import numpy as np import pytest import pandas as pd import pandas._testing as tm @pytest.mark.parametrize( "to_concat_dtypes, result_dtype", [ (["Int64", "Int64"], "Int64"), (["UInt64", "UInt64"], "UInt64"), (["Int8", "Int8"], "Int8"), (["Int8", "Int16"], "Int16"), (["UInt8", "Int8"], "Int16"), (["Int32", "UInt32"], "Int64"), (["Int64", "UInt64"], "Float64"), (["Int64", "boolean"], "Int64"), (["UInt8", "boolean"], "UInt8"), ], ) def test_concat_series(to_concat_dtypes, result_dtype): result = pd.concat([pd.Series([0, 1, pd.NA], dtype=t) for t in to_concat_dtypes]) expected = pd.concat([pd.Series([0, 1, pd.NA], dtype=object)] * 2).astype( result_dtype ) tm.assert_series_equal(result, expected) # order doesn't matter for result result = pd.concat( [pd.Series([0, 1, pd.NA], dtype=t) for t in to_concat_dtypes[::-1]] ) expected = pd.concat([pd.Series([0, 1, pd.NA], dtype=object)] * 2).astype( result_dtype ) tm.assert_series_equal(result, expected) @pytest.mark.parametrize( "to_concat_dtypes, result_dtype", [ (["Int64", "int64"], "Int64"), (["UInt64", "uint64"], "UInt64"), (["Int8", "int8"], "Int8"), (["Int8", "int16"], "Int16"), (["UInt8", "int8"], "Int16"), (["Int32", "uint32"], "Int64"), (["Int64", "uint64"], "Float64"), (["Int64", "bool"], "Int64"), (["UInt8", "bool"], "UInt8"), ], ) def test_concat_series_with_numpy(to_concat_dtypes, result_dtype): s1 = pd.Series([0, 1, pd.NA], dtype=to_concat_dtypes[0]) s2 = pd.Series(np.array([0, 1], dtype=to_concat_dtypes[1])) result = pd.concat([s1, s2], ignore_index=True) expected = pd.Series([0, 1, pd.NA, 0, 1], dtype=object).astype(result_dtype) tm.assert_series_equal(result, expected) # order doesn't matter for result result = pd.concat([s2, s1], ignore_index=True) expected = pd.Series([0, 1, 0, 1, pd.NA], dtype=object).astype(result_dtype) tm.assert_series_equal(result, expected)