Merge pull request #12 from raisadz/increase-coverage

add more coverage for dataframe

narwhals/pandas_like/utils.py

@@ -99,13 +99,16 @@ def parse_into_expr(implementation: str, into_expr: IntoPandasExpr) -> PandasExp
     from narwhals.expression import Expr
     from narwhals.pandas_like.expr import PandasExpr
     from narwhals.pandas_like.namespace import PandasNamespace
+    from narwhals.pandas_like.series import PandasSeries
 
     plx = PandasNamespace(implementation=implementation)
 
     if isinstance(into_expr, PandasExpr):
         return into_expr
     if isinstance(into_expr, Expr):
         return into_expr._call(plx)
+    if isinstance(into_expr, PandasSeries):
+        return plx._create_expr_from_series(into_expr)
     if isinstance(into_expr, str):
         return plx.col(into_expr)
     msg = f"Expected IntoExpr, got {type(into_expr)}"

narwhals/series.py

@@ -134,3 +134,9 @@ def mean(self) -> Any:
 
     def std(self) -> Any:
         return self._series.std()
+
+    def __gt__(self, other: Any) -> Series:
+        return self._series.__gt__(self._extract_native(other))  # type: ignore[no-any-return]
+
+    def __lt__(self, other: Any) -> Series:
+        return self._series.__lt__(self._extract_native(other))  # type: ignore[no-any-return]

requirements-dev.txt

@@ -1,4 +1,5 @@
 covdefaults
+modin[dask]
 pandas
 polars
 pre-commit

tests/test_common.py

@@ -1,7 +1,9 @@
 from __future__ import annotations
 
+import warnings
 from typing import Any
 
+import modin.pandas as mpd
 import numpy as np
 import pandas as pd
 import polars as pl
@@ -13,6 +15,11 @@
 df_pandas = pd.DataFrame({"a": [1, 3, 2], "b": [4, 4, 6], "z": [7.0, 8, 9]})
 df_polars = pl.DataFrame({"a": [1, 3, 2], "b": [4, 4, 6], "z": [7.0, 8, 9]})
 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 = mpd.DataFrame(
+        pd.DataFrame({"a": [1, 3, 2], "b": [4, 4, 6], "z": [7.0, 8, 9]})
+    )
 
 
 @pytest.mark.parametrize(
@@ -33,7 +40,7 @@ def test_sort(df_raw: Any) -> None:
 
 @pytest.mark.parametrize(
     "df_raw",
-    [df_pandas, df_polars, df_lazy],
+    [df_pandas, df_lazy],
 )
 def test_filter(df_raw: Any) -> None:
     df = nw.LazyFrame(df_raw)
@@ -45,7 +52,19 @@ def test_filter(df_raw: Any) -> None:
 
 @pytest.mark.parametrize(
     "df_raw",
-    [df_pandas, df_polars, df_lazy],
+    [df_pandas],
+)
+def test_filter_series(df_raw: Any) -> None:
+    df = nw.DataFrame(df_raw)
+    result = df.filter(df["a"] > 1)
+    result_native = nw.to_native(result)
+    expected = {"a": [3, 2], "b": [4, 6], "z": [8.0, 9.0]}
+    compare_dicts(result_native, expected)
+
+
+@pytest.mark.parametrize(
+    "df_raw",
+    [df_pandas, df_lazy],
 )
 def test_add(df_raw: Any) -> None:
     df = nw.LazyFrame(df_raw)
@@ -66,7 +85,7 @@ def test_add(df_raw: Any) -> None:
 
 @pytest.mark.parametrize(
     "df_raw",
-    [df_pandas, df_polars, df_lazy],
+    [df_pandas, df_lazy],
 )
 def test_double(df_raw: Any) -> None:
     df = nw.LazyFrame(df_raw)
@@ -76,7 +95,7 @@ def test_double(df_raw: Any) -> None:
     compare_dicts(result_native, expected)
 
 
-@pytest.mark.parametrize("df_raw", [df_pandas, df_polars, df_lazy])
+@pytest.mark.parametrize("df_raw", [df_pandas, df_lazy])
 def test_sumh(df_raw: Any) -> None:
     df = nw.LazyFrame(df_raw)
     result = df.with_columns(horizonal_sum=nw.sum_horizontal(nw.col("a"), nw.col("b")))
@@ -90,7 +109,7 @@ def test_sumh(df_raw: Any) -> None:
     compare_dicts(result_native, expected)
 
 
-@pytest.mark.parametrize("df_raw", [df_pandas, df_polars, df_lazy])
+@pytest.mark.parametrize("df_raw", [df_pandas, df_lazy])
 def test_sumh_literal(df_raw: Any) -> None:
     df = nw.LazyFrame(df_raw)
     result = df.with_columns(horizonal_sum=nw.sum_horizontal("a", nw.col("b")))
@@ -104,7 +123,7 @@ def test_sumh_literal(df_raw: Any) -> None:
     compare_dicts(result_native, expected)
 
 
-@pytest.mark.parametrize("df_raw", [df_pandas, df_polars, df_lazy])
+@pytest.mark.parametrize("df_raw", [df_pandas, df_lazy])
 def test_sum_all(df_raw: Any) -> None:
     df = nw.LazyFrame(df_raw)
     result = df.select(nw.all().sum())
@@ -113,7 +132,7 @@ def test_sum_all(df_raw: Any) -> None:
     compare_dicts(result_native, expected)
 
 
-@pytest.mark.parametrize("df_raw", [df_pandas, df_polars, df_lazy])
+@pytest.mark.parametrize("df_raw", [df_pandas, df_lazy])
 def test_double_selected(df_raw: Any) -> None:
     df = nw.LazyFrame(df_raw)
     result = df.select(nw.col("a", "b") * 2)
@@ -122,7 +141,7 @@ def test_double_selected(df_raw: Any) -> None:
     compare_dicts(result_native, expected)
 
 
-@pytest.mark.parametrize("df_raw", [df_pandas, df_polars, df_lazy])
+@pytest.mark.parametrize("df_raw", [df_pandas, df_lazy])
 def test_rename(df_raw: Any) -> None:
     df = nw.LazyFrame(df_raw)
     result = df.rename({"a": "x", "b": "y"})
@@ -131,7 +150,7 @@ def test_rename(df_raw: Any) -> None:
     compare_dicts(result_native, expected)
 
 
-@pytest.mark.parametrize("df_raw", [df_pandas, df_polars, df_lazy])
+@pytest.mark.parametrize("df_raw", [df_pandas, df_lazy])
 def test_join(df_raw: Any) -> None:
     df = nw.LazyFrame(df_raw)
     df_right = df.rename({"z": "z_right"})
@@ -141,15 +160,15 @@ def test_join(df_raw: Any) -> None:
     compare_dicts(result_native, expected)
 
 
-@pytest.mark.parametrize("df_raw", [df_pandas, df_polars, df_lazy])
+@pytest.mark.parametrize("df_raw", [df_pandas, df_lazy])
 def test_schema(df_raw: Any) -> None:
     df = nw.LazyFrame(df_raw)
     result = df.schema
     expected = {"a": nw.dtypes.Int64, "b": nw.dtypes.Int64, "z": nw.dtypes.Float64}
     assert result == expected
 
 
-@pytest.mark.parametrize("df_raw", [df_pandas, df_polars, df_lazy])
+@pytest.mark.parametrize("df_raw", [df_pandas, df_lazy])
 def test_columns(df_raw: Any) -> None:
     df = nw.LazyFrame(df_raw)
     result = df.columns
@@ -158,8 +177,29 @@ def test_columns(df_raw: Any) -> None:
     assert all(x == y for x, y in zip(result, expected))
 
 
+@pytest.mark.parametrize("df_raw", [df_lazy])
+def test_lazy_instantiation(df_raw: Any) -> None:
+    with pytest.raises(
+        TypeError, match="Can't instantiate DataFrame from Polars LazyFrame."
+    ):
+        _ = nw.DataFrame(df_raw).shape
+
+
+@pytest.mark.parametrize("df_raw", [df_polars, df_pandas, df_mpd])
+def test_eager_instantiation(df_raw: Any) -> None:
+    result = nw.DataFrame(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)
+
+
 def test_accepted_dataframes() -> None:
     array = np.array([[0, 4.0], [2, 5]])
+    with pytest.raises(
+        TypeError,
+        match="Expected pandas-like dataframe, Polars dataframe, or Polars lazyframe, got: <class 'numpy.ndarray'>",
+    ):
+        nw.DataFrame(array)
     with pytest.raises(
         TypeError,
         match="Expected pandas-like dataframe, Polars dataframe, or Polars lazyframe, got: <class 'numpy.ndarray'>",