Merge pull request #83 from MarcoGorelli/preserve-object

preserve object dtype

narwhals/_pandas_like/dataframe.py

@@ -11,9 +11,7 @@
 from narwhals._pandas_like.utils import translate_dtype
 from narwhals._pandas_like.utils import validate_dataframe_comparand
 from narwhals._pandas_like.utils import validate_indices
-from narwhals.dependencies import get_pyarrow
 from narwhals.utils import flatten
-from narwhals.utils import parse_version
 
 if TYPE_CHECKING:
     from collections.abc import Sequence
@@ -36,7 +34,7 @@ def __init__(
         implementation: str,
     ) -> None:
         self._validate_columns(dataframe.columns)
-        self._dataframe = self._convert_object_dtypes(dataframe)
+        self._dataframe = dataframe
         self._implementation = implementation
 
     def __narwhals_dataframe__(self) -> Self:
@@ -50,25 +48,6 @@ def __narwhals_namespace__(self) -> PandasNamespace:
 
         return PandasNamespace(self._implementation)
 
-    def _convert_object_dtypes(self, dataframe: Any) -> Any:
-        schema = dataframe.dtypes
-        if (schema != object).all():
-            return dataframe
-        replacements = {}
-        for col in dataframe.columns:
-            if schema[col] != object:
-                continue
-            import pandas as pd  # todo: generalise across pandas-like implementations
-
-            if parse_version(pd.__version__) >= parse_version("2.0.0"):
-                if get_pyarrow() is not None:
-                    replacements[col] = dataframe[col].astype("string[pyarrow]")
-                else:  # pragma: no cover
-                    replacements[col] = dataframe[col].astype("string[python]")
-            else:  # pragma: no cover
-                pass
-        return dataframe.assign(**replacements)
-
     def _validate_columns(self, columns: Sequence[str]) -> None:
         if len(columns) != len(set(columns)):
             counter = collections.Counter(columns)

narwhals/_pandas_like/utils.py

@@ -312,11 +312,7 @@ def translate_dtype(dtype: Any) -> DType:
     if str(dtype).startswith("datetime64"):
         # todo: different time units and time zones
         return dtypes.Datetime()
-    if dtype == "object":  # pragma: no cover
-        import pandas as pd
-
-        assert parse_version(pd.__version__) < parse_version("2.0.0")
-        # Should only happen for pandas pre 2.0.0
+    if dtype == "object":
         return dtypes.String()
     msg = f"Unknown dtype: {dtype}"  # pragma: no cover
     raise AssertionError(msg)

tests/hypothesis/test_basic_arithmetic.py

@@ -2,6 +2,7 @@
 
 import pandas as pd
 import polars as pl
+import pytest
 from hypothesis import given
 from hypothesis import strategies as st
 from numpy.testing import assert_allclose
@@ -21,6 +22,7 @@
         max_size=3,
     ),
 )  # type: ignore[misc]
+@pytest.mark.slow()
 def test_mean(
     integer: st.SearchStrategy[list[int]],
     floats: st.SearchStrategy[float],