8000 REF/TST: collect reduction tests by jbrockmendel · Pull Request #24367 · pandas-dev/pandas · GitHub
[go: up one dir, main page]
Skip to content

REF/TST: collect reduction tests #24367

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 9 commits into from
Dec 23, 2018
Merged

REF/TST: collect reduction tests #24367

Show file tree
Hide file tree
Changes from 1 commit
Commits
Show all changes
9 commits
Select commit Hold shift + click to select a range
8e544cf
collect reduction tests
jbrockmendel Dec 20, 2018
6c98821
dont use singleton fixtures
jbrockmendel Dec 20, 2018
767b498
isort fixup
jbrockmendel Dec 20, 2018
17278f0
Merge branch 'master' of https://github.com/pandas-dev/pandas into tred
jbrockmendel Dec 21, 2018
f7c6eae
Merge branch 'master' of https://github.com/pandas-dev/pandas into tred
jbrockmendel Dec 21, 2018
1c73ec8
Merge branch 'master' of https://github.com/pandas-dev/pandas into tred
jbrockmendel Dec 21, 2018
b45e9b5
Merge branch 'master' of https://github.com/pandas-dev/pandas into tred
jbrockmendel Dec 21, 2018
e8c2b47
make tests.reductions dir
jbrockmendel Dec 21, 2018
e3a6fc6
split into reductions test dir
jbrockmendel Dec 21, 2018
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Prev Previous commit
split into reductions test dir
  • Loading branch information
@jbrockmendel
jbrockmendel committed Dec 21, 2018
commit e3a6fc690b1e7da26cbbf563d69cf1df7b29d93e
4 changes: 4 additions & 0 deletions pandas/tests/reductions/__init__.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,4 @@
"""
Tests for reductions where we want to test for matching behavior across
Array, Index, Series, and DataFrame methods.
"""
196 changes: 1 addition & 195 deletions pandas/tests/reductions/test_reductions.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,15 +1,9 @@
"""
Tests for reductions where we want to test for matching behavior across
Array, Index, Series, and DataFrame methods.
"""
# -*- coding: utf-8 -*-
from datetime import datetime

import numpy as np
import pytest

from pandas.compat import lrange
import pandas.util._test_decorators as td

import pandas as pd
from pandas import Categorical, DataFrame, Index, PeriodIndex, Series, compat
from pandas.core import nanops
Expand Down Expand Up @@ -103,194 +97,6 @@ def test_nanops(self):
assert obj.argmax() == -1


class TestSeriesStatReductions(object):
# Note: the name TestSeriesStatReductions indicates these tests
# were moved from a series-specific test file, _not_ that these tests are
# intended long-term to be series-specific

def _check_stat_op(self, name, alternate, string_series_,
check_objects=False, check_allna=False):

with pd.option_context('use_bottleneck', False):
f = getattr(Series, name)

# add some NaNs
string_series_[5:15] = np.NaN

# idxmax, idxmin, min, and max are valid for dates
if name not in ['max', 'min']:
ds = Series(pd.date_range('1/1/2001', periods=10))
with pytest.raises(TypeError):
f(ds)

# skipna or no
assert pd.notna(f(string_series_))
assert pd.isna(f(string_series_, skipna=False))

# check the result is correct
nona = string_series_.dropna()
tm.assert_almost_equal(f(nona), alternate(nona.values))
tm.assert_almost_equal(f(string_series_), alternate(nona.values))

allna = string_series_ * np.nan

if check_allna:
assert np.isnan(f(allna))

# dtype=object with None, it works!
s = Series([1, 2, 3, None, 5])
f(s)

# GH#2888
items = [0]
items.extend(lrange(2 ** 40, 2 ** 40 + 1000))
s = Series(items, dtype='int64')
tm.assert_almost_equal(float(f(s)), float(alternate(s.values)))

# check date range
if check_objects:
s = Series(pd.bdate_range('1/1/2000', periods=10))
res = f(s)
exp = alternate(s)
assert res == exp

# check on string data
if name not in ['sum', 'min', 'max']:
with pytest.raises(TypeError):
f(Series(list('abc')))

# Invalid axis.
with pytest.raises(ValueError):
f(string_series_, axis=1)

# Unimplemented numeric_only parameter.
if 'numeric_only' in compat.signature(f).args:
with pytest.raises(NotImplementedError, match=name):
f(string_series_, numeric_only=True)

def test_sum(self):
string_series = tm.makeStringSeries().rename('series')
self._check_stat_op('sum', np.sum, string_series, check_allna=False)

def test_mean(self):
string_series = tm.makeStringSeries().rename('series')
self._check_stat_op('mean', np.mean, string_series)

def test_median(self):
string_series = tm.makeStringSeries().rename('series')
self._check_stat_op('median', np.median, string_series)

# test with integers, test failure
int_ts = Series(np.ones(10, dtype=int), index=lrange(10))
tm.assert_almost_equal(np.median(int_ts), int_ts.median())

def test_prod(self):
string_series = tm.makeStringSeries().rename('series')
self._check_stat_op('prod', np.prod, string_series)

def test_min(self):
string_series = tm.makeStringSeries().rename('series')
self._check_stat_op('min', np.min, string_series, check_objects=True)

def test_max(self):
string_series = tm.makeStringSeries().rename('series')
self._check_stat_op('max', np.max, string_series, check_objects=True)

def test_var_std(self):
string_series = tm.makeStringSeries().rename('series')
datetime_series = tm.makeTimeSeries().rename('ts')

alt = lambda x: np.std(x, ddof=1)
self._check_stat_op('std', alt, string_series)

alt = lambda x: np.var(x, ddof=1)
self._check_stat_op('var', alt, string_series)

result = datetime_series.std(ddof=4)
expected = np.std(datetime_series.values, ddof=4)
tm.assert_almost_equal(result, expected)

result = datetime_series.var(ddof=4)
expected = np.var(datetime_series.values, ddof=4)
tm.assert_almost_equal(result, expected)

# 1 - element series with ddof=1
s = datetime_series.iloc[[0]]
result = s.var(ddof=1)
assert pd.isna(result)

result = s.std(ddof=1)
assert pd.isna(result)

def test_sem(self):
string_series = tm.makeStringSeries().rename('series')
datetime_series = tm.makeTimeSeries().rename('ts')

alt = lambda x: np.std(x, ddof=1) / np.sqrt(len(x))
self._check_stat_op('sem', alt, string_series)

result = datetime_series.sem(ddof=4)
expected = np.std(datetime_series.values,
ddof=4) / np.sqrt(len(datetime_series.values))
tm.assert_almost_equal(result, expected)

# 1 - element series with ddof=1
s = datetime_series.iloc[[0]]
result = s.sem(ddof=1)
assert pd.isna(result)

@td.skip_if_no_scipy
def test_skew(self):
from scipy.stats import s BF21 kew

string_series = tm.makeStringSeries().rename('series')

alt = lambda x: skew(x, bias=False)
self._check_stat_op('skew', alt, string_series)

# test corner cases, skew() returns NaN unless there's at least 3
# values
min_N = 3
for i in range(1, min_N + 1):
s = Series(np.ones(i))
df = DataFrame(np.ones((i, i)))
if i < min_N:
assert np.isnan(s.skew())
assert np.isnan(df.skew()).all()
else:
assert 0 == s.skew()
assert (df.skew() == 0).all()

@td.skip_if_no_scipy
def test_kurt(self):
from scipy.stats import kurtosis

string_series = tm.makeStringSeries().rename('series')

alt = lambda x: kurtosis(x, bias=False)
self._check_stat_op('kurt', alt, string_series)

index = pd.MultiIndex(
levels=[['bar'], ['one', 'two', 'three'], [0, 1]],
codes=[[0, 0, 0, 0, 0, 0], [0, 1, 2, 0, 1, 2], [0, 1, 0, 1, 0, 1]]
)
s = Series(np.random.randn(6), index=index)
tm.assert_almost_equal(s.kurt(), s.kurt(level=0)['bar'])

# test corner cases, kurt() returns NaN unless there's at least 4
# values
min_N = 4
for i in range(1, min_N + 1):
s = Series(np.ones(i))
df = DataFrame(np.ones((i, i)))
if i < min_N:
assert np.isnan(s.kurt())
assert np.isnan(df.kurt()).all()
else:
assert 0 == s.kurt()
assert (df.kurt() == 0).all()


class TestSeriesReductions(object):
# Note: the name TestSeriesReductions indicates these tests
# were moved from a series-specific test file, _not_ that these tests are
Expand Down
Loading
0