Merge branch 'main' of github.com:MarcoGorelli/narwhals

narwhals/dataframe.py

@@ -172,7 +172,9 @@ def __init__(
         elif (mpd := get_modin()) is not None and isinstance(df, mpd.DataFrame):
             self._dataframe = PandasDataFrame(df, implementation="modin")
             self._implementation = "modin"
-        elif (cudf := get_cudf()) is not None and isinstance(df, cudf.DataFrame):
+        elif (cudf := get_cudf()) is not None and isinstance(
+            df, cudf.DataFrame
+        ):  # pragma: no cover
             self._dataframe = PandasDataFrame(df, implementation="cudf")
             self._implementation = "cudf"
         else:
@@ -220,7 +222,9 @@ def __init__(
         elif (mpd := get_modin()) is not None and isinstance(df, mpd.DataFrame):
             self._dataframe = PandasDataFrame(df, implementation="modin")
             self._implementation = "modin"
-        elif (cudf := get_cudf()) is not None and isinstance(df, cudf.DataFrame):
+        elif (cudf := get_cudf()) is not None and isinstance(
+            df, cudf.DataFrame
+        ):  # pragma: no cover
             self._dataframe = PandasDataFrame(df, implementation="cudf")
             self._implementation = "cudf"
         else:

narwhals/pandas_like/dataframe.py

@@ -232,4 +232,8 @@ def to_numpy(self) -> Any:
         return self._dataframe.to_numpy()
 
     def to_pandas(self) -> Any:
-        return self._dataframe
+        if self._implementation == "pandas":
+            return self._dataframe
+        if self._implementation == "modin":
+            return self._dataframe._to_pandas()
+        return self._dataframe.to_pandas()

tests/test_common.py

@@ -3,6 +3,7 @@
 import warnings
 from typing import Any
 
+import modin.pandas as mpd
 import numpy as np
 import pandas as pd
 import polars as pl
@@ -16,7 +17,7 @@
 df_lazy = pl.LazyFrame({"a": [1, 3, 2], "b": [4, 4, 6], "z": [7.0, 8, 9]})
 with warnings.catch_warnings():
     warnings.filterwarnings("ignore", category=UserWarning)
-    df_mpd = pd.DataFrame(
+    df_mpd = mpd.DataFrame(
         pd.DataFrame({"a": [1, 3, 2], "b": [4, 4, 6], "z": [7.0, 8, 9]})
     )
 
@@ -184,12 +185,19 @@ def test_columns(df_raw: Any) -> None:
     df = nw.LazyFrame(df_raw)
     result = df.columns
     expected = ["a", "b", "z"]
-    assert len(result) == len(expected)
-    assert all(x == y for x, y in zip(result, expected))
+    assert result == expected
 
 
-@pytest.mark.parametrize("df_raw", [df_lazy])
+@pytest.mark.parametrize("df_raw", [df_polars, df_pandas, df_mpd, df_lazy])
 def test_lazy_instantiation(df_raw: Any) -> None:
+    result = nw.LazyFrame(df_raw)
+    result_native = nw.to_native(result)
+    expected = {"a": [1, 3, 2], "b": [4, 4, 6], "z": [7.0, 8, 9]}
+    compare_dicts(result_native, expected)
+
+
+@pytest.mark.parametrize("df_raw", [df_lazy])
+def test_lazy_instantiation_error(df_raw: Any) -> None:
     with pytest.raises(
         TypeError, match="Can't instantiate DataFrame from Polars LazyFrame."
     ):
@@ -216,3 +224,24 @@ def test_accepted_dataframes() -> None:
         match="Expected pandas-like dataframe, Polars dataframe, or Polars lazyframe, got: <class 'numpy.ndarray'>",
     ):
         nw.LazyFrame(array)
+
+
+@pytest.mark.parametrize("df_raw", [df_polars, df_pandas, df_mpd])
+def test_convert_pandas(df_raw: Any) -> None:
+    result = nw.DataFrame(df_raw).to_pandas()
+    expected = pd.DataFrame({"a": [1, 3, 2], "b": [4, 4, 6], "z": [7.0, 8, 9]})
+    pd.testing.assert_frame_equal(result, expected)
+
+
+@pytest.mark.parametrize("df_raw", [df_polars, df_pandas, df_mpd])
+def test_convert_numpy(df_raw: Any) -> None:
+    result = nw.DataFrame(df_raw).to_numpy()
+    expected = np.array([[1, 3, 2], [4, 4, 6], [7.0, 8, 9]]).T
+    np.testing.assert_array_equal(result, expected)
+
+
+@pytest.mark.parametrize("df_raw", [df_polars, df_pandas, df_mpd])
+def test_shape(df_raw: Any) -> None:
+    result = nw.DataFrame(df_raw).shape
+    expected = (3, 3)
+    assert result == expected