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"""Tests for dataframe detection functions."""
import numpy as np
import pytest
from sklearn._min_dependencies import dependent_packages
from sklearn.utils._dataframe import is_df_or_series, is_pandas_df, is_polars_df
from sklearn.utils._testing import _convert_container
@pytest.mark.parametrize("constructor_name", ["pyarrow", "dataframe", "polars"])
def test_is_df_or_series(constructor_name):
df = _convert_container([[1, 4, 2], [3, 3, 6]], constructor_name)
assert is_df_or_series(df)
assert not is_df_or_series(np.asarray([1, 2, 3]))
@pytest.mark.parametrize("constructor_name", ["pyarrow", "dataframe", "polars"])
def test_is_pandas_df_other_libraries(constructor_name):
df = _convert_container([[1, 4, 2], [3, 3, 6]], constructor_name)
if constructor_name in ("pyarrow", "polars"):
assert not is_pandas_df(df)
else:
assert is_pandas_df(df)
def test_is_pandas_df():
"""Check behavior of is_pandas_df when pandas is installed."""
pd = pytest.importorskip("pandas")
df = pd.DataFrame([[1, 2, 3]])
assert is_pandas_df(df)
assert not is_pandas_df(np.asarray([1, 2, 3]))
assert not is_pandas_df(1)
def test_is_pandas_df_pandas_not_installed(hide_available_pandas):
"""Check is_pandas_df when pandas is not installed."""
assert not is_pandas_df(np.asarray([1, 2, 3]))
assert not is_pandas_df(1)
@pytest.mark.parametrize(
"constructor_name, minversion",
[
("pyarrow", dependent_packages["pyarrow"][0]),
("dataframe", dependent_packages["pandas"][0]),
("polars", dependent_packages["polars"][0]),
],
)
def test_is_polars_df_other_libraries(constructor_name, minversion):
df = _convert_container(
[[1, 4, 2], [3, 3, 6]],
constructor_name,
minversion=minversion,
)
if constructor_name in ("pyarrow", "dataframe"):
assert not is_polars_df(df)
else:
assert is_polars_df(df)
def test_is_polars_df_for_duck_typed_polars_dataframe():
"""Check is_polars_df for object that looks like a polars dataframe"""
class NotAPolarsDataFrame:
def __init__(self):
self.columns = [1, 2, 3]
self.schema = "my_schema"
not_a_polars_df = NotAPolarsDataFrame()
assert not is_polars_df(not_a_polars_df)
def test_is_polars_df():
"""Check that is_polars_df return False for non-dataframe objects."""
class LooksLikePolars:
def __init__(self):
self.columns = ["a", "b"]
self.schema = ["a", "b"]
assert not is_polars_df(LooksLikePolars())
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