Let :meth:`DataFrame.to_feather` accept a non-default :class:`Index` and non-string column names (:issue:`51787`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_210.notable_bug_fixes:

diff --git a/pandas/io/feather_format.py b/pandas/io/feather_format.py
@@ -22,10 +22,7 @@
     arrays,
     get_option,
 )
-from pandas.core.api import (
-    DataFrame,
-    RangeIndex,
-)
+from pandas.core.api import DataFrame
 from pandas.core.shared_docs import _shared_docs
 
 from pandas.io.common import get_handle
@@ -60,39 +57,6 @@ def to_feather(
     if not isinstance(df, DataFrame):
        raise ValueError("feather only support IO with DataFrames")
 
-    valid_types = {"string", "unicode"}
-
-    # validate index
-    # --------------
-
-    # validate that we have only a default index
-    # raise on anything else as we don't serialize the index
-
-    if not df.index.dtype == "int64":
-        typ = type(df.index)
-        raise ValueError(
-            f"feather does not support serializing {typ} "
-            "for the index; you can .reset_index() to make the index into column(s)"
-        )
-
-    if not df.index.equals(RangeIndex.from_range(range(len(df)))):
-        raise ValueError(
-            "feather does not support serializing a non-default index for the index; "
-            "you can .reset_index() to make the index into column(s)"
-        )
-
-    if df.index.name is not None:
-        raise ValueError(
-            "feather does not serialize index meta-data on a default index"
-        )
-
-    # validate columns
-    # ----------------
-
-    # must have value column names (strings only)
-    if df.columns.inferred_type not in valid_types:
-        raise ValueError("feather must have string column names")
-
     with get_handle(
         path, "wb", storage_options=storage_options, is_text=False
     ) as handles:

diff --git a/pandas/tests/io/test_feather.py b/pandas/tests/io/test_feather.py
@@ -34,7 +34,7 @@ def check_external_error_on_write(self, df):
 
     def check_round_trip(self, df, expected=None, write_kwargs={}, **read_kwargs):
         if expected is None:
-            expected = df
+            expected = df.copy()
 
         with tm.ensure_clean() as path:
             to_feather(df, path, **write_kwargs)
@@ -250,3 +250,7 @@ def test_read_json_nullable(self, string_storage, dtype_backend, option):
             )
 
         tm.assert_frame_equal(result, expected)
+
+    def test_int_columns_and_index(self):
+        df = pd.DataFrame({"a": [1, 2, 3]}, index=pd.Index([3, 4, 5], name="test"))
+        self.check_round_trip(df)