-
-
Notifications
You must be signed in to change notification settings - Fork 18.5k
REF/TST: Add more pytest idiom to indexing/multiindex/test_iloc.py #24272
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.
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
Changes from 1 commit
Commits
Show all changes
2 commits
Select commit
Hold shift + click to select a range
File filter
Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
There are no files selected for viewing
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -1,129 +1,97 @@ | ||
from warnings import catch_warnings | ||
|
||
import numpy as np | ||
import pytest | ||
|
||
from pandas import DataFrame, MultiIndex, Series | ||
from pandas.util import testing as tm | ||
|
||
|
||
@pytest.mark.filterwarnings("ignore:\\n.ix:DeprecationWarning") | ||
class TestMultiIndexIloc(object): | ||
|
||
def test_iloc_getitem_multiindex2(self): | ||
# TODO(wesm): fix this | ||
pytest.skip('this test was being suppressed, ' | ||
'needs to be fixed') | ||
|
||
arr = np.random.randn(3, 3) | ||
df = DataFrame(arr, columns=[[2, 2, 4], [6, 8, 10]], | ||
index=[[4, 4, 8], [8, 10, 12]]) | ||
|
||
rs = df.iloc[2] | ||
xp = Series(arr[2], index=df.columns) | ||
tm.assert_series_equal(rs, xp) | ||
|
||
rs = df.iloc[:, 2] | ||
xp = Series(arr[:, 2], index=df.index) | ||
tm.assert_series_equal(rs, xp) | ||
|
||
rs = df.iloc[2, 2] | ||
xp = df.values[2, 2] | ||
assert rs == xp | ||
|
||
# for multiple items | ||
# GH 5528 | ||
rs = df.iloc[[0, 1]] | ||
xp = df.xs(4, drop_level=False) | ||
tm.assert_frame_equal(rs, xp) | ||
|
||
tup = zip(*[['a', 'a', 'b', 'b'], ['x', 'y', 'x', 'y']]) | ||
index = MultiIndex.from_tuples(tup) | ||
df = DataFrame(np.random.randn(4, 4), index=index) | ||
rs = df.iloc[[2, 3]] | ||
xp = df.xs('b', drop_level=False) | ||
tm.assert_frame_equal(rs, xp) | ||
|
||
def test_iloc_getitem_multiindex(self): | ||
mi_labels = DataFrame(np.random.randn(4, 3), | ||
columns=[['i', 'i', 'j'], ['A', 'A', 'B']], | ||
index=[['i', 'i', 'j', 'k'], | ||
['X', 'X', 'Y', 'Y']]) | ||
|
||
mi_int = DataFrame(np.random.randn(3, 3), | ||
columns=[[2, 2, 4], [6, 8, 10]], | ||
index=[[4, 4, 8], [8, 10, 12]]) | ||
|
||
# the first row | ||
rs = mi_int.iloc[0] | ||
with catch_warnings(record=True): | ||
xp = mi_int.ix[4].ix[8] | ||
tm.assert_series_equal(rs, xp, check_names=False) | ||
assert rs.name == (4, 8) | ||
assert xp.name == 8 | ||
|
||
# 2nd (last) columns | ||
rs = mi_int.iloc[:, 2] | ||
with catch_warnings(record=True): | ||
xp = mi_int.ix[:, 2] | ||
tm.assert_series_equal(rs, xp) | ||
|
||
# corner column | ||
rs = mi_int.iloc[2, 2] | ||
with catch_warnings(record=True): | ||
# First level is int - so use .loc rather than .ix (GH 21593) | ||
xp = mi_int.loc[(8, 12), (4, 10)] | ||
assert rs == xp | ||
|
||
# this is basically regular indexing | ||
rs = mi_labels.iloc[2, 2] | ||
with catch_warnings(record=True): | ||
xp = mi_labels.ix['j'].ix[:, 'j'].ix[0, 0] | ||
assert rs == xp | ||
|
||
def test_frame_getitem_setitem_slice( | ||
self, multiindex_dataframe_random_data): | ||
frame = multiindex_dataframe_random_data | ||
# getitem | ||
result = frame.iloc[:4] | ||
expected = frame[:4] | ||
tm.assert_frame_equal(result, expected) | ||
|
||
# setitem | ||
cp = frame.copy() | ||
cp.iloc[:4] = 0 | ||
|
||
assert (cp.values[:4] == 0).all() | ||
assert (cp.values[4:] != 0).all() | ||
|
||
def test_indexing_ambiguity_bug_1678(self): | ||
columns = MultiIndex.from_tuples([('Ohio', 'Green'), ('Ohio', 'Red'), ( | ||
'Colorado', 'Green')]) | ||
index = MultiIndex.from_tuples([('a', 1), ('a', 2), ('b', 1), ('b', 2) | ||
]) | ||
|
||
frame = DataFrame(np.arange(12).reshape((4, 3)), index=index, | ||
columns=columns) | ||
|
||
result = frame.iloc[:, 1] | ||
exp = frame.loc[:, ('Ohio', 'Red')] | ||
assert isinstance(result, Series) | ||
tm.assert_series_equal(result, exp) | ||
|
||
def test_iloc_mi(self): | ||
# GH 13797 | ||
# Test if iloc can handle integer locations in MultiIndexed DataFrame | ||
|
||
data = [['str00', 'str01'], ['str10', 'str11'], ['str20', 'srt21'], | ||
['str30', 'str31'], ['str40', 'str41']] | ||
|
||
mi = MultiIndex.from_tuples( | ||
[('CC', 'A'), ('CC', 'B'), ('CC', 'B'), ('BB', 'a'), ('BB', 'b')]) | ||
|
||
expected = DataFrame(data) | ||
df_mi = DataFrame(data, index=mi) | ||
|
||
result = DataFrame([[df_mi.iloc[r, c] for c in range(2)] | ||
for r in range(5)]) | ||
|
||
tm.assert_frame_equal(result, expected) | ||
@pytest.mark.parametrize('indexer, expected', [ | ||
(lambda df: df.iloc[0], | ||
lambda arr, df: Series(arr[0], index=df.columns, name=(4, 8))), | ||
(lambda df: df.iloc[2], | ||
lambda arr, df: Series(arr[2], index=df.columns, name=(8, 12))), | ||
(lambda df: df.iloc[:, 2], | ||
lambda arr, df: Series(arr[:, 2], index=df.index, name=(4, 10))), | ||
(lambda df: df.iloc[2, 2], | ||
lambda arr, df: arr[2, 2]), | ||
(lambda df: df.iloc[[0, 1]], | ||
lambda arr, df: df.xs(4, drop_level=False)) | ||
]) | ||
def test_iloc_getitem(indexer, expected): | ||
arr = np.random.randn(3, 3) | ||
df = DataFrame(arr, columns=[[2, 2, 4], [6, 8, 10]], | ||
index=[[4, 4, 8], [8, 10, 12]]) | ||
|
||
result = indexer(df) | ||
expected = expected(arr, df) | ||
|
||
try: | ||
tm.assert_equal(result, expected) | ||
except NotImplementedError: | ||
assert result == expected | ||
|
||
|
||
def test_iloc_getitem_multiple_items(): | ||
# GH 5528 | ||
tup = zip(*[['a', 'a', 'b', 'b'], ['x', 'y', 'x', 'y']]) | ||
index = MultiIndex.from_tuples(tup) | ||
df = DataFrame(np.random.randn(4, 4), index=index) | ||
result = df.iloc[[2, 3]] | ||
expected = df.xs('b', drop_level=False) | ||
tm.assert_frame_equal(result, expected) | ||
|
||
|
||
def test_iloc_getitem_labels(): | ||
# this is basically regular indexing | ||
arr = np.random.randn(4, 3) | ||
df = DataFrame(arr, | ||
columns=[['i', 'i', 'j'], ['A', 'A', 'B']], | ||
index=[['i', 'i', 'j', 'k'], ['X', 'X', 'Y', 'Y']]) | ||
result = df.iloc[2, 2] | ||
expected = arr[2, 2] | ||
assert result == expected | ||
|
||
|
||
def test_frame_getitem_slice(multiindex_dataframe_random_data): | ||
frame = multiindex_dataframe_random_data | ||
result = frame.iloc[:4] | ||
expected = frame[:4] | ||
tm.assert_frame_equal(result, expected) | ||
|
||
|
||
def test_frame_setitem_slice(multiindex_dataframe_random_data): | ||
df = multiindex_dataframe_random_data | ||
df.iloc[:4] = 0 | ||
|
||
assert (df.values[:4] == 0).all() | ||
assert (df.values[4:] != 0).all() | ||
|
||
|
||
def test_indexing_ambiguity_bug_1678(): | ||
columns = MultiIndex.from_tuples( | ||
[('Ohio', 'Green'), ('Ohio', 'Red'), ('Colorado', 'Green')]) | ||
index = MultiIndex.from_tuples([('a', 1), ('a', 2), ('b', 1), ('b', 2)]) | ||
|
||
df = DataFrame(np.arange(12).reshape((4, 3)), index=index, columns=columns) | ||
|
||
result = df.iloc[:, 1] | ||
expected = df.loc[:, ('Ohio', 'Red')] | ||
tm.assert_series_equal(result, expected) | ||
|
||
|
||
def test_iloc_mi(): | ||
# GH 13797 | ||
# Test if iloc can handle integer locations in MultiIndexed DataFrame | ||
|
||
data = [['str00', 'str01'], ['str10', 'str11'], ['str20', 'srt21'], | ||
['str30', 'str31'], ['str40', 'str41']] | ||
|
||
index = MultiIndex.from_tuples( | ||
[('CC', 'A'), ('CC', 'B'), ('CC', 'B'), ('BB', 'a'), ('BB', 'b')]) | ||
|
||
expected = DataFrame(data) | ||
df = DataFrame(data, index=index) | ||
|
||
result = DataFrame([[df.iloc[r, c] for c in range(2)] for r in range(5)]) | ||
|
||
tm.assert_frame_equal(result, expected) |
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
what case hits this? would like to more explict here (e.g. not using a try/except)
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
@jreback
.loc
returns either a series, dataframe or scalar value, the except is for the scalar values. it may be better to split this test into three seperate tests;test_iloc_returns_series
,test_iloc_returns_dataframe
, andtest_iloc_returns_scalar
. we would then be duplicating the setup but this could be made a fixture. what's you thoughts?There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
yes let's do that. i am very leary anytime have a try/except in a test as they often hide actual errors.