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80 lines
2.2 KiB
Python
80 lines
2.2 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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from pandas import Index, MultiIndex
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@pytest.fixture
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def idx():
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# a MultiIndex used to test the general functionality of the
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# general functionality of this object
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major_axis = Index(["foo", "bar", "baz", "qux"])
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minor_axis = Index(["one", "two"])
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major_codes = np.array([0, 0, 1, 2, 3, 3])
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minor_codes = np.array([0, 1, 0, 1, 0, 1])
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index_names = ["first", "second"]
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mi = MultiIndex(
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levels=[major_axis, minor_axis],
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codes=[major_codes, minor_codes],
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names=index_names,
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verify_integrity=False,
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)
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return mi
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@pytest.fixture
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def idx_dup():
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# compare tests/indexes/multi/conftest.py
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major_axis = Index(["foo", "bar", "baz", "qux"])
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minor_axis = Index(["one", "two"])
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major_codes = np.array([0, 0, 1, 0, 1, 1])
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minor_codes = np.array([0, 1, 0, 1, 0, 1])
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index_names = ["first", "second"]
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mi = MultiIndex(
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levels=[major_axis, minor_axis],
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codes=[major_codes, minor_codes],
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names=index_names,
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verify_integrity=False,
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)
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return mi
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@pytest.fixture
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def index_names():
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# names that match those in the idx fixture for testing equality of
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# names assigned to the idx
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return ["first", "second"]
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@pytest.fixture
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def compat_props():
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# a MultiIndex must have these properties associated with it
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return ["shape", "ndim", "size"]
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@pytest.fixture
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def narrow_multi_index():
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"""
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Return a MultiIndex that is narrower than the display (<80 characters).
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"""
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n = 1000
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ci = pd.CategoricalIndex(list("a" * n) + (["abc"] * n))
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dti = pd.date_range("2000-01-01", freq="s", periods=n * 2)
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return MultiIndex.from_arrays([ci, ci.codes + 9, dti], names=["a", "b", "dti"])
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@pytest.fixture
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def wide_multi_index():
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"""
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Return a MultiIndex that is wider than the display (>80 characters).
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"""
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n = 1000
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ci = pd.CategoricalIndex(list("a" * n) + (["abc"] * n))
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dti = pd.date_range("2000-01-01", freq="s", periods=n * 2)
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levels = [ci, ci.codes + 9, dti, dti, dti]
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names = ["a", "b", "dti_1", "dti_2", "dti_3"]
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return MultiIndex.from_arrays(levels, names=names)
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