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 (
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SparseArray,
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SparseDtype,
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)
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arr_data = np.array([np.nan, np.nan, 1, 2, 3, np.nan, 4, 5, np.nan, 6])
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arr = SparseArray(arr_data)
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class TestGetitem:
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def test_getitem(self):
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dense = arr.to_dense()
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for i, value in enumerate(arr):
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tm.assert_almost_equal(value, dense[i])
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tm.assert_almost_equal(arr[-i], dense[-i])
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def test_getitem_arraylike_mask(self):
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arr = SparseArray([0, 1, 2])
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result = arr[[True, False, True]]
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expected = SparseArray([0, 2])
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tm.assert_sp_array_equal(result, expected)
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@pytest.mark.parametrize(
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"slc",
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[
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np.s_[:],
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np.s_[1:10],
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np.s_[1:100],
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np.s_[10:1],
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np.s_[:-3],
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np.s_[-5:-4],
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np.s_[:-12],
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np.s_[-12:],
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np.s_[2:],
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np.s_[2::3],
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np.s_[::2],
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np.s_[::-1],
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np.s_[::-2],
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np.s_[1:6:2],
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np.s_[:-6:-2],
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],
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)
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@pytest.mark.parametrize(
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"as_dense", [[np.nan] * 10, [1] * 10, [np.nan] * 5 + [1] * 5, []]
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)
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def test_getslice(self, slc, as_dense):
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as_dense = np.array(as_dense)
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arr = SparseArray(as_dense)
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result = arr[slc]
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expected = SparseArray(as_dense[slc])
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tm.assert_sp_array_equal(result, expected)
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def test_getslice_tuple(self):
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dense = np.array([np.nan, 0, 3, 4, 0, 5, np.nan, np.nan, 0])
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sparse = SparseArray(dense)
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res = sparse[(slice(4, None),)]
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exp = SparseArray(dense[4:])
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tm.assert_sp_array_equal(res, exp)
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sparse = SparseArray(dense, fill_value=0)
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res = sparse[(slice(4, None),)]
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exp = SparseArray(dense[4:], fill_value=0)
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tm.assert_sp_array_equal(res, exp)
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msg = "too many indices for array"
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with pytest.raises(IndexError, match=msg):
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sparse[4:, :]
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with pytest.raises(IndexError, match=msg):
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# check numpy compat
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dense[4:, :]
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def test_boolean_slice_empty(self):
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arr = SparseArray([0, 1, 2])
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res = arr[[False, False, False]]
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assert res.dtype == arr.dtype
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def test_getitem_bool_sparse_array(self):
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# GH 23122
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spar_bool = SparseArray([False, True] * 5, dtype=np.bool_, fill_value=True)
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exp = SparseArray([np.nan, 2, np.nan, 5, 6])
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tm.assert_sp_array_equal(arr[spar_bool], exp)
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spar_bool = ~spar_bool
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res = arr[spar_bool]
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exp = SparseArray([np.nan, 1, 3, 4, np.nan])
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tm.assert_sp_array_equal(res, exp)
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spar_bool = SparseArray(
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[False, True, np.nan] * 3, dtype=np.bool_, fill_value=np.nan
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)
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res = arr[spar_bool]
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exp = SparseArray([np.nan, 3, 5])
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tm.assert_sp_array_equal(res, exp)
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def test_getitem_bool_sparse_array_as_comparison(self):
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# GH 45110
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arr = SparseArray([1, 2, 3, 4, np.nan, np.nan], fill_value=np.nan)
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res = arr[arr > 2]
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exp = SparseArray([3.0, 4.0], fill_value=np.nan)
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tm.assert_sp_array_equal(res, exp)
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def test_get_item(self):
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zarr = SparseArray([0, 0, 1, 2, 3, 0, 4, 5, 0, 6], fill_value=0)
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assert np.isnan(arr[1])
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assert arr[2] == 1
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assert arr[7] == 5
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assert zarr[0] == 0
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assert zarr[2] == 1
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assert zarr[7] == 5
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errmsg = "must be an integer between -10 and 10"
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with pytest.raises(IndexError, match=errmsg):
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arr[11]
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with pytest.raises(IndexError, match=errmsg):
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arr[-11]
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assert arr[-1] == arr[len(arr) - 1]
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class TestSetitem:
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def test_set_item(self):
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arr = SparseArray(arr_data).copy()
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def setitem():
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arr[5] = 3
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def setslice():
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arr[1:5] = 2
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with pytest.raises(TypeError, match="assignment via setitem"):
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setitem()
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with pytest.raises(TypeError, match="assignment via setitem"):
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setslice()
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class TestTake:
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def test_take_scalar_raises(self):
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msg = "'indices' must be an array, not a scalar '2'."
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with pytest.raises(ValueError, match=msg):
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arr.take(2)
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def test_take(self):
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exp = SparseArray(np.take(arr_data, [2, 3]))
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tm.assert_sp_array_equal(arr.take([2, 3]), exp)
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exp = SparseArray(np.take(arr_data, [0, 1, 2]))
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tm.assert_sp_array_equal(arr.take([0, 1, 2]), exp)
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def test_take_all_empty(self):
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a = pd.array([0, 0], dtype=SparseDtype("int64"))
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result = a.take([0, 1], allow_fill=True, fill_value=np.nan)
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tm.assert_sp_array_equal(a, result)
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def test_take_fill_value(self):
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data = np.array([1, np.nan, 0, 3, 0])
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sparse = SparseArray(data, fill_value=0)
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exp = SparseArray(np.take(data, [0]), fill_value=0)
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tm.assert_sp_array_equal(sparse.take([0]), exp)
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exp = SparseArray(np.take(data, [1, 3, 4]), fill_value=0)
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tm.assert_sp_array_equal(sparse.take([1, 3, 4]), exp)
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def test_take_negative(self):
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exp = SparseArray(np.take(arr_data, [-1]))
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tm.assert_sp_array_equal(arr.take([-1]), exp)
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exp = SparseArray(np.take(arr_data, [-4, -3, -2]))
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tm.assert_sp_array_equal(arr.take([-4, -3, -2]), exp)
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def test_bad_take(self):
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with pytest.raises(IndexError, match="bounds"):
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arr.take([11])
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def test_take_filling(self):
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# similar tests as GH 12631
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sparse = SparseArray([np.nan, np.nan, 1, np.nan, 4])
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result = sparse.take(np.array([1, 0, -1]))
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expected = SparseArray([np.nan, np.nan, 4])
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tm.assert_sp_array_equal(result, expected)
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# TODO: actionable?
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# XXX: test change: fill_value=True -> allow_fill=True
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result = sparse.take(np.array([1, 0, -1]), allow_fill=True)
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expected = SparseArray([np.nan, np.nan, np.nan])
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tm.assert_sp_array_equal(result, expected)
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# allow_fill=False
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result = sparse.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
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expected = SparseArray([np.nan, np.nan, 4])
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tm.assert_sp_array_equal(result, expected)
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msg = "Invalid value in 'indices'"
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with pytest.raises(ValueError, match=msg):
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sparse.take(np.array([1, 0, -2]), allow_fill=True)
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with pytest.raises(ValueError, match=msg):
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sparse.take(np.array([1, 0, -5]), allow_fill=True)
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msg = "out of bounds value in 'indices'"
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with pytest.raises(IndexError, match=msg):
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sparse.take(np.array([1, -6]))
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with pytest.raises(IndexError, match=msg):
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sparse.take(np.array([1, 5]))
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with pytest.raises(IndexError, match=msg):
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sparse.take(np.array([1, 5]), allow_fill=True)
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def test_take_filling_fill_value(self):
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# same tests as GH#12631
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sparse = SparseArray([np.nan, 0, 1, 0, 4], fill_value=0)
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result = sparse.take(np.array([1, 0, -1]))
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expected = SparseArray([0, np.nan, 4], fill_value=0)
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tm.assert_sp_array_equal(result, expected)
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# fill_value
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result = sparse.take(np.array([1, 0, -1]), allow_fill=True)
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# TODO: actionable?
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# XXX: behavior change.
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# the old way of filling self.fill_value doesn't follow EA rules.
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# It's supposed to be self.dtype.na_value (nan in this case)
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expected = SparseArray([0, np.nan, np.nan], fill_value=0)
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tm.assert_sp_array_equal(result, expected)
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# allow_fill=False
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result = sparse.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
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expected = SparseArray([0, np.nan, 4], fill_value=0)
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tm.assert_sp_array_equal(result, expected)
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msg = "Invalid value in 'indices'."
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with pytest.raises(ValueError, match=msg):
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sparse.take(np.array([1, 0, -2]), allow_fill=True)
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with pytest.raises(ValueError, match=msg):
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sparse.take(np.array([1, 0, -5]), allow_fill=True)
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msg = "out of bounds value in 'indices'"
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with pytest.raises(IndexError, match=msg):
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sparse.take(np.array([1, -6]))
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with pytest.raises(IndexError, match=msg):
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sparse.take(np.array([1, 5]))
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with pytest.raises(IndexError, match=msg):
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sparse.take(np.array([1, 5]), fill_value=True)
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@pytest.mark.parametrize("kind", ["block", "integer"])
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def test_take_filling_all_nan(self, kind):
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sparse = SparseArray([np.nan, np.nan, np.nan, np.nan, np.nan], kind=kind)
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result = sparse.take(np.array([1, 0, -1]))
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expected = SparseArray([np.nan, np.nan, np.nan], kind=kind)
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tm.assert_sp_array_equal(result, expected)
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result = sparse.take(np.array([1, 0, -1]), fill_value=True)
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expected = SparseArray([np.nan, np.nan, np.nan], kind=kind)
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tm.assert_sp_array_equal(result, expected)
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msg = "out of bounds value in 'indices'"
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with pytest.raises(IndexError, match=msg):
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sparse.take(np.array([1, -6]))
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with pytest.raises(IndexError, match=msg):
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sparse.take(np.array([1, 5]))
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with pytest.raises(IndexError, match=msg):
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sparse.take(np.array([1, 5]), fill_value=True)
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class TestWhere:
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def test_where_retain_fill_value(self):
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# GH#45691 don't lose fill_value on _where
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arr = SparseArray([np.nan, 1.0], fill_value=0)
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mask = np.array([True, False])
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res = arr._where(~mask, 1)
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exp = SparseArray([1, 1.0], fill_value=0)
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tm.assert_sp_array_equal(res, exp)
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ser = pd.Series(arr)
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res = ser.where(~mask, 1)
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tm.assert_series_equal(res, pd.Series(exp))
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