mirror of
https://github.com/PiBrewing/craftbeerpi4.git
synced 2024-09-20 06:17:29 +02:00
346 lines
9.1 KiB
Python
346 lines
9.1 KiB
Python
import numpy as np
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import pytest
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from pandas._libs import join as _join
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from pandas import Categorical, DataFrame, Index, merge
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import pandas._testing as tm
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class TestIndexer:
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@pytest.mark.parametrize(
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"dtype", ["int32", "int64", "float32", "float64", "object"]
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)
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def test_outer_join_indexer(self, dtype):
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indexer = _join.outer_join_indexer
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left = np.arange(3, dtype=dtype)
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right = np.arange(2, 5, dtype=dtype)
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empty = np.array([], dtype=dtype)
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result, lindexer, rindexer = indexer(left, right)
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assert isinstance(result, np.ndarray)
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assert isinstance(lindexer, np.ndarray)
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assert isinstance(rindexer, np.ndarray)
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tm.assert_numpy_array_equal(result, np.arange(5, dtype=dtype))
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exp = np.array([0, 1, 2, -1, -1], dtype=np.int64)
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tm.assert_numpy_array_equal(lindexer, exp)
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exp = np.array([-1, -1, 0, 1, 2], dtype=np.int64)
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tm.assert_numpy_array_equal(rindexer, exp)
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result, lindexer, rindexer = indexer(empty, right)
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tm.assert_numpy_array_equal(result, right)
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exp = np.array([-1, -1, -1], dtype=np.int64)
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tm.assert_numpy_array_equal(lindexer, exp)
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exp = np.array([0, 1, 2], dtype=np.int64)
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tm.assert_numpy_array_equal(rindexer, exp)
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result, lindexer, rindexer = indexer(left, empty)
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tm.assert_numpy_array_equal(result, left)
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exp = np.array([0, 1, 2], dtype=np.int64)
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tm.assert_numpy_array_equal(lindexer, exp)
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exp = np.array([-1, -1, -1], dtype=np.int64)
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tm.assert_numpy_array_equal(rindexer, exp)
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def test_left_join_indexer_unique():
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a = np.array([1, 2, 3, 4, 5], dtype=np.int64)
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b = np.array([2, 2, 3, 4, 4], dtype=np.int64)
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result = _join.left_join_indexer_unique(b, a)
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expected = np.array([1, 1, 2, 3, 3], dtype=np.int64)
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tm.assert_numpy_array_equal(result, expected)
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def test_left_outer_join_bug():
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left = np.array(
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[
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0,
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1,
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0,
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1,
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1,
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2,
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3,
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1,
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0,
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2,
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1,
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2,
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0,
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1,
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1,
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2,
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3,
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2,
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3,
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2,
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1,
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1,
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3,
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0,
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3,
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2,
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3,
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0,
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0,
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2,
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3,
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2,
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0,
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3,
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1,
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3,
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0,
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1,
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3,
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0,
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0,
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1,
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0,
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3,
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1,
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0,
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1,
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0,
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1,
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1,
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0,
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2,
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2,
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2,
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2,
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2,
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0,
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3,
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1,
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2,
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0,
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0,
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3,
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1,
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3,
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2,
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2,
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0,
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1,
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3,
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0,
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2,
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3,
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2,
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3,
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3,
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2,
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3,
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3,
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1,
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3,
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2,
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0,
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0,
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3,
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1,
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1,
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1,
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0,
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2,
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3,
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3,
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1,
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2,
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0,
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3,
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1,
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2,
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0,
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2,
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],
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dtype=np.int64,
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)
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right = np.array([3, 1], dtype=np.int64)
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max_groups = 4
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lidx, ridx = _join.left_outer_join(left, right, max_groups, sort=False)
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exp_lidx = np.arange(len(left), dtype=np.int64)
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exp_ridx = -np.ones(len(left), dtype=np.int64)
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exp_ridx[left == 1] = 1
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exp_ridx[left == 3] = 0
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tm.assert_numpy_array_equal(lidx, exp_lidx)
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tm.assert_numpy_array_equal(ridx, exp_ridx)
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def test_inner_join_indexer():
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a = np.array([1, 2, 3, 4, 5], dtype=np.int64)
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b = np.array([0, 3, 5, 7, 9], dtype=np.int64)
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index, ares, bres = _join.inner_join_indexer(a, b)
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index_exp = np.array([3, 5], dtype=np.int64)
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tm.assert_almost_equal(index, index_exp)
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aexp = np.array([2, 4], dtype=np.int64)
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bexp = np.array([1, 2], dtype=np.int64)
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tm.assert_almost_equal(ares, aexp)
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tm.assert_almost_equal(bres, bexp)
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a = np.array([5], dtype=np.int64)
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b = np.array([5], dtype=np.int64)
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index, ares, bres = _join.inner_join_indexer(a, b)
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tm.assert_numpy_array_equal(index, np.array([5], dtype=np.int64))
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tm.assert_numpy_array_equal(ares, np.array([0], dtype=np.int64))
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tm.assert_numpy_array_equal(bres, np.array([0], dtype=np.int64))
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def test_outer_join_indexer():
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a = np.array([1, 2, 3, 4, 5], dtype=np.int64)
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b = np.array([0, 3, 5, 7, 9], dtype=np.int64)
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index, ares, bres = _join.outer_join_indexer(a, b)
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index_exp = np.array([0, 1, 2, 3, 4, 5, 7, 9], dtype=np.int64)
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tm.assert_almost_equal(index, index_exp)
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aexp = np.array([-1, 0, 1, 2, 3, 4, -1, -1], dtype=np.int64)
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bexp = np.array([0, -1, -1, 1, -1, 2, 3, 4], dtype=np.int64)
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tm.assert_almost_equal(ares, aexp)
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tm.assert_almost_equal(bres, bexp)
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a = np.array([5], dtype=np.int64)
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b = np.array([5], dtype=np.int64)
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index, ares, bres = _join.outer_join_indexer(a, b)
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tm.assert_numpy_array_equal(index, np.array([5], dtype=np.int64))
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tm.assert_numpy_array_equal(ares, np.array([0], dtype=np.int64))
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tm.assert_numpy_array_equal(bres, np.array([0], dtype=np.int64))
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def test_left_join_indexer():
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a = np.array([1, 2, 3, 4, 5], dtype=np.int64)
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b = np.array([0, 3, 5, 7, 9], dtype=np.int64)
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index, ares, bres = _join.left_join_indexer(a, b)
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tm.assert_almost_equal(index, a)
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aexp = np.array([0, 1, 2, 3, 4], dtype=np.int64)
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bexp = np.array([-1, -1, 1, -1, 2], dtype=np.int64)
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tm.assert_almost_equal(ares, aexp)
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tm.assert_almost_equal(bres, bexp)
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a = np.array([5], dtype=np.int64)
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b = np.array([5], dtype=np.int64)
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index, ares, bres = _join.left_join_indexer(a, b)
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tm.assert_numpy_array_equal(index, np.array([5], dtype=np.int64))
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tm.assert_numpy_array_equal(ares, np.array([0], dtype=np.int64))
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tm.assert_numpy_array_equal(bres, np.array([0], dtype=np.int64))
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def test_left_join_indexer2():
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idx = Index([1, 1, 2, 5])
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idx2 = Index([1, 2, 5, 7, 9])
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res, lidx, ridx = _join.left_join_indexer(idx2.values, idx.values)
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exp_res = np.array([1, 1, 2, 5, 7, 9], dtype=np.int64)
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tm.assert_almost_equal(res, exp_res)
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exp_lidx = np.array([0, 0, 1, 2, 3, 4], dtype=np.int64)
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tm.assert_almost_equal(lidx, exp_lidx)
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exp_ridx = np.array([0, 1, 2, 3, -1, -1], dtype=np.int64)
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tm.assert_almost_equal(ridx, exp_ridx)
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def test_outer_join_indexer2():
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idx = Index([1, 1, 2, 5])
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idx2 = Index([1, 2, 5, 7, 9])
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res, lidx, ridx = _join.outer_join_indexer(idx2.values, idx.values)
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exp_res = np.array([1, 1, 2, 5, 7, 9], dtype=np.int64)
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tm.assert_almost_equal(res, exp_res)
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exp_lidx = np.array([0, 0, 1, 2, 3, 4], dtype=np.int64)
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tm.assert_almost_equal(lidx, exp_lidx)
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exp_ridx = np.array([0, 1, 2, 3, -1, -1], dtype=np.int64)
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tm.assert_almost_equal(ridx, exp_ridx)
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def test_inner_join_indexer2():
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idx = Index([1, 1, 2, 5])
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idx2 = Index([1, 2, 5, 7, 9])
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res, lidx, ridx = _join.inner_join_indexer(idx2.values, idx.values)
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exp_res = np.array([1, 1, 2, 5], dtype=np.int64)
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tm.assert_almost_equal(res, exp_res)
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exp_lidx = np.array([0, 0, 1, 2], dtype=np.int64)
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tm.assert_almost_equal(lidx, exp_lidx)
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exp_ridx = np.array([0, 1, 2, 3], dtype=np.int64)
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tm.assert_almost_equal(ridx, exp_ridx)
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def test_merge_join_categorical_multiindex():
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# From issue 16627
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a = {
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"Cat1": Categorical(["a", "b", "a", "c", "a", "b"], ["a", "b", "c"]),
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"Int1": [0, 1, 0, 1, 0, 0],
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}
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a = DataFrame(a)
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b = {
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"Cat": Categorical(["a", "b", "c", "a", "b", "c"], ["a", "b", "c"]),
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"Int": [0, 0, 0, 1, 1, 1],
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"Factor": [1.1, 1.2, 1.3, 1.4, 1.5, 1.6],
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}
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b = DataFrame(b).set_index(["Cat", "Int"])["Factor"]
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expected = merge(
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a,
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b.reset_index(),
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left_on=["Cat1", "Int1"],
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right_on=["Cat", "Int"],
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how="left",
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)
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result = a.join(b, on=["Cat1", "Int1"])
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expected = expected.drop(["Cat", "Int"], axis=1)
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tm.assert_frame_equal(expected, result)
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# Same test, but with ordered categorical
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a = {
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"Cat1": Categorical(
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["a", "b", "a", "c", "a", "b"], ["b", "a", "c"], ordered=True
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),
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"Int1": [0, 1, 0, 1, 0, 0],
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}
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a = DataFrame(a)
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b = {
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"Cat": Categorical(
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["a", "b", "c", "a", "b", "c"], ["b", "a", "c"], ordered=True
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),
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"Int": [0, 0, 0, 1, 1, 1],
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"Factor": [1.1, 1.2, 1.3, 1.4, 1.5, 1.6],
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}
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b = DataFrame(b).set_index(["Cat", "Int"])["Factor"]
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expected = merge(
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a,
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b.reset_index(),
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left_on=["Cat1", "Int1"],
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right_on=["Cat", "Int"],
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how="left",
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)
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result = a.join(b, on=["Cat1", "Int1"])
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expected = expected.drop(["Cat", "Int"], axis=1)
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tm.assert_frame_equal(expected, result)
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