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