LSR/env/lib/python3.6/site-packages/pandas/tests/indexes/multi/conftest.py
2020-06-04 17:24:47 +02:00

86 lines
2.3 KiB
Python

import numpy as np
import pytest
import pandas as pd
from pandas import Index, MultiIndex
@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 holder():
# the MultiIndex constructor used to base compatibility with pickle
return MultiIndex
@pytest.fixture
def compat_props():
# a MultiIndex must have these properties associated with it
return ["shape", "ndim", "size"]
@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 pd.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 pd.MultiIndex.from_arrays(levels, names=names)