import numpy as np
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import pytest
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from pandas.compat import HAS_PYARROW
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from pandas.core.dtypes.cast import find_common_type
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import pandas as pd
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import pandas._testing as tm
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from pandas.util.version import Version
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@pytest.mark.parametrize(
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"to_concat_dtypes, result_dtype",
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[
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# same types
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([("pyarrow", pd.NA), ("pyarrow", pd.NA)], ("pyarrow", pd.NA)),
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([("pyarrow", np.nan), ("pyarrow", np.nan)], ("pyarrow", np.nan)),
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([("python", pd.NA), ("python", pd.NA)], ("python", pd.NA)),
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([("python", np.nan), ("python", np.nan)], ("python", np.nan)),
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# pyarrow preference
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([("pyarrow", pd.NA), ("python", pd.NA)], ("pyarrow", pd.NA)),
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# NA preference
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([("python", pd.NA), ("python", np.nan)], ("python", pd.NA)),
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],
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)
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def test_concat_series(request, to_concat_dtypes, result_dtype):
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if any(storage == "pyarrow" for storage, _ in to_concat_dtypes) and not HAS_PYARROW:
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pytest.skip("Could not import 'pyarrow'")
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ser_list = [
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pd.Series(["a", "b", None], dtype=pd.StringDtype(storage, na_value))
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for storage, na_value in to_concat_dtypes
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]
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result = pd.concat(ser_list, ignore_index=True)
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expected = pd.Series(
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["a", "b", None, "a", "b", None], dtype=pd.StringDtype(*result_dtype)
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)
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tm.assert_series_equal(result, expected)
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# order doesn't matter for result
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result = pd.concat(ser_list[::1], ignore_index=True)
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tm.assert_series_equal(result, expected)
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def test_concat_with_object(string_dtype_arguments):
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# _get_common_dtype cannot inspect values, so object dtype with strings still
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# results in object dtype
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result = pd.concat(
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[
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pd.Series(["a", "b", None], dtype=pd.StringDtype(*string_dtype_arguments)),
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pd.Series(["a", "b", None], dtype=object),
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]
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)
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assert result.dtype == np.dtype("object")
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def test_concat_with_numpy(string_dtype_arguments):
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# common type with a numpy string dtype always preserves the pandas string dtype
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dtype = pd.StringDtype(*string_dtype_arguments)
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assert find_common_type([dtype, np.dtype("U")]) == dtype
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assert find_common_type([np.dtype("U"), dtype]) == dtype
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assert find_common_type([dtype, np.dtype("U10")]) == dtype
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assert find_common_type([np.dtype("U10"), dtype]) == dtype
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# with any other numpy dtype -> object
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assert find_common_type([dtype, np.dtype("S")]) == np.dtype("object")
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assert find_common_type([dtype, np.dtype("int64")]) == np.dtype("object")
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if Version(np.__version__) >= Version("2"):
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assert find_common_type([dtype, np.dtypes.StringDType()]) == dtype
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assert find_common_type([np.dtypes.StringDType(), dtype]) == dtype
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