63 lines
2.6 KiB
Python
63 lines
2.6 KiB
Python
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import numpy as np
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import pytest
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import pandas as pd
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import pandas._testing as tm
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from pandas.core.arrays.sparse import SparseArray
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class TestSparseArrayConcat:
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@pytest.mark.parametrize("kind", ["integer", "block"])
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def test_basic(self, kind):
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a = SparseArray([1, 0, 0, 2], kind=kind)
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b = SparseArray([1, 0, 2, 2], kind=kind)
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result = SparseArray._concat_same_type([a, b])
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# Can't make any assertions about the sparse index itself
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# since we aren't don't merge sparse blocs across arrays
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# in to_concat
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expected = np.array([1, 2, 1, 2, 2], dtype="int64")
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tm.assert_numpy_array_equal(result.sp_values, expected)
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assert result.kind == kind
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@pytest.mark.parametrize("kind", ["integer", "block"])
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def test_uses_first_kind(self, kind):
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other = "integer" if kind == "block" else "block"
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a = SparseArray([1, 0, 0, 2], kind=kind)
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b = SparseArray([1, 0, 2, 2], kind=other)
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result = SparseArray._concat_same_type([a, b])
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expected = np.array([1, 2, 1, 2, 2], dtype="int64")
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tm.assert_numpy_array_equal(result.sp_values, expected)
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assert result.kind == kind
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@pytest.mark.parametrize(
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"other, expected_dtype",
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[
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# compatible dtype -> preserve sparse
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(pd.Series([3, 4, 5], dtype="int64"), pd.SparseDtype("int64", 0)),
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# (pd.Series([3, 4, 5], dtype="Int64"), pd.SparseDtype("int64", 0)),
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# incompatible dtype -> Sparse[common dtype]
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(pd.Series([1.5, 2.5, 3.5], dtype="float64"), pd.SparseDtype("float64", 0)),
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# incompatible dtype -> Sparse[object] dtype
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(pd.Series(["a", "b", "c"], dtype=object), pd.SparseDtype(object, 0)),
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# categorical with compatible categories -> dtype of the categories
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(pd.Series([3, 4, 5], dtype="category"), np.dtype("int64")),
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(pd.Series([1.5, 2.5, 3.5], dtype="category"), np.dtype("float64")),
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# categorical with incompatible categories -> object dtype
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(pd.Series(["a", "b", "c"], dtype="category"), np.dtype(object)),
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],
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)
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def test_concat_with_non_sparse(other, expected_dtype):
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# https://github.com/pandas-dev/pandas/issues/34336
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s_sparse = pd.Series([1, 0, 2], dtype=pd.SparseDtype("int64", 0))
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result = pd.concat([s_sparse, other], ignore_index=True)
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expected = pd.Series(list(s_sparse) + list(other)).astype(expected_dtype)
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tm.assert_series_equal(result, expected)
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result = pd.concat([other, s_sparse], ignore_index=True)
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expected = pd.Series(list(other) + list(s_sparse)).astype(expected_dtype)
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tm.assert_series_equal(result, expected)
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