160 lines
5.5 KiB
Python
160 lines
5.5 KiB
Python
import string
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import numpy as np
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import pytest
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import pandas.util._test_decorators as td
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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 (
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SparseArray,
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SparseDtype,
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)
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class TestSeriesAccessor:
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# TODO: collect other Series accessor tests
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def test_to_dense(self):
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s = pd.Series([0, 1, 0, 10], dtype="Sparse[int64]")
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result = s.sparse.to_dense()
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expected = pd.Series([0, 1, 0, 10])
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tm.assert_series_equal(result, expected)
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class TestFrameAccessor:
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def test_accessor_raises(self):
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df = pd.DataFrame({"A": [0, 1]})
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with pytest.raises(AttributeError, match="sparse"):
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df.sparse
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@pytest.mark.parametrize("format", ["csc", "csr", "coo"])
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@pytest.mark.parametrize("labels", [None, list(string.ascii_letters[:10])])
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@pytest.mark.parametrize("dtype", ["float64", "int64"])
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@td.skip_if_no_scipy
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def test_from_spmatrix(self, format, labels, dtype):
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import scipy.sparse
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sp_dtype = SparseDtype(dtype, np.array(0, dtype=dtype).item())
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mat = scipy.sparse.eye(10, format=format, dtype=dtype)
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result = pd.DataFrame.sparse.from_spmatrix(mat, index=labels, columns=labels)
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expected = pd.DataFrame(
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np.eye(10, dtype=dtype), index=labels, columns=labels
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).astype(sp_dtype)
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tm.assert_frame_equal(result, expected)
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@pytest.mark.parametrize("format", ["csc", "csr", "coo"])
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@td.skip_if_no_scipy
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def test_from_spmatrix_including_explicit_zero(self, format):
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import scipy.sparse
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mat = scipy.sparse.random(10, 2, density=0.5, format=format)
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mat.data[0] = 0
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result = pd.DataFrame.sparse.from_spmatrix(mat)
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dtype = SparseDtype("float64", 0.0)
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expected = pd.DataFrame(mat.todense()).astype(dtype)
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tm.assert_frame_equal(result, expected)
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@pytest.mark.parametrize(
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"columns",
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[["a", "b"], pd.MultiIndex.from_product([["A"], ["a", "b"]]), ["a", "a"]],
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)
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@td.skip_if_no_scipy
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def test_from_spmatrix_columns(self, columns):
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import scipy.sparse
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dtype = SparseDtype("float64", 0.0)
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mat = scipy.sparse.random(10, 2, density=0.5)
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result = pd.DataFrame.sparse.from_spmatrix(mat, columns=columns)
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expected = pd.DataFrame(mat.toarray(), columns=columns).astype(dtype)
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tm.assert_frame_equal(result, expected)
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@pytest.mark.parametrize(
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"colnames", [("A", "B"), (1, 2), (1, pd.NA), (0.1, 0.2), ("x", "x"), (0, 0)]
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)
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@td.skip_if_no_scipy
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def test_to_coo(self, colnames):
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import scipy.sparse
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df = pd.DataFrame(
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{colnames[0]: [0, 1, 0], colnames[1]: [1, 0, 0]}, dtype="Sparse[int64, 0]"
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)
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result = df.sparse.to_coo()
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expected = scipy.sparse.coo_matrix(np.asarray(df))
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assert (result != expected).nnz == 0
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@pytest.mark.parametrize("fill_value", [1, np.nan])
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@td.skip_if_no_scipy
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def test_to_coo_nonzero_fill_val_raises(self, fill_value):
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df = pd.DataFrame(
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{
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"A": SparseArray(
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[fill_value, fill_value, fill_value, 2], fill_value=fill_value
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),
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"B": SparseArray(
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[fill_value, 2, fill_value, fill_value], fill_value=fill_value
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),
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}
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)
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with pytest.raises(ValueError, match="fill value must be 0"):
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df.sparse.to_coo()
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def test_to_dense(self):
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df = pd.DataFrame(
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{
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"A": SparseArray([1, 0], dtype=SparseDtype("int64", 0)),
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"B": SparseArray([1, 0], dtype=SparseDtype("int64", 1)),
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"C": SparseArray([1.0, 0.0], dtype=SparseDtype("float64", 0.0)),
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},
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index=["b", "a"],
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)
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result = df.sparse.to_dense()
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expected = pd.DataFrame(
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{"A": [1, 0], "B": [1, 0], "C": [1.0, 0.0]}, index=["b", "a"]
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)
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tm.assert_frame_equal(result, expected)
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def test_density(self):
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df = pd.DataFrame(
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{
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"A": SparseArray([1, 0, 2, 1], fill_value=0),
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"B": SparseArray([0, 1, 1, 1], fill_value=0),
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}
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)
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res = df.sparse.density
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expected = 0.75
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assert res == expected
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@pytest.mark.parametrize("dtype", ["int64", "float64"])
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@pytest.mark.parametrize("dense_index", [True, False])
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@td.skip_if_no_scipy
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def test_series_from_coo(self, dtype, dense_index):
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import scipy.sparse
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A = scipy.sparse.eye(3, format="coo", dtype=dtype)
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result = pd.Series.sparse.from_coo(A, dense_index=dense_index)
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index = pd.MultiIndex.from_tuples([(0, 0), (1, 1), (2, 2)])
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expected = pd.Series(SparseArray(np.array([1, 1, 1], dtype=dtype)), index=index)
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if dense_index:
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expected = expected.reindex(pd.MultiIndex.from_product(index.levels))
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tm.assert_series_equal(result, expected)
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@td.skip_if_no_scipy
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def test_series_from_coo_incorrect_format_raises(self):
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# gh-26554
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import scipy.sparse
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m = scipy.sparse.csr_matrix(np.array([[0, 1], [0, 0]]))
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with pytest.raises(
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TypeError, match="Expected coo_matrix. Got csr_matrix instead."
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):
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pd.Series.sparse.from_coo(m)
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def test_with_column_named_sparse(self):
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# https://github.com/pandas-dev/pandas/issues/30758
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df = pd.DataFrame({"sparse": pd.arrays.SparseArray([1, 2])})
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assert isinstance(df.sparse, pd.core.arrays.sparse.accessor.SparseFrameAccessor)
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