craftbeerpi4-pione/venv/lib/python3.8/site-packages/pandas/tests/indexes/common.py

819 lines
28 KiB
Python

import gc
from typing import Type
import numpy as np
import pytest
from pandas._libs import iNaT
from pandas.errors import InvalidIndexError
from pandas.core.dtypes.common import is_datetime64tz_dtype
from pandas.core.dtypes.dtypes import CategoricalDtype
import pandas as pd
from pandas import (
CategoricalIndex,
DatetimeIndex,
Index,
Int64Index,
IntervalIndex,
MultiIndex,
PeriodIndex,
RangeIndex,
Series,
TimedeltaIndex,
UInt64Index,
isna,
)
import pandas._testing as tm
from pandas.core.indexes.datetimelike import DatetimeIndexOpsMixin
class Base:
""" base class for index sub-class tests """
_holder: Type[Index]
_compat_props = ["shape", "ndim", "size", "nbytes"]
def create_index(self) -> Index:
raise NotImplementedError("Method not implemented")
def test_pickle_compat_construction(self):
# need an object to create with
msg = (
r"Index\(\.\.\.\) must be called with a collection of some "
r"kind, None was passed|"
r"__new__\(\) missing 1 required positional argument: 'data'|"
r"__new__\(\) takes at least 2 arguments \(1 given\)"
)
with pytest.raises(TypeError, match=msg):
self._holder()
@pytest.mark.parametrize("name", [None, "new_name"])
def test_to_frame(self, name):
# see GH-15230, GH-22580
idx = self.create_index()
if name:
idx_name = name
else:
idx_name = idx.name or 0
df = idx.to_frame(name=idx_name)
assert df.index is idx
assert len(df.columns) == 1
assert df.columns[0] == idx_name
assert df[idx_name].values is not idx.values
df = idx.to_frame(index=False, name=idx_name)
assert df.index is not idx
def test_shift(self):
# GH8083 test the base class for shift
idx = self.create_index()
msg = (
f"This method is only implemented for DatetimeIndex, PeriodIndex and "
f"TimedeltaIndex; Got type {type(idx).__name__}"
)
with pytest.raises(NotImplementedError, match=msg):
idx.shift(1)
with pytest.raises(NotImplementedError, match=msg):
idx.shift(1, 2)
def test_constructor_name_unhashable(self):
# GH#29069 check that name is hashable
# See also same-named test in tests.series.test_constructors
idx = self.create_index()
with pytest.raises(TypeError, match="Index.name must be a hashable type"):
type(idx)(idx, name=[])
def test_create_index_existing_name(self):
# GH11193, when an existing index is passed, and a new name is not
# specified, the new index should inherit the previous object name
expected = self.create_index()
if not isinstance(expected, MultiIndex):
expected.name = "foo"
result = Index(expected)
tm.assert_index_equal(result, expected)
result = Index(expected, name="bar")
expected.name = "bar"
tm.assert_index_equal(result, expected)
else:
expected.names = ["foo", "bar"]
result = Index(expected)
tm.assert_index_equal(
result,
Index(
Index(
[
("foo", "one"),
("foo", "two"),
("bar", "one"),
("baz", "two"),
("qux", "one"),
("qux", "two"),
],
dtype="object",
),
names=["foo", "bar"],
),
)
result = Index(expected, names=["A", "B"])
tm.assert_index_equal(
result,
Index(
Index(
[
("foo", "one"),
("foo", "two"),
("bar", "one"),
("baz", "two"),
("qux", "one"),
("qux", "two"),
],
dtype="object",
),
names=["A", "B"],
),
)
def test_numeric_compat(self):
idx = self.create_index()
# Check that this doesn't cover MultiIndex case, if/when it does,
# we can remove multi.test_compat.test_numeric_compat
assert not isinstance(idx, MultiIndex)
if type(idx) is Index:
return
typ = type(idx._data).__name__
lmsg = "|".join(
[
rf"unsupported operand type\(s\) for \*: '{typ}' and 'int'",
"cannot perform (__mul__|__truediv__|__floordiv__) with "
f"this index type: {typ}",
]
)
with pytest.raises(TypeError, match=lmsg):
idx * 1
rmsg = "|".join(
[
rf"unsupported operand type\(s\) for \*: 'int' and '{typ}'",
"cannot perform (__rmul__|__rtruediv__|__rfloordiv__) with "
f"this index type: {typ}",
]
)
with pytest.raises(TypeError, match=rmsg):
1 * idx
div_err = lmsg.replace("*", "/")
with pytest.raises(TypeError, match=div_err):
idx / 1
div_err = rmsg.replace("*", "/")
with pytest.raises(TypeError, match=div_err):
1 / idx
floordiv_err = lmsg.replace("*", "//")
with pytest.raises(TypeError, match=floordiv_err):
idx // 1
floordiv_err = rmsg.replace("*", "//")
with pytest.raises(TypeError, match=floordiv_err):
1 // idx
def test_logical_compat(self):
idx = self.create_index()
with pytest.raises(TypeError, match="cannot perform all"):
idx.all()
with pytest.raises(TypeError, match="cannot perform any"):
idx.any()
def test_reindex_base(self):
idx = self.create_index()
expected = np.arange(idx.size, dtype=np.intp)
actual = idx.get_indexer(idx)
tm.assert_numpy_array_equal(expected, actual)
with pytest.raises(ValueError, match="Invalid fill method"):
idx.get_indexer(idx, method="invalid")
def test_get_indexer_consistency(self, index):
# See GH 16819
if isinstance(index, IntervalIndex):
return
if index.is_unique or isinstance(index, CategoricalIndex):
indexer = index.get_indexer(index[0:2])
assert isinstance(indexer, np.ndarray)
assert indexer.dtype == np.intp
else:
e = "Reindexing only valid with uniquely valued Index objects"
with pytest.raises(InvalidIndexError, match=e):
index.get_indexer(index[0:2])
indexer, _ = index.get_indexer_non_unique(index[0:2])
assert isinstance(indexer, np.ndarray)
assert indexer.dtype == np.intp
def test_ndarray_compat_properties(self):
idx = self.create_index()
assert idx.T.equals(idx)
assert idx.transpose().equals(idx)
values = idx.values
for prop in self._compat_props:
assert getattr(idx, prop) == getattr(values, prop)
# test for validity
idx.nbytes
idx.values.nbytes
def test_repr_roundtrip(self):
idx = self.create_index()
tm.assert_index_equal(eval(repr(idx)), idx)
def test_repr_max_seq_item_setting(self):
# GH10182
idx = self.create_index()
idx = idx.repeat(50)
with pd.option_context("display.max_seq_items", None):
repr(idx)
assert "..." not in str(idx)
def test_copy_name(self, index):
# gh-12309: Check that the "name" argument
# passed at initialization is honored.
if isinstance(index, MultiIndex):
return
first = type(index)(index, copy=True, name="mario")
second = type(first)(first, copy=False)
# Even though "copy=False", we want a new object.
assert first is not second
# Not using tm.assert_index_equal() since names differ.
assert index.equals(first)
assert first.name == "mario"
assert second.name == "mario"
s1 = Series(2, index=first)
s2 = Series(3, index=second[:-1])
if not isinstance(index, CategoricalIndex):
# See gh-13365
s3 = s1 * s2
assert s3.index.name == "mario"
def test_copy_name2(self, index):
# gh-35592
if isinstance(index, MultiIndex):
return
assert index.copy(name="mario").name == "mario"
with pytest.raises(ValueError, match="Length of new names must be 1, got 2"):
index.copy(name=["mario", "luigi"])
msg = f"{type(index).__name__}.name must be a hashable type"
with pytest.raises(TypeError, match=msg):
index.copy(name=[["mario"]])
def test_copy_dtype_deprecated(self, index):
# GH35853
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
index.copy(dtype=object)
def test_ensure_copied_data(self, index):
# Check the "copy" argument of each Index.__new__ is honoured
# GH12309
init_kwargs = {}
if isinstance(index, PeriodIndex):
# Needs "freq" specification:
init_kwargs["freq"] = index.freq
elif isinstance(index, (RangeIndex, MultiIndex, CategoricalIndex)):
# RangeIndex cannot be initialized from data
# MultiIndex and CategoricalIndex are tested separately
return
index_type = type(index)
result = index_type(index.values, copy=True, **init_kwargs)
if is_datetime64tz_dtype(index.dtype):
result = result.tz_localize("UTC").tz_convert(index.tz)
if isinstance(index, (DatetimeIndex, TimedeltaIndex)):
index = index._with_freq(None)
tm.assert_index_equal(index, result)
if isinstance(index, PeriodIndex):
# .values an object array of Period, thus copied
result = index_type(ordinal=index.asi8, copy=False, **init_kwargs)
tm.assert_numpy_array_equal(index.asi8, result.asi8, check_same="same")
elif isinstance(index, IntervalIndex):
# checked in test_interval.py
pass
else:
result = index_type(index.values, copy=False, **init_kwargs)
tm.assert_numpy_array_equal(index.values, result.values, check_same="same")
def test_memory_usage(self, index):
index._engine.clear_mapping()
result = index.memory_usage()
if index.empty:
# we report 0 for no-length
assert result == 0
return
# non-zero length
index.get_loc(index[0])
result2 = index.memory_usage()
result3 = index.memory_usage(deep=True)
# RangeIndex, IntervalIndex
# don't have engines
if not isinstance(index, (RangeIndex, IntervalIndex)):
assert result2 > result
if index.inferred_type == "object":
assert result3 > result2
def test_argsort(self, request, index):
# separately tested
if isinstance(index, CategoricalIndex):
return
result = index.argsort()
expected = np.array(index).argsort()
tm.assert_numpy_array_equal(result, expected, check_dtype=False)
def test_numpy_argsort(self, index):
result = np.argsort(index)
expected = index.argsort()
tm.assert_numpy_array_equal(result, expected)
# these are the only two types that perform
# pandas compatibility input validation - the
# rest already perform separate (or no) such
# validation via their 'values' attribute as
# defined in pandas.core.indexes/base.py - they
# cannot be changed at the moment due to
# backwards compatibility concerns
if isinstance(type(index), (CategoricalIndex, RangeIndex)):
# TODO: why type(index)?
msg = "the 'axis' parameter is not supported"
with pytest.raises(ValueError, match=msg):
np.argsort(index, axis=1)
msg = "the 'kind' parameter is not supported"
with pytest.raises(ValueError, match=msg):
np.argsort(index, kind="mergesort")
msg = "the 'order' parameter is not supported"
with pytest.raises(ValueError, match=msg):
np.argsort(index, order=("a", "b"))
def test_repeat(self):
rep = 2
i = self.create_index()
expected = Index(i.values.repeat(rep), name=i.name)
tm.assert_index_equal(i.repeat(rep), expected)
i = self.create_index()
rep = np.arange(len(i))
expected = Index(i.values.repeat(rep), name=i.name)
tm.assert_index_equal(i.repeat(rep), expected)
def test_numpy_repeat(self):
rep = 2
i = self.create_index()
expected = i.repeat(rep)
tm.assert_index_equal(np.repeat(i, rep), expected)
msg = "the 'axis' parameter is not supported"
with pytest.raises(ValueError, match=msg):
np.repeat(i, rep, axis=0)
@pytest.mark.parametrize("klass", [list, tuple, np.array, Series])
def test_where(self, klass):
i = self.create_index()
if isinstance(i, (pd.DatetimeIndex, pd.TimedeltaIndex)):
# where does not preserve freq
i = i._with_freq(None)
cond = [True] * len(i)
result = i.where(klass(cond))
expected = i
tm.assert_index_equal(result, expected)
cond = [False] + [True] * len(i[1:])
expected = Index([i._na_value] + i[1:].tolist(), dtype=i.dtype)
result = i.where(klass(cond))
tm.assert_index_equal(result, expected)
def test_insert_base(self, index):
result = index[1:4]
if not len(index):
return
# test 0th element
assert index[0:4].equals(result.insert(0, index[0]))
def test_delete_base(self, index):
if not len(index):
return
if isinstance(index, RangeIndex):
# tested in class
return
expected = index[1:]
result = index.delete(0)
assert result.equals(expected)
assert result.name == expected.name
expected = index[:-1]
result = index.delete(-1)
assert result.equals(expected)
assert result.name == expected.name
length = len(index)
msg = f"index {length} is out of bounds for axis 0 with size {length}"
with pytest.raises(IndexError, match=msg):
index.delete(length)
def test_equals(self, index):
if isinstance(index, IntervalIndex):
# IntervalIndex tested separately, the index.equals(index.astype(object))
# fails for IntervalIndex
return
assert index.equals(index)
assert index.equals(index.copy())
assert index.equals(index.astype(object))
assert not index.equals(list(index))
assert not index.equals(np.array(index))
# Cannot pass in non-int64 dtype to RangeIndex
if not isinstance(index, RangeIndex):
same_values = Index(index, dtype=object)
assert index.equals(same_values)
assert same_values.equals(index)
if index.nlevels == 1:
# do not test MultiIndex
assert not index.equals(Series(index))
def test_equals_op(self):
# GH9947, GH10637
index_a = self.create_index()
n = len(index_a)
index_b = index_a[0:-1]
index_c = index_a[0:-1].append(index_a[-2:-1])
index_d = index_a[0:1]
msg = "Lengths must match|could not be broadcast"
with pytest.raises(ValueError, match=msg):
index_a == index_b
expected1 = np.array([True] * n)
expected2 = np.array([True] * (n - 1) + [False])
tm.assert_numpy_array_equal(index_a == index_a, expected1)
tm.assert_numpy_array_equal(index_a == index_c, expected2)
# test comparisons with numpy arrays
array_a = np.array(index_a)
array_b = np.array(index_a[0:-1])
array_c = np.array(index_a[0:-1].append(index_a[-2:-1]))
array_d = np.array(index_a[0:1])
with pytest.raises(ValueError, match=msg):
index_a == array_b
tm.assert_numpy_array_equal(index_a == array_a, expected1)
tm.assert_numpy_array_equal(index_a == array_c, expected2)
# test comparisons with Series
series_a = Series(array_a)
series_b = Series(array_b)
series_c = Series(array_c)
series_d = Series(array_d)
with pytest.raises(ValueError, match=msg):
index_a == series_b
tm.assert_numpy_array_equal(index_a == series_a, expected1)
tm.assert_numpy_array_equal(index_a == series_c, expected2)
# cases where length is 1 for one of them
with pytest.raises(ValueError, match="Lengths must match"):
index_a == index_d
with pytest.raises(ValueError, match="Lengths must match"):
index_a == series_d
with pytest.raises(ValueError, match="Lengths must match"):
index_a == array_d
msg = "Can only compare identically-labeled Series objects"
with pytest.raises(ValueError, match=msg):
series_a == series_d
with pytest.raises(ValueError, match="Lengths must match"):
series_a == array_d
# comparing with a scalar should broadcast; note that we are excluding
# MultiIndex because in this case each item in the index is a tuple of
# length 2, and therefore is considered an array of length 2 in the
# comparison instead of a scalar
if not isinstance(index_a, MultiIndex):
expected3 = np.array([False] * (len(index_a) - 2) + [True, False])
# assuming the 2nd to last item is unique in the data
item = index_a[-2]
tm.assert_numpy_array_equal(index_a == item, expected3)
# For RangeIndex we can convert to Int64Index
tm.assert_series_equal(series_a == item, Series(expected3))
def test_format(self):
# GH35439
idx = self.create_index()
expected = [str(x) for x in idx]
assert idx.format() == expected
def test_format_empty(self):
# GH35712
empty_idx = self._holder([])
assert empty_idx.format() == []
assert empty_idx.format(name=True) == [""]
def test_hasnans_isnans(self, index):
# GH 11343, added tests for hasnans / isnans
if isinstance(index, MultiIndex):
return
# cases in indices doesn't include NaN
idx = index.copy(deep=True)
expected = np.array([False] * len(idx), dtype=bool)
tm.assert_numpy_array_equal(idx._isnan, expected)
assert idx.hasnans is False
idx = index.copy(deep=True)
values = np.asarray(idx.values)
if len(index) == 0:
return
elif isinstance(index, DatetimeIndexOpsMixin):
values[1] = iNaT
elif isinstance(index, (Int64Index, UInt64Index)):
return
else:
values[1] = np.nan
if isinstance(index, PeriodIndex):
idx = type(index)(values, freq=index.freq)
else:
idx = type(index)(values)
expected = np.array([False] * len(idx), dtype=bool)
expected[1] = True
tm.assert_numpy_array_equal(idx._isnan, expected)
assert idx.hasnans is True
def test_fillna(self, index):
# GH 11343
if len(index) == 0:
pass
elif isinstance(index, MultiIndex):
idx = index.copy(deep=True)
msg = "isna is not defined for MultiIndex"
with pytest.raises(NotImplementedError, match=msg):
idx.fillna(idx[0])
else:
idx = index.copy(deep=True)
result = idx.fillna(idx[0])
tm.assert_index_equal(result, idx)
assert result is not idx
msg = "'value' must be a scalar, passed: "
with pytest.raises(TypeError, match=msg):
idx.fillna([idx[0]])
idx = index.copy(deep=True)
values = np.asarray(idx.values)
if isinstance(index, DatetimeIndexOpsMixin):
values[1] = iNaT
elif isinstance(index, (Int64Index, UInt64Index)):
return
else:
values[1] = np.nan
if isinstance(index, PeriodIndex):
idx = type(index)(values, freq=index.freq)
else:
idx = type(index)(values)
expected = np.array([False] * len(idx), dtype=bool)
expected[1] = True
tm.assert_numpy_array_equal(idx._isnan, expected)
assert idx.hasnans is True
def test_nulls(self, index):
# this is really a smoke test for the methods
# as these are adequately tested for function elsewhere
if len(index) == 0:
tm.assert_numpy_array_equal(index.isna(), np.array([], dtype=bool))
elif isinstance(index, MultiIndex):
idx = index.copy()
msg = "isna is not defined for MultiIndex"
with pytest.raises(NotImplementedError, match=msg):
idx.isna()
elif not index.hasnans:
tm.assert_numpy_array_equal(index.isna(), np.zeros(len(index), dtype=bool))
tm.assert_numpy_array_equal(index.notna(), np.ones(len(index), dtype=bool))
else:
result = isna(index)
tm.assert_numpy_array_equal(index.isna(), result)
tm.assert_numpy_array_equal(index.notna(), ~result)
def test_empty(self):
# GH 15270
index = self.create_index()
assert not index.empty
assert index[:0].empty
def test_join_self_unique(self, join_type):
index = self.create_index()
if index.is_unique:
joined = index.join(index, how=join_type)
assert (index == joined).all()
def test_map(self):
# callable
index = self.create_index()
# we don't infer UInt64
if isinstance(index, pd.UInt64Index):
expected = index.astype("int64")
else:
expected = index
result = index.map(lambda x: x)
# For RangeIndex we convert to Int64Index
tm.assert_index_equal(result, expected)
@pytest.mark.parametrize(
"mapper",
[
lambda values, index: {i: e for e, i in zip(values, index)},
lambda values, index: Series(values, index),
],
)
def test_map_dictlike(self, mapper):
index = self.create_index()
if isinstance(index, (pd.CategoricalIndex, pd.IntervalIndex)):
pytest.skip(f"skipping tests for {type(index)}")
identity = mapper(index.values, index)
# we don't infer to UInt64 for a dict
if isinstance(index, pd.UInt64Index) and isinstance(identity, dict):
expected = index.astype("int64")
else:
expected = index
result = index.map(identity)
# For RangeIndex we convert to Int64Index
tm.assert_index_equal(result, expected)
# empty mappable
expected = Index([np.nan] * len(index))
result = index.map(mapper(expected, index))
tm.assert_index_equal(result, expected)
def test_map_str(self):
# GH 31202
index = self.create_index()
result = index.map(str)
expected = Index([str(x) for x in index], dtype=object)
tm.assert_index_equal(result, expected)
def test_putmask_with_wrong_mask(self):
# GH18368
index = self.create_index()
fill = index[0]
msg = "putmask: mask and data must be the same size"
with pytest.raises(ValueError, match=msg):
index.putmask(np.ones(len(index) + 1, np.bool_), fill)
with pytest.raises(ValueError, match=msg):
index.putmask(np.ones(len(index) - 1, np.bool_), fill)
with pytest.raises(ValueError, match=msg):
index.putmask("foo", fill)
@pytest.mark.parametrize("copy", [True, False])
@pytest.mark.parametrize("name", [None, "foo"])
@pytest.mark.parametrize("ordered", [True, False])
def test_astype_category(self, copy, name, ordered):
# GH 18630
index = self.create_index()
if name:
index = index.rename(name)
# standard categories
dtype = CategoricalDtype(ordered=ordered)
result = index.astype(dtype, copy=copy)
expected = CategoricalIndex(index.values, name=name, ordered=ordered)
tm.assert_index_equal(result, expected)
# non-standard categories
dtype = CategoricalDtype(index.unique().tolist()[:-1], ordered)
result = index.astype(dtype, copy=copy)
expected = CategoricalIndex(index.values, name=name, dtype=dtype)
tm.assert_index_equal(result, expected)
if ordered is False:
# dtype='category' defaults to ordered=False, so only test once
result = index.astype("category", copy=copy)
expected = CategoricalIndex(index.values, name=name)
tm.assert_index_equal(result, expected)
def test_is_unique(self):
# initialize a unique index
index = self.create_index().drop_duplicates()
assert index.is_unique is True
# empty index should be unique
index_empty = index[:0]
assert index_empty.is_unique is True
# test basic dupes
index_dup = index.insert(0, index[0])
assert index_dup.is_unique is False
# single NA should be unique
index_na = index.insert(0, np.nan)
assert index_na.is_unique is True
# multiple NA should not be unique
index_na_dup = index_na.insert(0, np.nan)
assert index_na_dup.is_unique is False
@pytest.mark.arm_slow
def test_engine_reference_cycle(self):
# GH27585
index = self.create_index()
nrefs_pre = len(gc.get_referrers(index))
index._engine
assert len(gc.get_referrers(index)) == nrefs_pre
def test_getitem_2d_deprecated(self):
# GH#30588
idx = self.create_index()
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
res = idx[:, None]
assert isinstance(res, np.ndarray), type(res)
def test_contains_requires_hashable_raises(self):
idx = self.create_index()
msg = "unhashable type: 'list'"
with pytest.raises(TypeError, match=msg):
[] in idx
msg = "|".join(
[
r"unhashable type: 'dict'",
r"must be real number, not dict",
r"an integer is required",
r"\{\}",
r"pandas\._libs\.interval\.IntervalTree' is not iterable",
]
)
with pytest.raises(TypeError, match=msg):
{} in idx._engine
def test_copy_shares_cache(self):
# GH32898, GH36840
idx = self.create_index()
idx.get_loc(idx[0]) # populates the _cache.
copy = idx.copy()
assert copy._cache is idx._cache
def test_shallow_copy_shares_cache(self):
# GH32669, GH36840
idx = self.create_index()
idx.get_loc(idx[0]) # populates the _cache.
shallow_copy = idx._shallow_copy()
assert shallow_copy._cache is idx._cache
shallow_copy = idx._shallow_copy(idx._data)
assert shallow_copy._cache is not idx._cache
assert shallow_copy._cache == {}