feat: support Date dtype in Narwhals (#341)

* feat: support Date dtype in Narwhals

* skip on old pandas versions

narwhals/__init__.py

@@ -3,6 +3,7 @@
 from narwhals.dataframe import LazyFrame
 from narwhals.dtypes import Boolean
 from narwhals.dtypes import Categorical
+from narwhals.dtypes import Date
 from narwhals.dtypes import Datetime
 from narwhals.dtypes import Float32
 from narwhals.dtypes import Float64
@@ -75,6 +76,7 @@
     "Categorical",
     "String",
     "Datetime",
+    "Date",
     "narwhalify",
     "narwhalify_method",
     "show_versions",

narwhals/_pandas_like/namespace.py

@@ -35,6 +35,7 @@ class PandasNamespace:
     Categorical = dtypes.Categorical
     String = dtypes.String
     Datetime = dtypes.Datetime
+    Date = dtypes.Date
 
     @property
     def selectors(self) -> PandasSelectorNamespace:

narwhals/_pandas_like/utils.py

@@ -409,6 +409,8 @@ def translate_dtype(dtype: Any) -> DType:
         # pyarrow-backed datetime
         # todo: different time units and time zones
         return dtypes.Datetime()
+    if str(dtype) == "date32[day][pyarrow]":
+        return dtypes.Date()
     if dtype == "object":
         return dtypes.String()
     msg = f"Unknown dtype: {dtype}"  # pragma: no cover
@@ -532,6 +534,11 @@ def reverse_translate_dtype(  # noqa: PLR0915
         if dtype_backend == "pyarrow-nullable":
             return "timestamp[ns][pyarrow]"
         return "datetime64[ns]"
+    if isinstance_or_issubclass(dtype, dtypes.Date):
+        if dtype_backend == "pyarrow-nullable":
+            return "date32[pyarrow]"
+        msg = "Date dtype only supported for pyarrow-backed data types in pandas"
+        raise NotImplementedError(msg)
     msg = f"Unknown dtype: {dtype}"  # pragma: no cover
     raise AssertionError(msg)
 

narwhals/dtypes.py

@@ -110,6 +110,8 @@ def translate_dtype(plx: Any, dtype: DType) -> Any:
         return plx.Categorical
     if dtype == Datetime:
         return plx.Datetime
+    if dtype == Date:
+        return plx.Date
     msg = f"Unknown dtype: {dtype}"  # pragma: no cover
     raise AssertionError(msg)
 
@@ -147,5 +149,7 @@ def to_narwhals_dtype(dtype: Any, *, is_polars: bool) -> DType:
         return Categorical()
     if dtype == pl.Datetime:
         return Datetime()
+    if dtype == pl.Date:
+        return Date()
     msg = f"Unexpected dtype, got: {type(dtype)}"  # pragma: no cover
     raise AssertionError(msg)

tests/series/cast_test.py

@@ -1,7 +1,13 @@
+from datetime import date
+from datetime import datetime
+
 import pandas as pd
 import polars as pl
+import pytest
+from polars.testing import assert_frame_equal
 
 import narwhals as nw
+from narwhals.utils import parse_version
 
 
 def test_cast_253() -> None:
@@ -16,3 +22,65 @@ def test_cast_253() -> None:
         nw.col("a").cast(nw.String) + "hi"
     )["a"][0]
     assert result == "1hi"
+
+
+def test_cast_date_datetime_polars() -> None:
+    # polars: date to datetime
+    dfpl = pl.DataFrame({"a": [date(2020, 1, 1), date(2020, 1, 2)]})
+    df = nw.from_native(dfpl)
+    df = df.select(nw.col("a").cast(nw.Datetime))
+    result = nw.to_native(df)
+    expected = pl.DataFrame({"a": [datetime(2020, 1, 1), datetime(2020, 1, 2)]})
+    assert_frame_equal(result, expected)
+
+    # polars: datetime to date
+    dfpl = pl.DataFrame({"a": [datetime(2020, 1, 1), datetime(2020, 1, 2)]})
+    df = nw.from_native(dfpl)
+    df = df.select(nw.col("a").cast(nw.Date))
+    result = nw.to_native(df)
+    expected = pl.DataFrame({"a": [date(2020, 1, 1), date(2020, 1, 2)]})
+    assert_frame_equal(result, expected)
+    assert df.schema == {"a": nw.Date}
+
+
+@pytest.mark.skipif(
+    parse_version(pd.__version__) < parse_version("2.0.0"),
+    reason="pyarrow dtype not available",
+)
+def test_cast_date_datetime_pandas() -> None:
+    # pandas: pyarrow date to datetime
+    dfpd = pd.DataFrame({"a": [date(2020, 1, 1), date(2020, 1, 2)]}).astype(
+        {"a": "date32[pyarrow]"}
+    )
+    df = nw.from_native(dfpd)
+    df = df.select(nw.col("a").cast(nw.Datetime))
+    result = nw.to_native(df)
+    expected = pd.DataFrame({"a": [datetime(2020, 1, 1), datetime(2020, 1, 2)]}).astype(
+        {"a": "timestamp[ns][pyarrow]"}
+    )
+    pd.testing.assert_frame_equal(result, expected)
+
+    # pandas: pyarrow datetime to date
+    dfpd = pd.DataFrame({"a": [datetime(2020, 1, 1), datetime(2020, 1, 2)]}).astype(
+        {"a": "timestamp[ns][pyarrow]"}
+    )
+    df = nw.from_native(dfpd)
+    df = df.select(nw.col("a").cast(nw.Date))
+    result = nw.to_native(df)
+    expected = pd.DataFrame({"a": [date(2020, 1, 1), date(2020, 1, 2)]}).astype(
+        {"a": "date32[pyarrow]"}
+    )
+    pd.testing.assert_frame_equal(result, expected)
+    assert df.schema == {"a": nw.Date}
+
+
+@pytest.mark.skipif(
+    parse_version(pd.__version__) < parse_version("2.0.0"),
+    reason="pyarrow dtype not available",
+)
+def test_cast_date_datetime_invalid() -> None:
+    # pandas: pyarrow datetime to date
+    dfpd = pd.DataFrame({"a": [datetime(2020, 1, 1), datetime(2020, 1, 2)]})
+    df = nw.from_native(dfpd)
+    with pytest.raises(NotImplementedError, match="pyarrow"):
+        df.select(nw.col("a").cast(nw.Date))