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