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Version:
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# -*- coding: utf-8 -*-
import pytest
from datetime import datetime
from pandas.compat import range, PY3
import numpy as np
from pandas import (date_range, Series, Index, Float64Index,
Int64Index, UInt64Index, RangeIndex)
import pandas.util.testing as tm
import pandas as pd
from pandas._libs.tslib import Timestamp, Timedelta
from pandas.tests.indexes.common import Base
def full_like(array, value):
"""Compatibility for numpy<1.8.0
"""
ret = np.empty(array.shape, dtype=np.array(value).dtype)
ret.fill(value)
return ret
class TestIndexArithmeticWithTimedeltaScalar(object):
@pytest.mark.parametrize('index', [
Int64Index(range(1, 11)),
UInt64Index(range(1, 11)),
Float64Index(range(1, 11)),
RangeIndex(1, 11)])
@pytest.mark.parametrize('scalar_td', [Timedelta(days=1),
Timedelta(days=1).to_timedelta64(),
Timedelta(days=1).to_pytimedelta()])
def test_index_mul_timedelta(self, scalar_td, index):
# GH#19333
expected = pd.timedelta_range('1 days', '10 days')
result = index * scalar_td
tm.assert_index_equal(result, expected)
commute = scalar_td * index
tm.assert_index_equal(commute, expected)
@pytest.mark.parametrize('index', [Int64Index(range(1, 3)),
UInt64Index(range(1, 3)),
Float64Index(range(1, 3)),
RangeIndex(1, 3)])
@pytest.mark.parametrize('scalar_td', [Timedelta(days=1),
Timedelta(days=1).to_timedelta64(),
Timedelta(days=1).to_pytimedelta()])
def test_index_rdiv_timedelta(self, scalar_td, index):
expected = pd.TimedeltaIndex(['1 Day', '12 Hours'])
result = scalar_td / index
tm.assert_index_equal(result, expected)
with pytest.raises(TypeError):
index / scalar_td
class Numeric(Base):
def test_can_hold_identifiers(self):
idx = self.create_index()
key = idx[0]
assert idx._can_hold_identifiers_and_holds_name(key) is False
def test_numeric_compat(self):
pass # override Base method
def test_mul_int(self):
idx = self.create_index()
result = idx * 1
tm.assert_index_equal(result, idx)
def test_rmul_int(self):
idx = self.create_index()
result = 1 * idx
tm.assert_index_equal(result, idx)
def test_div_int(self):
idx = self.create_index()
# truediv under PY3
result = idx / 1
expected = idx
if PY3:
expected = expected.astype('float64')
tm.assert_index_equal(result, expected)
result = idx / 2
if PY3:
expected = expected.astype('float64')
expected = Index(idx.values / 2)
tm.assert_index_equal(result, expected)
def test_floordiv_int(self):
idx = self.create_index()
result = idx // 1
tm.assert_index_equal(result, idx)
def test_mul_int_array(self):
idx = self.create_index()
didx = idx * idx
result = idx * np.array(5, dtype='int64')
tm.assert_index_equal(result, idx * 5)
arr_dtype = 'uint64' if isinstance(idx, UInt64Index) else 'int64'
result = idx * np.arange(5, dtype=arr_dtype)
tm.assert_index_equal(result, didx)
def test_mul_int_series(self):
idx = self.create_index()
didx = idx * idx
arr_dtype = 'uint64' if isinstance(idx, UInt64Index) else 'int64'
result = idx * Series(np.arange(5, dtype=arr_dtype))
tm.assert_series_equal(result, Series(didx))
def test_mul_float_series(self):
idx = self.create_index()
rng5 = np.arange(5, dtype='float64')
result = idx * Series(rng5 + 0.1)
expected = Series(rng5 * (rng5 + 0.1))
tm.assert_series_equal(result, expected)
def test_mul_index(self):
idx = self.create_index()
# in general not true for RangeIndex
if not isinstance(idx, RangeIndex):
result = idx * idx
tm.assert_index_equal(result, idx ** 2)
def test_mul_datelike_raises(self):
idx = self.create_index()
with pytest.raises(TypeError):
idx * date_range('20130101', periods=5)
def test_mul_size_mismatch_raises(self):
idx = self.create_index()
with pytest.raises(ValueError):
idx * idx[0:3]
with pytest.raises(ValueError):
idx * np.array([1, 2])
def test_divmod(self):
idx = self.create_index()
result = divmod(idx, 2)
with np.errstate(all='ignore'):
div, mod = divmod(idx.values, 2)
expected = Index(div), Index(mod)
for r, e in zip(result, expected):
tm.assert_index_equal(r, e)
result = divmod(idx, full_like(idx.values, 2))
with np.errstate(all='ignore'):
div, mod = divmod(idx.values, full_like(idx.values, 2))
expected = Index(div), Index(mod)
for r, e in zip(result, expected):
tm.assert_index_equal(r, e)
def test_pow_float(self):
# test power calculations both ways, GH 14973
idx = self.create_index()
expected = pd.Float64Index(idx.values**2.0)
result = idx**2.0
tm.assert_index_equal(result, expected)
def test_rpow_float(self):
# test power calculations both ways, GH 14973
idx = self.create_index()
expected = pd.Float64Index(2.0**idx.values)
result = 2.0**idx
tm.assert_index_equal(result, expected)
@pytest.mark.xfail(reason='GH#19252 Series has no __rdivmod__')
def test_divmod_series(self):
idx = self.create_index()
result = divmod(idx, Series(full_like(idx.values, 2)))
with np.errstate(all='ignore'):
div, mod = divmod(idx.values, full_like(idx.values, 2))
expected = Series(div), Series(mod)
for r, e in zip(result, expected):
tm.assert_series_equal(r, e)
def test_div_zero(self, zero):
idx = self.create_index()
expected = Index([np.nan, np.inf, np.inf, np.inf, np.inf],
dtype=np.float64)
result = idx / zero
tm.assert_index_equal(result, expected)
ser_compat = Series(idx).astype('i8') / np.array(zero).astype('i8')
tm.assert_series_equal(ser_compat, Series(result))
def test_floordiv_zero(self, zero):
idx = self.create_index()
expected = Index([np.nan, np.inf, np.inf, np.inf, np.inf],
dtype=np.float64)
result = idx // zero
tm.assert_index_equal(result, expected)
ser_compat = Series(idx).astype('i8') // np.array(zero).astype('i8')
tm.assert_series_equal(ser_compat, Series(result))
def test_mod_zero(self, zero):
idx = self.create_index()
expected = Index([np.nan, np.nan, np.nan, np.nan, np.nan],
dtype=np.float64)
result = idx % zero
tm.assert_index_equal(result, expected)
ser_compat = Series(idx).astype('i8') % np.array(zero).astype('i8')
tm.assert_series_equal(ser_compat, Series(result))
def test_divmod_zero(self, zero):
idx = self.create_index()
exleft = Index([np.nan, np.inf, np.inf, np.inf, np.inf],
dtype=np.float64)
exright = Index([np.nan, np.nan, np.nan, np.nan, np.nan],
dtype=np.float64)
result = divmod(idx, zero)
tm.assert_index_equal(result[0], exleft)
tm.assert_index_equal(result[1], exright)
def test_explicit_conversions(self):
# GH 8608
# add/sub are overridden explicitly for Float/Int Index
idx = self._holder(np.arange(5, dtype='int64'))
# float conversions
arr = np.arange(5, dtype='int64') * 3.2
expected = Float64Index(arr)
fidx = idx * 3.2
tm.assert_index_equal(fidx, expected)
fidx = 3.2 * idx
tm.assert_index_equal(fidx, expected)
# interops with numpy arrays
expected = Float64Index(arr)
a = np.zeros(5, dtype='float64')
result = fidx - a
tm.assert_index_equal(result, expected)
expected = Float64Index(-arr)
a = np.zeros(5, dtype='float64')
result = a - fidx
tm.assert_index_equal(result, expected)
def test_ufunc_compat(self):
idx = self._holder(np.arange(5, dtype='int64'))
result = np.sin(idx)
expected = Float64Index(np.sin(np.arange(5, dtype='int64')))
tm.assert_index_equal(result, expected)
def test_index_groupby(self):
int_idx = Index(range(6))
float_idx = Index(np.arange(0, 0.6, 0.1))
obj_idx = Index('A B C D E F'.split())
dt_idx = pd.date_range('2013-01-01', freq='M', periods=6)
for idx in [int_idx, float_idx, obj_idx, dt_idx]:
to_groupby = np.array([1, 2, np.nan, np.nan, 2, 1])
tm.assert_dict_equal(idx.groupby(to_groupby),
{1.0: idx[[0, 5]], 2.0: idx[[1, 4]]})
to_groupby = Index([datetime(2011, 11, 1),
datetime(2011, 12, 1),
pd.NaT,
pd.NaT,
datetime(2011, 12, 1),
datetime(2011, 11, 1)],
tz='UTC').values
ex_keys = [Timestamp('2011-11-01'), Timestamp('2011-12-01')]
expected = {ex_keys[0]: idx[[0, 5]],
ex_keys[1]: idx[[1, 4]]}
tm.assert_dict_equal(idx.groupby(to_groupby), expected)
def test_modulo(self):
# GH 9244
index = self.create_index()
expected = Index(index.values % 2)
tm.assert_index_equal(index % 2, expected)
@pytest.mark.parametrize('klass', [list, tuple, np.array, Series])
def test_where(self, klass):
i = self.create_index()
cond = [True] * len(i)
expected = i
result = i.where(klass(cond))
cond = [False] + [True] * (len(i) - 1)
expected = Float64Index([i._na_value] + i[1:].tolist())
result = i.where(klass(cond))
tm.assert_index_equal(result, expected)
def test_insert(self):
# GH 18295 (test missing)
expected = Float64Index([0, np.nan, 1, 2, 3, 4])
for na in (np.nan, pd.NaT, None):
result = self.create_index().insert(1, na)
tm.assert_index_equal(result, expected)
class TestFloat64Index(Numeric):
_holder = Float64Index
def setup_method(self, method):
self.indices = dict(mixed=Float64Index([1.5, 2, 3, 4, 5]),
float=Float64Index(np.arange(5) * 2.5),
mixed_dec=Float64Index([5, 4, 3, 2, 1.5]),
float_dec=Float64Index(np.arange(4, -1, -1) * 2.5))
self.setup_indices()
def create_index(self):
return Float64Index(np.arange(5, dtype='float64'))
def test_repr_roundtrip(self):
for ind in (self.mixed, self.float):
tm.assert_index_equal(eval(repr(ind)), ind)
def check_is_index(self, i):
assert isinstance(i, Index)
assert not isinstance(i, Float64Index)
def check_coerce(self, a, b, is_float_index=True):
assert a.equals(b)
tm.assert_index_equal(a, b, exact=False)
if is_float_index:
assert isinstance(b, Float64Index)
else:
self.check_is_index(b)
def test_constructor(self):
# explicit construction
index = Float64Index([1, 2, 3, 4, 5])
assert isinstance(index, Float64Index)
expected = np.array([1, 2, 3, 4, 5], dtype='float64')
tm.assert_numpy_array_equal(index.values, expected)
index = Float64Index(np.array([1, 2, 3, 4, 5]))
assert isinstance(index, Float64Index)
index = Float64Index([1., 2, 3, 4, 5])
assert isinstance(index, Float64Index)
index = Float64Index(np.array([1., 2, 3, 4, 5]))
assert isinstance(index, Float64Index)
assert index.dtype == float
index = Float64Index(np.array([1., 2, 3, 4, 5]), dtype=np.float32)
assert isinstance(index, Float64Index)
assert index.dtype == np.float64
index = Float64Index(np.array([1, 2, 3, 4, 5]), dtype=np.float32)
assert isinstance(index, Float64Index)
assert index.dtype == np.float64
# nan handling
result = Float64Index([np.nan, np.nan])
assert pd.isna(result.values).all()
result = Float64Index(np.array([np.nan]))
assert pd.isna(result.values).all()
result = Index(np.array([np.nan]))
assert pd.isna(result.values).all()
def test_constructor_invalid(self):
# invalid
pytest.raises(TypeError, Float64Index, 0.)
pytest.raises(TypeError, Float64Index, ['a', 'b', 0.])
pytest.raises(TypeError, Float64Index, [Timestamp('20130101')])
def test_constructor_coerce(self):
self.check_coerce(self.mixed, Index([1.5, 2, 3, 4, 5]))
self.check_coerce(self.float, Index(np.arange(5) * 2.5))
self.check_coerce(self.float, Index(np.array(
np.arange(5) * 2.5, dtype=object)))
def test_constructor_explicit(self):
# these don't auto convert
self.check_coerce(self.float,
Index((np.arange(5) * 2.5), dtype=object),
is_float_index=False)
self.check_coerce(self.mixed, Index(
[1.5, 2, 3, 4, 5], dtype=object), is_float_index=False)
def test_astype(self):
result = self.float.astype(object)
assert result.equals(self.float)
assert self.float.equals(result)
self.check_is_index(result)
i = self.mixed.copy()
i.name = 'foo'
result = i.astype(object)
assert result.equals(i)
assert i.equals(result)
self.check_is_index(result)
# GH 12881
# a float astype int
for dtype in ['int16', 'int32', 'int64']:
i = Float64Index([0, 1, 2])
result = i.astype(dtype)
expected = Int64Index([0, 1, 2])
tm.assert_index_equal(result, expected)
i = Float64Index([0, 1.1, 2])
result = i.astype(dtype)
expected = Int64Index([0, 1, 2])
tm.assert_index_equal(result, expected)
for dtype in ['float32', 'float64']:
i = Float64Index([0, 1, 2])
result = i.astype(dtype)
expected = i
tm.assert_index_equal(result, expected)
i = Float64Index([0, 1.1, 2])
result = i.astype(dtype)
expected = Index(i.values.astype(dtype))
tm.assert_index_equal(result, expected)
# invalid
for dtype in ['M8[ns]', 'm8[ns]']:
pytest.raises(TypeError, lambda: i.astype(dtype))
# GH 13149
for dtype in ['int16', 'int32', 'int64']:
i = Float64Index([0, 1.1, np.NAN])
pytest.raises(ValueError, lambda: i.astype(dtype))
def test_equals_numeric(self):
i = Float64Index([1.0, 2.0])
assert i.equals(i)
assert i.identical(i)
i2 = Float64Index([1.0, 2.0])
assert i.equals(i2)
i = Float64Index([1.0, np.nan])
assert i.equals(i)
assert i.identical(i)
i2 = Float64Index([1.0, np.nan])
assert i.equals(i2)
def test_get_indexer(self):
idx = Float64Index([0.0, 1.0, 2.0])
tm.assert_numpy_array_equal(idx.get_indexer(idx),
np.array([0, 1, 2], dtype=np.intp))
target = [-0.1, 0.5, 1.1]
tm.assert_numpy_array_equal(idx.get_indexer(target, 'pad'),
np.array([-1, 0, 1], dtype=np.intp))
tm.assert_numpy_array_equal(idx.get_indexer(target, 'backfill'),
np.array([0, 1, 2], dtype=np.intp))
tm.assert_numpy_array_equal(idx.get_indexer(target, 'nearest'),
np.array([0, 1, 1], dtype=np.intp))
def test_get_loc(self):
idx = Float64Index([0.0, 1.0, 2.0])
for method in [None, 'pad', 'backfill', 'nearest']:
assert idx.get_loc(1, method) == 1
if method is not None:
assert idx.get_loc(1, method, tolerance=0) == 1
for method, loc in [('pad', 1), ('backfill', 2), ('nearest', 1)]:
assert idx.get_loc(1.1, method) == loc
assert idx.get_loc(1.1, method, tolerance=0.9) == loc
pytest.raises(KeyError, idx.get_loc, 'foo')
pytest.raises(KeyError, idx.get_loc, 1.5)
pytest.raises(KeyError, idx.get_loc, 1.5, method='pad',
tolerance=0.1)
with tm.assert_raises_regex(ValueError, 'must be numeric'):
idx.get_loc(1.4, method='nearest', tolerance='foo')
with pytest.raises(ValueError, match='must contain numeric elements'):
idx.get_loc(1.4, method='nearest', tolerance=np.array(['foo']))
with pytest.raises(
ValueError,
match='tolerance size must match target index size'):
idx.get_loc(1.4, method='nearest', tolerance=np.array([1, 2]))
def test_get_loc_na(self):
idx = Float64Index([np.nan, 1, 2])
assert idx.get_loc(1) == 1
assert idx.get_loc(np.nan) == 0
idx = Float64Index([np.nan, 1, np.nan])
assert idx.get_loc(1) == 1
# representable by slice [0:2:2]
# pytest.raises(KeyError, idx.slice_locs, np.nan)
sliced = idx.slice_locs(np.nan)
assert isinstance(sliced, tuple)
assert sliced == (0, 3)
# not representable by slice
idx = Float64Index([np.nan, 1, np.nan, np.nan])
assert idx.get_loc(1) == 1
pytest.raises(KeyError, idx.slice_locs, np.nan)
def test_get_loc_missing_nan(self):
# GH 8569
idx = Float64Index([1, 2])
assert idx.get_loc(1) == 0
pytest.raises(KeyError, idx.get_loc, 3)
pytest.raises(KeyError, idx.get_loc, np.nan)
pytest.raises(KeyError, idx.get_loc, [np.nan])
def test_contains_nans(self):
i = Float64Index([1.0, 2.0, np.nan])
assert np.nan in i
def test_contains_not_nans(self):
i = Float64Index([1.0, 2.0, np.nan])
assert 1.0 in i
def test_doesnt_contain_all_the_things(self):
i = Float64Index([np.nan])
assert not i.isin([0]).item()
assert not i.isin([1]).item()
assert i.isin([np.nan]).item()
def test_nan_multiple_containment(self):
i = Float64Index([1.0, np.nan])
tm.assert_numpy_array_equal(i.isin([1.0]), np.array([True, False]))
tm.assert_numpy_array_equal(i.isin([2.0, np.pi]),
np.array([False, False]))
tm.assert_numpy_array_equal(i.isin([np.nan]), np.array([False, True]))
tm.assert_numpy_array_equal(i.isin([1.0, np.nan]),
np.array([True, True]))
i = Float64Index([1.0, 2.0])
tm.assert_numpy_array_equal(i.isin([np.nan]), np.array([False, False]))
def test_astype_from_object(self):
index = Index([1.0, np.nan, 0.2], dtype='object')
result = index.astype(float)
expected = Float64Index([1.0, np.nan, 0.2])
assert result.dtype == expected.dtype
tm.assert_index_equal(result, expected)
def test_fillna_float64(self):
# GH 11343
idx = Index([1.0, np.nan, 3.0], dtype=float, name='x')
# can't downcast
exp = Index([1.0, 0.1, 3.0], name='x')
tm.assert_index_equal(idx.fillna(0.1), exp)
# downcast
exp = Float64Index([1.0, 2.0, 3.0], name='x')
tm.assert_index_equal(idx.fillna(2), exp)
# object
exp = Index([1.0, 'obj', 3.0], name='x')
tm.assert_index_equal(idx.fillna('obj'), exp)
def test_take_fill_value(self):
# GH 12631
idx = pd.Float64Index([1., 2., 3.], name='xxx')
result = idx.take(np.array([1, 0, -1]))
expected = pd.Float64Index([2., 1., 3.], name='xxx')
tm.assert_index_equal(result, expected)
# fill_value
result = idx.take(np.array([1, 0, -1]), fill_value=True)
expected = pd.Float64Index([2., 1., np.nan], name='xxx')
tm.assert_index_equal(result, expected)
# allow_fill=False
result = idx.take(np.array([1, 0, -1]), allow_fill=False,
fill_value=True)
expected = pd.Float64Index([2., 1., 3.], name='xxx')
tm.assert_index_equal(result, expected)
msg = ('When allow_fill=True and fill_value is not None, '
'all indices must be >= -1')
with tm.assert_raises_regex(ValueError, msg):
idx.take(np.array([1, 0, -2]), fill_value=True)
with tm.assert_raises_regex(ValueError, msg):
idx.take(np.array([1, 0, -5]), fill_value=True)
with pytest.raises(IndexError):
idx.take(np.array([1, -5]))
class NumericInt(Numeric):
def test_view(self, indices):
super(NumericInt, self).test_view(indices)
i = self._holder([], name='Foo')
i_view = i.view()
assert i_view.name == 'Foo'
i_view = i.view(self._dtype)
tm.assert_index_equal(i, self._holder(i_view, name='Foo'))
i_view = i.view(self._holder)
tm.assert_index_equal(i, self._holder(i_view, name='Foo'))
def test_is_monotonic(self):
assert self.index.is_monotonic
assert self.index.is_monotonic_increasing
assert self.index._is_strictly_monotonic_increasing
assert not self.index.is_monotonic_decreasing
assert not self.index._is_strictly_monotonic_decreasing
index = self._holder([4, 3, 2, 1])
assert not index.is_monotonic
assert not index._is_strictly_monotonic_increasing
assert index._is_strictly_monotonic_decreasing
index = self._holder([1])
assert index.is_monotonic
assert index.is_monotonic_increasing
assert index.is_monotonic_decreasing
assert index._is_strictly_monotonic_increasing
assert index._is_strictly_monotonic_decreasing
def test_is_strictly_monotonic(self):
index = self._holder([1, 1, 2, 3])
assert index.is_monotonic_increasing
assert not index._is_strictly_monotonic_increasing
index = self._holder([3, 2, 1, 1])
assert index.is_monotonic_decreasing
assert not index._is_strictly_monotonic_decreasing
index = self._holder([1, 1])
assert index.is_monotonic_increasing
assert index.is_monotonic_decreasing
assert not index._is_strictly_monotonic_increasing
assert not index._is_strictly_monotonic_decreasing
def test_logical_compat(self):
idx = self.create_index()
assert idx.all() == idx.values.all()
assert idx.any() == idx.values.any()
def test_identical(self):
i = Index(self.index.copy())
assert i.identical(self.index)
same_values_different_type = Index(i, dtype=object)
assert not i.identical(same_values_different_type)
i = self.index.copy(dtype=object)
i = i.rename('foo')
same_values = Index(i, dtype=object)
assert same_values.identical(i)
assert not i.identical(self.index)
assert Index(same_values, name='foo', dtype=object).identical(i)
assert not self.index.copy(dtype=object).identical(
self.index.copy(dtype=self._dtype))
def test_join_non_unique(self):
left = Index([4, 4, 3, 3])
joined, lidx, ridx = left.join(left, return_indexers=True)
exp_joined = Index([3, 3, 3, 3, 4, 4, 4, 4])
tm.assert_index_equal(joined, exp_joined)
exp_lidx = np.array([2, 2, 3, 3, 0, 0, 1, 1], dtype=np.intp)
tm.assert_numpy_array_equal(lidx, exp_lidx)
exp_ridx = np.array([2, 3, 2, 3, 0, 1, 0, 1], dtype=np.intp)
tm.assert_numpy_array_equal(ridx, exp_ridx)
def test_join_self(self):
kinds = 'outer', 'inner', 'left', 'right'
for kind in kinds:
joined = self.index.join(self.index, how=kind)
assert self.index is joined
def test_union_noncomparable(self):
from datetime import datetime, timedelta
# corner case, non-Int64Index
now = datetime.now()
other = Index([now + timedelta(i) for i in range(4)], dtype=object)
result = self.index.union(other)
expected = Index(np.concatenate((self.index, other)))
tm.assert_index_equal(result, expected)
result = other.union(self.index)
expected = Index(np.concatenate((other, self.index)))
tm.assert_index_equal(result, expected)
def test_cant_or_shouldnt_cast(self):
# can't
data = ['foo', 'bar', 'baz']
pytest.raises(TypeError, self._holder, data)
# shouldn't
data = ['0', '1', '2']
pytest.raises(TypeError, self._holder, data)
def test_view_index(self):
self.index.view(Index)
def test_prevent_casting(self):
result = self.index.astype('O')
assert result.dtype == np.object_
def test_take_preserve_name(self):
index = self._holder([1, 2, 3, 4], name='foo')
taken = index.take([3, 0, 1])
assert index.name == taken.name
def test_take_fill_value(self):
# see gh-12631
idx = self._holder([1, 2, 3], name='xxx')
result = idx.take(np.array([1, 0, -1]))
expected = self._holder([2, 1, 3], name='xxx')
tm.assert_index_equal(result, expected)
name = self._holder.__name__
msg = ("Unable to fill values because "
"{name} cannot contain NA").format(name=name)
# fill_value=True
with tm.assert_raises_regex(ValueError, msg):
idx.take(np.array([1, 0, -1]), fill_value=True)
# allow_fill=False
result = idx.take(np.array([1, 0, -1]), allow_fill=False,
fill_value=True)
expected = self._holder([2, 1, 3], name='xxx')
tm.assert_index_equal(result, expected)
with tm.assert_raises_regex(ValueError, msg):
idx.take(np.array([1, 0, -2]), fill_value=True)
with tm.assert_raises_regex(ValueError, msg):
idx.take(np.array([1, 0, -5]), fill_value=True)
with pytest.raises(IndexError):
idx.take(np.array([1, -5]))
def test_slice_keep_name(self):
idx = self._holder([1, 2], name='asdf')
assert idx.name == idx[1:].name
def test_ufunc_coercions(self):
idx = self._holder([1, 2, 3, 4, 5], name='x')
result = np.sqrt(idx)
assert isinstance(result, Float64Index)
exp = Float64Index(np.sqrt(np.array([1, 2, 3, 4, 5])), name='x')
tm.assert_index_equal(result, exp)
result = np.divide(idx, 2.)
assert isinstance(result, Float64Index)
exp = Float64Index([0.5, 1., 1.5, 2., 2.5], name='x')
tm.assert_index_equal(result, exp)
# _evaluate_numeric_binop
result = idx + 2.
assert isinstance(result, Float64Index)
exp = Float64Index([3., 4., 5., 6., 7.], name='x')
tm.assert_index_equal(result, exp)
result = idx - 2.
assert isinstance(result, Float64Index)
exp = Float64Index([-1., 0., 1., 2., 3.], name='x')
tm.assert_index_equal(result, exp)
result = idx * 1.
assert isinstance(result, Float64Index)
exp = Float64Index([1., 2., 3., 4., 5.], name='x')
tm.assert_index_equal(result, exp)
result = idx / 2.
assert isinstance(result, Float64Index)
exp = Float64Index([0.5, 1., 1.5, 2., 2.5], name='x')
tm.assert_index_equal(result, exp)
class TestInt64Index(NumericInt):
_dtype = 'int64'
_holder = Int64Index
def setup_method(self, method):
self.indices = dict(index=Int64Index(np.arange(0, 20, 2)),
index_dec=Int64Index(np.arange(19, -1, -1)))
self.setup_indices()
def create_index(self):
return Int64Index(np.arange(5, dtype='int64'))
def test_constructor(self):
# pass list, coerce fine
index = Int64Index([-5, 0, 1, 2])
expected = Index([-5, 0, 1, 2], dtype=np.int64)
tm.assert_index_equal(index, expected)
# from iterable
index = Int64Index(iter([-5, 0, 1, 2]))
tm.assert_index_equal(index, expected)
# scalar raise Exception
pytest.raises(TypeError, Int64Index, 5)
# copy
arr = self.index.values
new_index = Int64Index(arr, copy=True)
tm.assert_index_equal(new_index, self.index)
val = arr[0] + 3000
# this should not change index
arr[0] = val
assert new_index[0] != val
# interpret list-like
expected = Int64Index([5, 0])
for cls in [Index, Int64Index]:
for idx in [cls([5, 0], dtype='int64'),
cls(np.array([5, 0]), dtype='int64'),
cls(Series([5, 0]), dtype='int64')]:
tm.assert_index_equal(idx, expected)
def test_constructor_corner(self):
arr = np.array([1, 2, 3, 4], dtype=object)
index = Int64Index(arr)
assert index.values.dtype == np.int64
tm.assert_index_equal(index, Index(arr))
# preventing casting
arr = np.array([1, '2', 3, '4'], dtype=object)
with tm.assert_raises_regex(TypeError, 'casting'):
Int64Index(arr)
arr_with_floats = [0, 2, 3, 4, 5, 1.25, 3, -1]
with tm.assert_raises_regex(TypeError, 'casting'):
Int64Index(arr_with_floats)
def test_coerce_list(self):
# coerce things
arr = Index([1, 2, 3, 4])
assert isinstance(arr, Int64Index)
# but not if explicit dtype passed
arr = Index([1, 2, 3, 4], dtype=object)
assert isinstance(arr, Index)
def test_get_indexer(self):
target = Int64Index(np.arange(10))
indexer = self.index.get_indexer(target)
expected = np.array([0, -1, 1, -1, 2, -1, 3, -1, 4, -1], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)
target = Int64Index(np.arange(10))
indexer = self.index.get_indexer(target, method='pad')
expected = np.array([0, 0, 1, 1, 2, 2, 3, 3, 4, 4], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)
target = Int64Index(np.arange(10))
indexer = self.index.get_indexer(target, method='backfill')
expected = np.array([0, 1, 1, 2, 2, 3, 3, 4, 4, 5], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)
def test_intersection(self):
other = Index([1, 2, 3, 4, 5])
result = self.index.intersection(other)
expected = Index(np.sort(np.intersect1d(self.index.values,
other.values)))
tm.assert_index_equal(result, expected)
result = other.intersection(self.index)
expected = Index(np.sort(np.asarray(np.intersect1d(self.index.values,
other.values))))
tm.assert_index_equal(result, expected)
def test_join_inner(self):
other = Int64Index([7, 12, 25, 1, 2, 5])
other_mono = Int64Index([1, 2, 5, 7, 12, 25])
# not monotonic
res, lidx, ridx = self.index.join(other, how='inner',
return_indexers=True)
# no guarantee of sortedness, so sort for comparison purposes
ind = res.argsort()
res = res.take(ind)
lidx = lidx.take(ind)
ridx = ridx.take(ind)
eres = Int64Index([2, 12])
elidx = np.array([1, 6], dtype=np.intp)
eridx = np.array([4, 1], dtype=np.intp)
assert isinstance(res, Int64Index)
tm.assert_index_equal(res, eres)
tm.assert_numpy_array_equal(lidx, elidx)
tm.assert_numpy_array_equal(ridx, eridx)
# monotonic
res, lidx, ridx = self.index.join(other_mono, how='inner',
return_indexers=True)
res2 = self.index.intersection(other_mono)
tm.assert_index_equal(res, res2)
elidx = np.array([1, 6], dtype=np.intp)
eridx = np.array([1, 4], dtype=np.intp)
assert isinstance(res, Int64Index)
tm.assert_index_equal(res, eres)
tm.assert_numpy_array_equal(lidx, elidx)
tm.assert_numpy_array_equal(ridx, eridx)
def test_join_left(self):
other = Int64Index([7, 12, 25, 1, 2, 5])
other_mono = Int64Index([1, 2, 5, 7, 12, 25])
# not monotonic
res, lidx, ridx = self.index.join(other, how='left',
return_indexers=True)
eres = self.index
eridx = np.array([-1, 4, -1, -1, -1, -1, 1, -1, -1, -1],
dtype=np.intp)
assert isinstance(res, Int64Index)
tm.assert_index_equal(res, eres)
assert lidx is None
tm.assert_numpy_array_equal(ridx, eridx)
# monotonic
res, lidx, ridx = self.index.join(other_mono, how='left',
return_indexers=True)
eridx = np.array([-1, 1, -1, -1, -1, -1, 4, -1, -1, -1],
dtype=np.intp)
assert isinstance(res, Int64Index)
tm.assert_index_equal(res, eres)
assert lidx is None
tm.assert_numpy_array_equal(ridx, eridx)
# non-unique
idx = Index([1, 1, 2, 5])
idx2 = Index([1, 2, 5, 7, 9])
res, lidx, ridx = idx2.join(idx, how='left', return_indexers=True)
eres = Index([1, 1, 2, 5, 7, 9]) # 1 is in idx2, so it should be x2
eridx = np.array([0, 1, 2, 3, -1, -1], dtype=np.intp)
elidx = np.array([0, 0, 1, 2, 3, 4], dtype=np.intp)
tm.assert_index_equal(res, eres)
tm.assert_numpy_array_equal(lidx, elidx)
tm.assert_numpy_array_equal(ridx, eridx)
def test_join_right(self):
other = Int64Index([7, 12, 25, 1, 2, 5])
other_mono = Int64Index([1, 2, 5, 7, 12, 25])
# not monotonic
res, lidx, ridx = self.index.join(other, how='right',
return_indexers=True)
eres = other
elidx = np.array([-1, 6, -1, -1, 1, -1], dtype=np.intp)
assert isinstance(other, Int64Index)
tm.assert_index_equal(res, eres)
tm.assert_numpy_array_equal(lidx, elidx)
assert ridx is None
# monotonic
res, lidx, ridx = self.index.join(other_mono, how='right',
return_indexers=True)
eres = other_mono
elidx = np.array([-1, 1, -1, -1, 6, -1], dtype=np.intp)
assert isinstance(other, Int64Index)
tm.assert_index_equal(res, eres)
tm.assert_numpy_array_equal(lidx, elidx)
assert ridx is None
# non-unique
idx = Index([1, 1, 2, 5])
idx2 = Index([1, 2, 5, 7, 9])
res, lidx, ridx = idx.join(idx2, how='right', return_indexers=True)
eres = Index([1, 1, 2, 5, 7, 9]) # 1 is in idx2, so it should be x2
elidx = np.array([0, 1, 2, 3, -1, -1], dtype=np.intp)
eridx = np.array([0, 0, 1, 2, 3, 4], dtype=np.intp)
tm.assert_index_equal(res, eres)
tm.assert_numpy_array_equal(lidx, elidx)
tm.assert_numpy_array_equal(ridx, eridx)
def test_join_non_int_index(self):
other = Index([3, 6, 7, 8, 10], dtype=object)
outer = self.index.join(other, how='outer')
outer2 = other.join(self.index, how='outer')
expected = Index([0, 2, 3, 4, 6, 7, 8, 10, 12, 14, 16, 18])
tm.assert_index_equal(outer, outer2)
tm.assert_index_equal(outer, expected)
inner = self.index.join(other, how='inner')
inner2 = other.join(self.index, how='inner')
expected = Index([6, 8, 10])
tm.assert_index_equal(inner, inner2)
tm.assert_index_equal(inner, expected)
left = self.index.join(other, how='left')
tm.assert_index_equal(left, self.index.astype(object))
left2 = other.join(self.index, how='left')
tm.assert_index_equal(left2, other)
right = self.index.join(other, how='right')
tm.assert_index_equal(right, other)
right2 = other.join(self.index, how='right')
tm.assert_index_equal(right2, self.index.astype(object))
def test_join_outer(self):
other = Int64Index([7, 12, 25, 1, 2, 5])
other_mono = Int64Index([1, 2, 5, 7, 12, 25])
# not monotonic
# guarantee of sortedness
res, lidx, ridx = self.index.join(other, how='outer',
return_indexers=True)
noidx_res = self.index.join(other, how='outer')
tm.assert_index_equal(res, noidx_res)
eres = Int64Index([0, 1, 2, 4, 5, 6, 7, 8, 10, 12, 14, 16, 18, 25])
elidx = np.array([0, -1, 1, 2, -1, 3, -1, 4, 5, 6, 7, 8, 9, -1],
dtype=np.intp)
eridx = np.array([-1, 3, 4, -1, 5, -1, 0, -1, -1, 1, -1, -1, -1, 2],
dtype=np.intp)
assert isinstance(res, Int64Index)
tm.assert_index_equal(res, eres)
tm.assert_numpy_array_equal(lidx, elidx)
tm.assert_numpy_array_equal(ridx, eridx)
# monotonic
res, lidx, ridx = self.index.join(other_mono, how='outer',
return_indexers=True)
noidx_res = self.index.join(other_mono, how='outer')
tm.assert_index_equal(res, noidx_res)
elidx = np.array([0, -1, 1, 2, -1, 3, -1, 4, 5, 6, 7, 8, 9, -1],
dtype=np.intp)
eridx = np.array([-1, 0, 1, -1, 2, -1, 3, -1, -1, 4, -1, -1, -1, 5],
dtype=np.intp)
assert isinstance(res, Int64Index)
tm.assert_index_equal(res, eres)
tm.assert_numpy_array_equal(lidx, elidx)
tm.assert_numpy_array_equal(ridx, eridx)
class TestUInt64Index(NumericInt):
_dtype = 'uint64'
_holder = UInt64Index
def setup_method(self, method):
vals = [2**63, 2**63 + 10, 2**63 + 15, 2**63 + 20, 2**63 + 25]
self.indices = dict(index=UInt64Index(vals),
index_dec=UInt64Index(reversed(vals)))
self.setup_indices()
def create_index(self):
return UInt64Index(np.arange(5, dtype='uint64'))
def test_constructor(self):
idx = UInt64Index([1, 2, 3])
res = Index([1, 2, 3], dtype=np.uint64)
tm.assert_index_equal(res, idx)
idx = UInt64Index([1, 2**63])
res = Index([1, 2**63], dtype=np.uint64)
tm.assert_index_equal(res, idx)
idx = UInt64Index([1, 2**63])
res = Index([1, 2**63])
tm.assert_index_equal(res, idx)
idx = Index([-1, 2**63], dtype=object)
res = Index(np.array([-1, 2**63], dtype=object))
tm.assert_index_equal(res, idx)
def test_get_indexer(self):
target = UInt64Index(np.arange(10).astype('uint64') * 5 + 2**63)
indexer = self.index.get_indexer(target)
expected = np.array([0, -1, 1, 2, 3, 4,
-1, -1, -1, -1], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)
target = UInt64Index(np.arange(10).astype('uint64') * 5 + 2**63)
indexer = self.index.get_indexer(target, method='pad')
expected = np.array([0, 0, 1, 2, 3, 4,
4, 4, 4, 4], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)
target = UInt64Index(np.arange(10).astype('uint64') * 5 + 2**63)
indexer = self.index.get_indexer(target, method='backfill')
expected = np.array([0, 1, 1, 2, 3, 4,
-1, -1, -1, -1], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)
def test_intersection(self):
other = Index([2**63, 2**63 + 5, 2**63 + 10, 2**63 + 15, 2**63 + 20])
result = self.index.intersection(other)
expected = Index(np.sort(np.intersect1d(self.index.values,
other.values)))
tm.assert_index_equal(result, expected)
result = other.intersection(self.index)
expected = Index(np.sort(np.asarray(np.intersect1d(self.index.values,
other.values))))
tm.assert_index_equal(result, expected)
def test_join_inner(self):
other = UInt64Index(2**63 + np.array(
[7, 12, 25, 1, 2, 10], dtype='uint64'))
other_mono = UInt64Index(2**63 + np.array(
[1, 2, 7, 10, 12, 25], dtype='uint64'))
# not monotonic
res, lidx, ridx = self.index.join(other, how='inner',
return_indexers=True)
# no guarantee of sortedness, so sort for comparison purposes
ind = res.argsort()
res = res.take(ind)
lidx = lidx.take(ind)
ridx = ridx.take(ind)
eres = UInt64Index(2**63 + np.array([10, 25], dtype='uint64'))
elidx = np.array([1, 4], dtype=np.intp)
eridx = np.array([5, 2], dtype=np.intp)
assert isinstance(res, UInt64Index)
tm.assert_index_equal(res, eres)
tm.assert_numpy_array_equal(lidx, elidx)
tm.assert_numpy_array_equal(ridx, eridx)
# monotonic
res, lidx, ridx = self.index.join(other_mono, how='inner',
return_indexers=True)
res2 = self.index.intersection(other_mono)
tm.assert_index_equal(res, res2)
elidx = np.array([1, 4], dtype=np.intp)
eridx = np.array([3, 5], dtype=np.intp)
assert isinstance(res, UInt64Index)
tm.assert_index_equal(res, eres)
tm.assert_numpy_array_equal(lidx, elidx)
tm.assert_numpy_array_equal(ridx, eridx)
def test_join_left(self):
other = UInt64Index(2**63 + np.array(
[7, 12, 25, 1, 2, 10], dtype='uint64'))
other_mono = UInt64Index(2**63 + np.array(
[1, 2, 7, 10, 12, 25], dtype='uint64'))
# not monotonic
res, lidx, ridx = self.index.join(other, how='left',
return_indexers=True)
eres = self.index
eridx = np.array([-1, 5, -1, -1, 2], dtype=np.intp)
assert isinstance(res, UInt64Index)
tm.assert_index_equal(res, eres)
assert lidx is None
tm.assert_numpy_array_equal(ridx, eridx)
# monotonic
res, lidx, ridx = self.index.join(other_mono, how='left',
return_indexers=True)
eridx = np.array([-1, 3, -1, -1, 5], dtype=np.intp)
assert isinstance(res, UInt64Index)
tm.assert_index_equal(res, eres)
assert lidx is None
tm.assert_numpy_array_equal(ridx, eridx)
# non-unique
idx = UInt64Index(2**63 + np.array([1, 1, 2, 5], dtype='uint64'))
idx2 = UInt64Index(2**63 + np.array([1, 2, 5, 7, 9], dtype='uint64'))
res, lidx, ridx = idx2.join(idx, how='left', return_indexers=True)
# 1 is in idx2, so it should be x2
eres = UInt64Index(2**63 + np.array(
[1, 1, 2, 5, 7, 9], dtype='uint64'))
eridx = np.array([0, 1, 2, 3, -1, -1], dtype=np.intp)
elidx = np.array([0, 0, 1, 2, 3, 4], dtype=np.intp)
tm.assert_index_equal(res, eres)
tm.assert_numpy_array_equal(lidx, elidx)
tm.assert_numpy_array_equal(ridx, eridx)
def test_join_right(self):
other = UInt64Index(2**63 + np.array(
[7, 12, 25, 1, 2, 10], dtype='uint64'))
other_mono = UInt64Index(2**63 + np.array(
[1, 2, 7, 10, 12, 25], dtype='uint64'))
# not monotonic
res, lidx, ridx = self.index.join(other, how='right',
return_indexers=True)
eres = other
elidx = np.array([-1, -1, 4, -1, -1, 1], dtype=np.intp)
tm.assert_numpy_array_equal(lidx, elidx)
assert isinstance(other, UInt64Index)
tm.assert_index_equal(res, eres)
assert ridx is None
# monotonic
res, lidx, ridx = self.index.join(other_mono, how='right',
return_indexers=True)
eres = other_mono
elidx = np.array([-1, -1, -1, 1, -1, 4], dtype=np.intp)
assert isinstance(other, UInt64Index)
tm.assert_numpy_array_equal(lidx, elidx)
tm.assert_index_equal(res, eres)
assert ridx is None
# non-unique
idx = UInt64Index(2**63 + np.array([1, 1, 2, 5], dtype='uint64'))
idx2 = UInt64Index(2**63 + np.array([1, 2, 5, 7, 9], dtype='uint64'))
res, lidx, ridx = idx.join(idx2, how='right', return_indexers=True)
# 1 is in idx2, so it should be x2
eres = UInt64Index(2**63 + np.array(
[1, 1, 2, 5, 7, 9], dtype='uint64'))
elidx = np.array([0, 1, 2, 3, -1, -1], dtype=np.intp)
eridx = np.array([0, 0, 1, 2, 3, 4], dtype=np.intp)
tm.assert_index_equal(res, eres)
tm.assert_numpy_array_equal(lidx, elidx)
tm.assert_numpy_array_equal(ridx, eridx)
def test_join_non_int_index(self):
other = Index(2**63 + np.array(
[1, 5, 7, 10, 20], dtype='uint64'), dtype=object)
outer = self.index.join(other, how='outer')
outer2 = other.join(self.index, how='outer')
expected = Index(2**63 + np.array(
[0, 1, 5, 7, 10, 15, 20, 25], dtype='uint64'))
tm.assert_index_equal(outer, outer2)
tm.assert_index_equal(outer, expected)
inner = self.index.join(other, how='inner')
inner2 = other.join(self.index, how='inner')
expected = Index(2**63 + np.array([10, 20], dtype='uint64'))
tm.assert_index_equal(inner, inner2)
tm.assert_index_equal(inner, expected)
left = self.index.join(other, how='left')
tm.assert_index_equal(left, self.index.astype(object))
left2 = other.join(self.index, how='left')
tm.assert_index_equal(left2, other)
right = self.index.join(other, how='right')
tm.assert_index_equal(right, other)
right2 = other.join(self.index, how='right')
tm.assert_index_equal(right2, self.index.astype(object))
def test_join_outer(self):
other = UInt64Index(2**63 + np.array(
[7, 12, 25, 1, 2, 10], dtype='uint64'))
other_mono = UInt64Index(2**63 + np.array(
[1, 2, 7, 10, 12, 25], dtype='uint64'))
# not monotonic
# guarantee of sortedness
res, lidx, ridx = self.index.join(other, how='outer',
return_indexers=True)
noidx_res = self.index.join(other, how='outer')
tm.assert_index_equal(res, noidx_res)
eres = UInt64Index(2**63 + np.array(
[0, 1, 2, 7, 10, 12, 15, 20, 25], dtype='uint64'))
elidx = np.array([0, -1, -1, -1, 1, -1, 2, 3, 4], dtype=np.intp)
eridx = np.array([-1, 3, 4, 0, 5, 1, -1, -1, 2], dtype=np.intp)
assert isinstance(res, UInt64Index)
tm.assert_index_equal(res, eres)
tm.assert_numpy_array_equal(lidx, elidx)
tm.assert_numpy_array_equal(ridx, eridx)
# monotonic
res, lidx, ridx = self.index.join(other_mono, how='outer',
return_indexers=True)
noidx_res = self.index.join(other_mono, how='outer')
tm.assert_index_equal(res, noidx_res)
elidx = np.array([0, -1, -1, -1, 1, -1, 2, 3, 4], dtype=np.intp)
eridx = np.array([-1, 0, 1, 2, 3, 4, -1, -1, 5], dtype=np.intp)
assert isinstance(res, UInt64Index)
tm.assert_index_equal(res, eres)
tm.assert_numpy_array_equal(lidx, elidx)
tm.assert_numpy_array_equal(ridx, eridx)