alpcentaur/laywerrobot
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions
laywerrobot/lib/python3.6/site-packages/pandas/tests/test_strings.py

3184 lines
122 KiB
Python
Raw Normal View History

first commit
2020-08-27 21:55:39 +02:00
# -*- coding: utf-8 -*-
# pylint: disable-msg=E1101,W0612
from datetime import datetime, timedelta
import pytest
import re
from numpy import nan as NA
import numpy as np
from numpy.random import randint
from pandas.compat import range, u
import pandas.compat as compat
from pandas import Index, Series, DataFrame, isna, MultiIndex, notna, concat
from pandas.util.testing import assert_series_equal, assert_index_equal
import pandas.util.testing as tm
import pandas.core.strings as strings
def assert_series_or_index_equal(left, right):
if isinstance(left, Series):
assert_series_equal(left, right)
else: # Index
assert_index_equal(left, right)
class TestStringMethods(object):
def test_api(self):
# GH 6106, GH 9322
assert Series.str is strings.StringMethods
assert isinstance(Series(['']).str, strings.StringMethods)
# GH 9184
invalid = Series([1])
with tm.assert_raises_regex(AttributeError,
"only use .str accessor"):
invalid.str
assert not hasattr(invalid, 'str')
def test_iter(self):
# GH3638
strs = 'google', 'wikimedia', 'wikipedia', 'wikitravel'
ds = Series(strs)
for s in ds.str:
# iter must yield a Series
assert isinstance(s, Series)
# indices of each yielded Series should be equal to the index of
# the original Series
tm.assert_index_equal(s.index, ds.index)
for el in s:
# each element of the series is either a basestring/str or nan
assert isinstance(el, compat.string_types) or isna(el)
# desired behavior is to iterate until everything would be nan on the
# next iter so make sure the last element of the iterator was 'l' in
# this case since 'wikitravel' is the longest string
assert s.dropna().values.item() == 'l'
def test_iter_empty(self):
ds = Series([], dtype=object)
i, s = 100, 1
for i, s in enumerate(ds.str):
pass
# nothing to iterate over so nothing defined values should remain
# unchanged
assert i == 100
assert s == 1
def test_iter_single_element(self):
ds = Series(['a'])
for i, s in enumerate(ds.str):
pass
assert not i
assert_series_equal(ds, s)
def test_iter_object_try_string(self):
ds = Series([slice(None, randint(10), randint(10, 20)) for _ in range(
4)])
i, s = 100, 'h'
for i, s in enumerate(ds.str):
pass
assert i == 100
assert s == 'h'
def test_cat(self):
one = np.array(['a', 'a', 'b', 'b', 'c', NA], dtype=np.object_)
two = np.array(['a', NA, 'b', 'd', 'foo', NA], dtype=np.object_)
# single array
result = strings.str_cat(one)
exp = 'aabbc'
assert result == exp
result = strings.str_cat(one, na_rep='NA')
exp = 'aabbcNA'
assert result == exp
result = strings.str_cat(one, na_rep='-')
exp = 'aabbc-'
assert result == exp
result = strings.str_cat(one, sep='_', na_rep='NA')
exp = 'a_a_b_b_c_NA'
assert result == exp
result = strings.str_cat(two, sep='-')
exp = 'a-b-d-foo'
assert result == exp
# Multiple arrays
result = strings.str_cat(one, [two], na_rep='NA')
exp = np.array(['aa', 'aNA', 'bb', 'bd', 'cfoo', 'NANA'],
dtype=np.object_)
tm.assert_numpy_array_equal(result, exp)
result = strings.str_cat(one, two)
exp = np.array(['aa', NA, 'bb', 'bd', 'cfoo', NA], dtype=np.object_)
tm.assert_almost_equal(result, exp)
# error for incorrect lengths
rgx = 'All arrays must be same length'
three = Series(['1', '2', '3'])
with tm.assert_raises_regex(ValueError, rgx):
strings.str_cat(one, three)
# error for incorrect type
rgx = "Must pass arrays containing strings to str_cat"
with tm.assert_raises_regex(ValueError, rgx):
strings.str_cat(one, 'three')
@pytest.mark.parametrize('container', [Series, Index])
@pytest.mark.parametrize('other', [None, Series, Index])
def test_str_cat_name(self, container, other):
# https://github.com/pandas-dev/pandas/issues/21053
values = ['a', 'b']
if other:
other = other(values)
else:
other = values
result = container(values, name='name').str.cat(other, sep=',',
join='left')
assert result.name == 'name'
@pytest.mark.parametrize('series_or_index', ['series', 'index'])
def test_str_cat(self, series_or_index):
# test_cat above tests "str_cat" from ndarray to ndarray;
# here testing "str.cat" from Series/Index to Series/Index/ndarray/list
s = Index(['a', 'a', 'b', 'b', 'c', np.nan])
if series_or_index == 'series':
s = Series(s)
t = Index(['a', np.nan, 'b', 'd', 'foo', np.nan])
# single array
result = s.str.cat()
exp = 'aabbc'
assert result == exp
result = s.str.cat(na_rep='-')
exp = 'aabbc-'
assert result == exp
result = s.str.cat(sep='_', na_rep='NA')
exp = 'a_a_b_b_c_NA'
assert result == exp
# Series/Index with Index
exp = Index(['aa', 'a-', 'bb', 'bd', 'cfoo', '--'])
if series_or_index == 'series':
exp = Series(exp)
# s.index / s is different from t (as Index) -> warning
with tm.assert_produces_warning(expected_warning=FutureWarning):
# FutureWarning to switch to alignment by default
assert_series_or_index_equal(s.str.cat(t, na_rep='-'), exp)
# Series/Index with Series
t = Series(t)
# s as Series has same index as t -> no warning
# s as Index is different from t.index -> warning (tested below)
if series_or_index == 'series':
assert_series_equal(s.str.cat(t, na_rep='-'), exp)
# Series/Index with Series: warning if different indexes
t.index = t.index + 1
with tm.assert_produces_warning(expected_warning=FutureWarning):
# FutureWarning to switch to alignment by default
assert_series_or_index_equal(s.str.cat(t, na_rep='-'), exp)
# Series/Index with array
assert_series_or_index_equal(s.str.cat(t.values, na_rep='-'), exp)
# Series/Index with list
assert_series_or_index_equal(s.str.cat(list(t), na_rep='-'), exp)
# errors for incorrect lengths
rgx = 'All arrays must be same length, except.*'
z = Series(['1', '2', '3'])
with tm.assert_raises_regex(ValueError, rgx):
s.str.cat(z)
with tm.assert_raises_regex(ValueError, rgx):
s.str.cat(z.values)
with tm.assert_raises_regex(ValueError, rgx):
s.str.cat(list(z))
@pytest.mark.parametrize('series_or_index', ['series', 'index'])
def test_str_cat_raises_intuitive_error(self, series_or_index):
# https://github.com/pandas-dev/pandas/issues/11334
s = Index(['a', 'b', 'c', 'd'])
if series_or_index == 'series':
s = Series(s)
message = "Did you mean to supply a `sep` keyword?"
with tm.assert_raises_regex(ValueError, message):
s.str.cat('|')
with tm.assert_raises_regex(ValueError, message):
s.str.cat(' ')
@pytest.mark.parametrize('series_or_index, dtype_caller, dtype_target', [
('series', 'object', 'object'),
('series', 'object', 'category'),
('series', 'category', 'object'),
('series', 'category', 'category'),
('index', 'object', 'object'),
('index', 'object', 'category'),
('index', 'category', 'object'),
('index', 'category', 'category')
])
def test_str_cat_categorical(self, series_or_index,
dtype_caller, dtype_target):
s = Index(['a', 'a', 'b', 'a'], dtype=dtype_caller)
if series_or_index == 'series':
s = Series(s)
t = Index(['b', 'a', 'b', 'c'], dtype=dtype_target)
exp = Index(['ab', 'aa', 'bb', 'ac'])
if series_or_index == 'series':
exp = Series(exp)
# Series/Index with Index
# s.index / s is different from t (as Index) -> warning
with tm.assert_produces_warning(expected_warning=FutureWarning):
# FutureWarning to switch to alignment by default
assert_series_or_index_equal(s.str.cat(t), exp)
# Series/Index with Series
t = Series(t)
# s as Series has same index as t -> no warning
# s as Index is different from t.index -> warning (tested below)
if series_or_index == 'series':
assert_series_equal(s.str.cat(t), exp)
# Series/Index with Series: warning if different indexes
t.index = t.index + 1
with tm.assert_produces_warning(expected_warning=FutureWarning):
# FutureWarning to switch to alignment by default
assert_series_or_index_equal(s.str.cat(t, na_rep='-'), exp)
@pytest.mark.parametrize('series_or_index', ['series', 'index'])
def test_str_cat_mixed_inputs(self, series_or_index):
s = Index(['a', 'b', 'c', 'd'])
if series_or_index == 'series':
s = Series(s)
t = Series(['A', 'B', 'C', 'D'])
d = concat([t, Series(s)], axis=1)
exp = Index(['aAa', 'bBb', 'cCc', 'dDd'])
if series_or_index == 'series':
exp = Series(exp)
# Series/Index with DataFrame
# s as Series has same index as d -> no warning
# s as Index is different from d.index -> warning (tested below)
if series_or_index == 'series':
assert_series_equal(s.str.cat(d), exp)
# Series/Index with DataFrame: warning if different indexes
d.index = d.index + 1
with tm.assert_produces_warning(expected_warning=FutureWarning):
# FutureWarning to switch to alignment by default
assert_series_or_index_equal(s.str.cat(d), exp)
# Series/Index with two-dimensional ndarray
assert_series_or_index_equal(s.str.cat(d.values), exp)
# Series/Index with list of Series
# s as Series has same index as t, s -> no warning
# s as Index is different from t.index -> warning (tested below)
if series_or_index == 'series':
assert_series_equal(s.str.cat([t, s]), exp)
# Series/Index with list of Series: warning if different indexes
tt = t.copy()
tt.index = tt.index + 1
with tm.assert_produces_warning(expected_warning=FutureWarning):
# FutureWarning to switch to alignment by default
assert_series_or_index_equal(s.str.cat([tt, s]), exp)
# Series/Index with list of list-likes
assert_series_or_index_equal(s.str.cat([t.values, list(s)]), exp)
# Series/Index with mixed list of Series/list-like
# s as Series has same index as t -> no warning
# s as Index is different from t.index -> warning (tested below)
if series_or_index == 'series':
assert_series_equal(s.str.cat([t, s.values]), exp)
# Series/Index with mixed list: warning if different indexes
with tm.assert_produces_warning(expected_warning=FutureWarning):
# FutureWarning to switch to alignment by default
assert_series_or_index_equal(s.str.cat([tt, s.values]), exp)
# Series/Index with iterator of list-likes
assert_series_or_index_equal(s.str.cat(iter([t.values, list(s)])), exp)
# errors for incorrect lengths
rgx = 'All arrays must be same length, except.*'
z = Series(['1', '2', '3'])
e = concat([z, z], axis=1)
# DataFrame
with tm.assert_raises_regex(ValueError, rgx):
s.str.cat(e)
# two-dimensional ndarray
with tm.assert_raises_regex(ValueError, rgx):
s.str.cat(e.values)
# list of Series
with tm.assert_raises_regex(ValueError, rgx):
s.str.cat([z, s])
# list of list-likes
with tm.assert_raises_regex(ValueError, rgx):
s.str.cat([z.values, list(s)])
# mixed list of Series/list-like
with tm.assert_raises_regex(ValueError, rgx):
s.str.cat([z, list(s)])
# errors for incorrect arguments in list-like
rgx = 'others must be Series, Index, DataFrame,.*'
# make sure None/NaN do not crash checks in _get_series_list
u = Series(['a', np.nan, 'c', None])
# mix of string and Series
with tm.assert_raises_regex(TypeError, rgx):
s.str.cat([u, 'u'])
# DataFrame in list
with tm.assert_raises_regex(TypeError, rgx):
s.str.cat([u, d])
# 2-dim ndarray in list
with tm.assert_raises_regex(TypeError, rgx):
s.str.cat([u, d.values])
# nested lists
with tm.assert_raises_regex(TypeError, rgx):
s.str.cat([u, [u, d]])
# forbidden input type, e.g. int
with tm.assert_raises_regex(TypeError, rgx):
s.str.cat(1)
@pytest.mark.parametrize('series_or_index, join', [
('series', 'left'), ('series', 'outer'),
('series', 'inner'), ('series', 'right'),
('index', 'left'), ('index', 'outer'),
('index', 'inner'), ('index', 'right')
])
def test_str_cat_align_indexed(self, series_or_index, join):
# https://github.com/pandas-dev/pandas/issues/18657
s = Series(['a', 'b', 'c', 'd'], index=['a', 'b', 'c', 'd'])
t = Series(['D', 'A', 'E', 'B'], index=['d', 'a', 'e', 'b'])
sa, ta = s.align(t, join=join)
# result after manual alignment of inputs
exp = sa.str.cat(ta, na_rep='-')
if series_or_index == 'index':
s = Index(s)
sa = Index(sa)
exp = Index(exp)
assert_series_or_index_equal(s.str.cat(t, join=join, na_rep='-'), exp)
@pytest.mark.parametrize('join', ['left', 'outer', 'inner', 'right'])
def test_str_cat_align_mixed_inputs(self, join):
s = Series(['a', 'b', 'c', 'd'])
t = Series(['d', 'a', 'e', 'b'], index=[3, 0, 4, 1])
d = concat([t, t], axis=1)
exp_outer = Series(['aaa', 'bbb', 'c--', 'ddd', '-ee'])
sa, ta = s.align(t, join=join)
exp = exp_outer.loc[ta.index]
# list of Series
tm.assert_series_equal(s.str.cat([t, t], join=join, na_rep='-'), exp)
# DataFrame
tm.assert_series_equal(s.str.cat(d, join=join, na_rep='-'), exp)
# mixed list of indexed/unindexed
u = ['A', 'B', 'C', 'D']
exp_outer = Series(['aaA', 'bbB', 'c-C', 'ddD', '-e-'])
# u will be forced have index of s -> use s here as placeholder
e = concat([t, s], axis=1, join=(join if join == 'inner' else 'outer'))
sa, ea = s.align(e, join=join)
exp = exp_outer.loc[ea.index]
tm.assert_series_equal(s.str.cat([t, u], join=join, na_rep='-'), exp)
# errors for incorrect lengths
rgx = 'If `others` contains arrays or lists.*'
z = ['1', '2', '3']
# unindexed object of wrong length
with tm.assert_raises_regex(ValueError, rgx):
s.str.cat(z, join=join)
# unindexed object of wrong length in list
with tm.assert_raises_regex(ValueError, rgx):
s.str.cat([t, z], join=join)
def test_str_cat_special_cases(self):
s = Series(['a', 'b', 'c', 'd'])
t = Series(['d', 'a', 'e', 'b'], index=[3, 0, 4, 1])
# iterator of elements with different types
exp = Series(['aaA', 'bbB', 'c-C', 'ddD', '-e-'])
tm.assert_series_equal(s.str.cat(iter([t, ['A', 'B', 'C', 'D']]),
join='outer', na_rep='-'), exp)
# right-align with different indexes in others
exp = Series(['aa-', 'd-d'], index=[0, 3])
tm.assert_series_equal(s.str.cat([t.loc[[0]], t.loc[[3]]],
join='right', na_rep='-'), exp)
def test_cat_on_filtered_index(self):
df = DataFrame(index=MultiIndex.from_product(
[[2011, 2012], [1, 2, 3]], names=['year', 'month']))
df = df.reset_index()
df = df[df.month > 1]
str_year = df.year.astype('str')
str_month = df.month.astype('str')
str_both = str_year.str.cat(str_month, sep=' ', join='left')
assert str_both.loc[1] == '2011 2'
str_multiple = str_year.str.cat([str_month, str_month],
sep=' ', join='left')
assert str_multiple.loc[1] == '2011 2 2'
def test_count(self):
values = np.array(['foo', 'foofoo', NA, 'foooofooofommmfoo'],
dtype=np.object_)
result = strings.str_count(values, 'f[o]+')
exp = np.array([1, 2, NA, 4])
tm.assert_numpy_array_equal(result, exp)
result = Series(values).str.count('f[o]+')
exp = Series([1, 2, NA, 4])
assert isinstance(result, Series)
tm.assert_series_equal(result, exp)
# mixed
mixed = ['a', NA, 'b', True, datetime.today(), 'foo', None, 1, 2.]
rs = strings.str_count(mixed, 'a')
xp = np.array([1, NA, 0, NA, NA, 0, NA, NA, NA])
tm.assert_numpy_array_equal(rs, xp)
rs = Series(mixed).str.count('a')
xp = Series([1, NA, 0, NA, NA, 0, NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_series_equal(rs, xp)
# unicode
values = [u('foo'), u('foofoo'), NA, u('foooofooofommmfoo')]
result = strings.str_count(values, 'f[o]+')
exp = np.array([1, 2, NA, 4])
tm.assert_numpy_array_equal(result, exp)
result = Series(values).str.count('f[o]+')
exp = Series([1, 2, NA, 4])
assert isinstance(result, Series)
tm.assert_series_equal(result, exp)
def test_contains(self):
values = np.array(['foo', NA, 'fooommm__foo',
'mmm_', 'foommm[_]+bar'], dtype=np.object_)
pat = 'mmm[_]+'
result = strings.str_contains(values, pat)
expected = np.array([False, NA, True, True, False], dtype=np.object_)
tm.assert_numpy_array_equal(result, expected)
result = strings.str_contains(values, pat, regex=False)
expected = np.array([False, NA, False, False, True], dtype=np.object_)
tm.assert_numpy_array_equal(result, expected)
values = ['foo', 'xyz', 'fooommm__foo', 'mmm_']
result = strings.str_contains(values, pat)
expected = np.array([False, False, True, True])
assert result.dtype == np.bool_
tm.assert_numpy_array_equal(result, expected)
# case insensitive using regex
values = ['Foo', 'xYz', 'fOOomMm__fOo', 'MMM_']
result = strings.str_contains(values, 'FOO|mmm', case=False)
expected = np.array([True, False, True, True])
tm.assert_numpy_array_equal(result, expected)
# case insensitive without regex
result = strings.str_contains(values, 'foo', regex=False, case=False)
expected = np.array([True, False, True, False])
tm.assert_numpy_array_equal(result, expected)
# mixed
mixed = ['a', NA, 'b', True, datetime.today(), 'foo', None, 1, 2.]
rs = strings.str_contains(mixed, 'o')
xp = np.array([False, NA, False, NA, NA, True, NA, NA, NA],
dtype=np.object_)
tm.assert_numpy_array_equal(rs, xp)
rs = Series(mixed).str.contains('o')
xp = Series([False, NA, False, NA, NA, True, NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_series_equal(rs, xp)
# unicode
values = np.array([u'foo', NA, u'fooommm__foo', u'mmm_'],
dtype=np.object_)
pat = 'mmm[_]+'
result = strings.str_contains(values, pat)
expected = np.array([False, np.nan, True, True], dtype=np.object_)
tm.assert_numpy_array_equal(result, expected)
result = strings.str_contains(values, pat, na=False)
expected = np.array([False, False, True, True])
tm.assert_numpy_array_equal(result, expected)
values = np.array(['foo', 'xyz', 'fooommm__foo', 'mmm_'],
dtype=np.object_)
result = strings.str_contains(values, pat)
expected = np.array([False, False, True, True])
assert result.dtype == np.bool_
tm.assert_numpy_array_equal(result, expected)
# na
values = Series(['om', 'foo', np.nan])
res = values.str.contains('foo', na="foo")
assert res.loc[2] == "foo"
def test_startswith(self):
values = Series(['om', NA, 'foo_nom', 'nom', 'bar_foo', NA, 'foo'])
result = values.str.startswith('foo')
exp = Series([False, NA, True, False, False, NA, True])
tm.assert_series_equal(result, exp)
# mixed
mixed = np.array(['a', NA, 'b', True, datetime.today(),
'foo', None, 1, 2.], dtype=np.object_)
rs = strings.str_startswith(mixed, 'f')
xp = np.array([False, NA, False, NA, NA, True, NA, NA, NA],
dtype=np.object_)
tm.assert_numpy_array_equal(rs, xp)
rs = Series(mixed).str.startswith('f')
assert isinstance(rs, Series)
xp = Series([False, NA, False, NA, NA, True, NA, NA, NA])
tm.assert_series_equal(rs, xp)
# unicode
values = Series([u('om'), NA, u('foo_nom'), u('nom'), u('bar_foo'), NA,
u('foo')])
result = values.str.startswith('foo')
exp = Series([False, NA, True, False, False, NA, True])
tm.assert_series_equal(result, exp)
result = values.str.startswith('foo', na=True)
tm.assert_series_equal(result, exp.fillna(True).astype(bool))
def test_endswith(self):
values = Series(['om', NA, 'foo_nom', 'nom', 'bar_foo', NA, 'foo'])
result = values.str.endswith('foo')
exp = Series([False, NA, False, False, True, NA, True])
tm.assert_series_equal(result, exp)
# mixed
mixed = ['a', NA, 'b', True, datetime.today(), 'foo', None, 1, 2.]
rs = strings.str_endswith(mixed, 'f')
xp = np.array([False, NA, False, NA, NA, False, NA, NA, NA],
dtype=np.object_)
tm.assert_numpy_array_equal(rs, xp)
rs = Series(mixed).str.endswith('f')
xp = Series([False, NA, False, NA, NA, False, NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_series_equal(rs, xp)
# unicode
values = Series([u('om'), NA, u('foo_nom'), u('nom'), u('bar_foo'), NA,
u('foo')])
result = values.str.endswith('foo')
exp = Series([False, NA, False, False, True, NA, True])
tm.assert_series_equal(result, exp)
result = values.str.endswith('foo', na=False)
tm.assert_series_equal(result, exp.fillna(False).astype(bool))
def test_title(self):
values = Series(["FOO", "BAR", NA, "Blah", "blurg"])
result = values.str.title()
exp = Series(["Foo", "Bar", NA, "Blah", "Blurg"])
tm.assert_series_equal(result, exp)
# mixed
mixed = Series(["FOO", NA, "bar", True, datetime.today(), "blah", None,
1, 2.])
mixed = mixed.str.title()
exp = Series(["Foo", NA, "Bar", NA, NA, "Blah", NA, NA, NA])
tm.assert_almost_equal(mixed, exp)
# unicode
values = Series([u("FOO"), NA, u("bar"), u("Blurg")])
results = values.str.title()
exp = Series([u("Foo"), NA, u("Bar"), u("Blurg")])
tm.assert_series_equal(results, exp)
def test_lower_upper(self):
values = Series(['om', NA, 'nom', 'nom'])
result = values.str.upper()
exp = Series(['OM', NA, 'NOM', 'NOM'])
tm.assert_series_equal(result, exp)
result = result.str.lower()
tm.assert_series_equal(result, values)
# mixed
mixed = Series(['a', NA, 'b', True, datetime.today(), 'foo', None, 1,
2.])
mixed = mixed.str.upper()
rs = Series(mixed).str.lower()
xp = Series(['a', NA, 'b', NA, NA, 'foo', NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_series_equal(rs, xp)
# unicode
values = Series([u('om'), NA, u('nom'), u('nom')])
result = values.str.upper()
exp = Series([u('OM'), NA, u('NOM'), u('NOM')])
tm.assert_series_equal(result, exp)
result = result.str.lower()
tm.assert_series_equal(result, values)
def test_capitalize(self):
values = Series(["FOO", "BAR", NA, "Blah", "blurg"])
result = values.str.capitalize()
exp = Series(["Foo", "Bar", NA, "Blah", "Blurg"])
tm.assert_series_equal(result, exp)
# mixed
mixed = Series(["FOO", NA, "bar", True, datetime.today(), "blah", None,
1, 2.])
mixed = mixed.str.capitalize()
exp = Series(["Foo", NA, "Bar", NA, NA, "Blah", NA, NA, NA])
tm.assert_almost_equal(mixed, exp)
# unicode
values = Series([u("FOO"), NA, u("bar"), u("Blurg")])
results = values.str.capitalize()
exp = Series([u("Foo"), NA, u("Bar"), u("Blurg")])
tm.assert_series_equal(results, exp)
def test_swapcase(self):
values = Series(["FOO", "BAR", NA, "Blah", "blurg"])
result = values.str.swapcase()
exp = Series(["foo", "bar", NA, "bLAH", "BLURG"])
tm.assert_series_equal(result, exp)
# mixed
mixed = Series(["FOO", NA, "bar", True, datetime.today(), "Blah", None,
1, 2.])
mixed = mixed.str.swapcase()
exp = Series(["foo", NA, "BAR", NA, NA, "bLAH", NA, NA, NA])
tm.assert_almost_equal(mixed, exp)
# unicode
values = Series([u("FOO"), NA, u("bar"), u("Blurg")])
results = values.str.swapcase()
exp = Series([u("foo"), NA, u("BAR"), u("bLURG")])
tm.assert_series_equal(results, exp)
def test_casemethods(self):
values = ['aaa', 'bbb', 'CCC', 'Dddd', 'eEEE']
s = Series(values)
assert s.str.lower().tolist() == [v.lower() for v in values]
assert s.str.upper().tolist() == [v.upper() for v in values]
assert s.str.title().tolist() == [v.title() for v in values]
assert s.str.capitalize().tolist() == [v.capitalize() for v in values]
assert s.str.swapcase().tolist() == [v.swapcase() for v in values]
def test_replace(self):
values = Series(['fooBAD__barBAD', NA])
result = values.str.replace('BAD[_]*', '')
exp = Series(['foobar', NA])
tm.assert_series_equal(result, exp)
result = values.str.replace('BAD[_]*', '', n=1)
exp = Series(['foobarBAD', NA])
tm.assert_series_equal(result, exp)
# mixed
mixed = Series(['aBAD', NA, 'bBAD', True, datetime.today(), 'fooBAD',
None, 1, 2.])
rs = Series(mixed).str.replace('BAD[_]*', '')
xp = Series(['a', NA, 'b', NA, NA, 'foo', NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_almost_equal(rs, xp)
# unicode
values = Series([u('fooBAD__barBAD'), NA])
result = values.str.replace('BAD[_]*', '')
exp = Series([u('foobar'), NA])
tm.assert_series_equal(result, exp)
result = values.str.replace('BAD[_]*', '', n=1)
exp = Series([u('foobarBAD'), NA])
tm.assert_series_equal(result, exp)
# flags + unicode
values = Series([b"abcd,\xc3\xa0".decode("utf-8")])
exp = Series([b"abcd, \xc3\xa0".decode("utf-8")])
result = values.str.replace(r"(?<=\w),(?=\w)", ", ", flags=re.UNICODE)
tm.assert_series_equal(result, exp)
# GH 13438
for klass in (Series, Index):
for repl in (None, 3, {'a': 'b'}):
for data in (['a', 'b', None], ['a', 'b', 'c', 'ad']):
values = klass(data)
pytest.raises(TypeError, values.str.replace, 'a', repl)
def test_replace_callable(self):
# GH 15055
values = Series(['fooBAD__barBAD', NA])
# test with callable
repl = lambda m: m.group(0).swapcase()
result = values.str.replace('[a-z][A-Z]{2}', repl, n=2)
exp = Series(['foObaD__baRbaD', NA])
tm.assert_series_equal(result, exp)
# test with wrong number of arguments, raising an error
if compat.PY2:
p_err = r'takes (no|(exactly|at (least|most)) ?\d+) arguments?'
else:
p_err = (r'((takes)|(missing)) (?(2)from \d+ to )?\d+ '
r'(?(3)required )positional arguments?')
repl = lambda: None
with tm.assert_raises_regex(TypeError, p_err):
values.str.replace('a', repl)
repl = lambda m, x: None
with tm.assert_raises_regex(TypeError, p_err):
values.str.replace('a', repl)
repl = lambda m, x, y=None: None
with tm.assert_raises_regex(TypeError, p_err):
values.str.replace('a', repl)
# test regex named groups
values = Series(['Foo Bar Baz', NA])
pat = r"(?P<first>\w+) (?P<middle>\w+) (?P<last>\w+)"
repl = lambda m: m.group('middle').swapcase()
result = values.str.replace(pat, repl)
exp = Series(['bAR', NA])
tm.assert_series_equal(result, exp)
def test_replace_compiled_regex(self):
# GH 15446
values = Series(['fooBAD__barBAD', NA])
# test with compiled regex
pat = re.compile(r'BAD[_]*')
result = values.str.replace(pat, '')
exp = Series(['foobar', NA])
tm.assert_series_equal(result, exp)
# mixed
mixed = Series(['aBAD', NA, 'bBAD', True, datetime.today(), 'fooBAD',
None, 1, 2.])
rs = Series(mixed).str.replace(pat, '')
xp = Series(['a', NA, 'b', NA, NA, 'foo', NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_almost_equal(rs, xp)
# unicode
values = Series([u('fooBAD__barBAD'), NA])
result = values.str.replace(pat, '')
exp = Series([u('foobar'), NA])
tm.assert_series_equal(result, exp)
result = values.str.replace(pat, '', n=1)
exp = Series([u('foobarBAD'), NA])
tm.assert_series_equal(result, exp)
# flags + unicode
values = Series([b"abcd,\xc3\xa0".decode("utf-8")])
exp = Series([b"abcd, \xc3\xa0".decode("utf-8")])
pat = re.compile(r"(?<=\w),(?=\w)", flags=re.UNICODE)
result = values.str.replace(pat, ", ")
tm.assert_series_equal(result, exp)
# case and flags provided to str.replace will have no effect
# and will produce warnings
values = Series(['fooBAD__barBAD__bad', NA])
pat = re.compile(r'BAD[_]*')
with tm.assert_raises_regex(ValueError,
"case and flags cannot be"):
result = values.str.replace(pat, '', flags=re.IGNORECASE)
with tm.assert_raises_regex(ValueError,
"case and flags cannot be"):
result = values.str.replace(pat, '', case=False)
with tm.assert_raises_regex(ValueError,
"case and flags cannot be"):
result = values.str.replace(pat, '', case=True)
# test with callable
values = Series(['fooBAD__barBAD', NA])
repl = lambda m: m.group(0).swapcase()
pat = re.compile('[a-z][A-Z]{2}')
result = values.str.replace(pat, repl, n=2)
exp = Series(['foObaD__baRbaD', NA])
tm.assert_series_equal(result, exp)
def test_replace_literal(self):
# GH16808 literal replace (regex=False vs regex=True)
values = Series(['f.o', 'foo', NA])
exp = Series(['bao', 'bao', NA])
result = values.str.replace('f.', 'ba')
tm.assert_series_equal(result, exp)
exp = Series(['bao', 'foo', NA])
result = values.str.replace('f.', 'ba', regex=False)
tm.assert_series_equal(result, exp)
# Cannot do a literal replace if given a callable repl or compiled
# pattern
callable_repl = lambda m: m.group(0).swapcase()
compiled_pat = re.compile('[a-z][A-Z]{2}')
pytest.raises(ValueError, values.str.replace, 'abc', callable_repl,
regex=False)
pytest.raises(ValueError, values.str.replace, compiled_pat, '',
regex=False)
def test_repeat(self):
values = Series(['a', 'b', NA, 'c', NA, 'd'])
result = values.str.repeat(3)
exp = Series(['aaa', 'bbb', NA, 'ccc', NA, 'ddd'])
tm.assert_series_equal(result, exp)
result = values.str.repeat([1, 2, 3, 4, 5, 6])
exp = Series(['a', 'bb', NA, 'cccc', NA, 'dddddd'])
tm.assert_series_equal(result, exp)
# mixed
mixed = Series(['a', NA, 'b', True, datetime.today(), 'foo', None, 1,
2.])
rs = Series(mixed).str.repeat(3)
xp = Series(['aaa', NA, 'bbb', NA, NA, 'foofoofoo', NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_series_equal(rs, xp)
# unicode
values = Series([u('a'), u('b'), NA, u('c'), NA, u('d')])
result = values.str.repeat(3)
exp = Series([u('aaa'), u('bbb'), NA, u('ccc'), NA, u('ddd')])
tm.assert_series_equal(result, exp)
result = values.str.repeat([1, 2, 3, 4, 5, 6])
exp = Series([u('a'), u('bb'), NA, u('cccc'), NA, u('dddddd')])
tm.assert_series_equal(result, exp)
def test_match(self):
# New match behavior introduced in 0.13
values = Series(['fooBAD__barBAD', NA, 'foo'])
result = values.str.match('.*(BAD[_]+).*(BAD)')
exp = Series([True, NA, False])
tm.assert_series_equal(result, exp)
values = Series(['fooBAD__barBAD', NA, 'foo'])
result = values.str.match('.*BAD[_]+.*BAD')
exp = Series([True, NA, False])
tm.assert_series_equal(result, exp)
# test passing as_indexer still works but is ignored
values = Series(['fooBAD__barBAD', NA, 'foo'])
exp = Series([True, NA, False])
with tm.assert_produces_warning(FutureWarning):
result = values.str.match('.*BAD[_]+.*BAD', as_indexer=True)
tm.assert_series_equal(result, exp)
with tm.assert_produces_warning(FutureWarning):
result = values.str.match('.*BAD[_]+.*BAD', as_indexer=False)
tm.assert_series_equal(result, exp)
with tm.assert_produces_warning(FutureWarning):
result = values.str.match('.*(BAD[_]+).*(BAD)', as_indexer=True)
tm.assert_series_equal(result, exp)
pytest.raises(ValueError, values.str.match, '.*(BAD[_]+).*(BAD)',
as_indexer=False)
# mixed
mixed = Series(['aBAD_BAD', NA, 'BAD_b_BAD', True, datetime.today(),
'foo', None, 1, 2.])
rs = Series(mixed).str.match('.*(BAD[_]+).*(BAD)')
xp = Series([True, NA, True, NA, NA, False, NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_series_equal(rs, xp)
# unicode
values = Series([u('fooBAD__barBAD'), NA, u('foo')])
result = values.str.match('.*(BAD[_]+).*(BAD)')
exp = Series([True, NA, False])
tm.assert_series_equal(result, exp)
# na GH #6609
res = Series(['a', 0, np.nan]).str.match('a', na=False)
exp = Series([True, False, False])
assert_series_equal(exp, res)
res = Series(['a', 0, np.nan]).str.match('a')
exp = Series([True, np.nan, np.nan])
assert_series_equal(exp, res)
def test_extract_expand_None(self):
values = Series(['fooBAD__barBAD', NA, 'foo'])
with tm.assert_raises_regex(ValueError,
'expand must be True or False'):
values.str.extract('.*(BAD[_]+).*(BAD)', expand=None)
def test_extract_expand_unspecified(self):
values = Series(['fooBAD__barBAD', NA, 'foo'])
result_unspecified = values.str.extract('.*(BAD[_]+).*')
assert isinstance(result_unspecified, DataFrame)
result_true = values.str.extract('.*(BAD[_]+).*', expand=True)
tm.assert_frame_equal(result_unspecified, result_true)
def test_extract_expand_False(self):
# Contains tests like those in test_match and some others.
values = Series(['fooBAD__barBAD', NA, 'foo'])
er = [NA, NA] # empty row
result = values.str.extract('.*(BAD[_]+).*(BAD)', expand=False)
exp = DataFrame([['BAD__', 'BAD'], er, er])
tm.assert_frame_equal(result, exp)
# mixed
mixed = Series(['aBAD_BAD', NA, 'BAD_b_BAD', True, datetime.today(),
'foo', None, 1, 2.])
rs = Series(mixed).str.extract('.*(BAD[_]+).*(BAD)', expand=False)
exp = DataFrame([['BAD_', 'BAD'], er, ['BAD_', 'BAD'], er, er, er, er,
er, er])
tm.assert_frame_equal(rs, exp)
# unicode
values = Series([u('fooBAD__barBAD'), NA, u('foo')])
result = values.str.extract('.*(BAD[_]+).*(BAD)', expand=False)
exp = DataFrame([[u('BAD__'), u('BAD')], er, er])
tm.assert_frame_equal(result, exp)
# GH9980
# Index only works with one regex group since
# multi-group would expand to a frame
idx = Index(['A1', 'A2', 'A3', 'A4', 'B5'])
with tm.assert_raises_regex(ValueError, "supported"):
idx.str.extract('([AB])([123])', expand=False)
# these should work for both Series and Index
for klass in [Series, Index]:
# no groups
s_or_idx = klass(['A1', 'B2', 'C3'])
f = lambda: s_or_idx.str.extract('[ABC][123]', expand=False)
pytest.raises(ValueError, f)
# only non-capturing groups
f = lambda: s_or_idx.str.extract('(?:[AB]).*', expand=False)
pytest.raises(ValueError, f)
# single group renames series/index properly
s_or_idx = klass(['A1', 'A2'])
result = s_or_idx.str.extract(r'(?P<uno>A)\d', expand=False)
assert result.name == 'uno'
exp = klass(['A', 'A'], name='uno')
if klass == Series:
tm.assert_series_equal(result, exp)
else:
tm.assert_index_equal(result, exp)
s = Series(['A1', 'B2', 'C3'])
# one group, no matches
result = s.str.extract('(_)', expand=False)
exp = Series([NA, NA, NA], dtype=object)
tm.assert_series_equal(result, exp)
# two groups, no matches
result = s.str.extract('(_)(_)', expand=False)
exp = DataFrame([[NA, NA], [NA, NA], [NA, NA]], dtype=object)
tm.assert_frame_equal(result, exp)
# one group, some matches
result = s.str.extract('([AB])[123]', expand=False)
exp = Series(['A', 'B', NA])
tm.assert_series_equal(result, exp)
# two groups, some matches
result = s.str.extract('([AB])([123])', expand=False)
exp = DataFrame([['A', '1'], ['B', '2'], [NA, NA]])
tm.assert_frame_equal(result, exp)
# one named group
result = s.str.extract('(?P<letter>[AB])', expand=False)
exp = Series(['A', 'B', NA], name='letter')
tm.assert_series_equal(result, exp)
# two named groups
result = s.str.extract('(?P<letter>[AB])(?P<number>[123])',
expand=False)
exp = DataFrame([['A', '1'], ['B', '2'], [NA, NA]],
columns=['letter', 'number'])
tm.assert_frame_equal(result, exp)
# mix named and unnamed groups
result = s.str.extract('([AB])(?P<number>[123])', expand=False)
exp = DataFrame([['A', '1'], ['B', '2'], [NA, NA]],
columns=[0, 'number'])
tm.assert_frame_equal(result, exp)
# one normal group, one non-capturing group
result = s.str.extract('([AB])(?:[123])', expand=False)
exp = Series(['A', 'B', NA])
tm.assert_series_equal(result, exp)
# two normal groups, one non-capturing group
result = Series(['A11', 'B22', 'C33']).str.extract(
'([AB])([123])(?:[123])', expand=False)
exp = DataFrame([['A', '1'], ['B', '2'], [NA, NA]])
tm.assert_frame_equal(result, exp)
# one optional group followed by one normal group
result = Series(['A1', 'B2', '3']).str.extract(
'(?P<letter>[AB])?(?P<number>[123])', expand=False)
exp = DataFrame([['A', '1'], ['B', '2'], [NA, '3']],
columns=['letter', 'number'])
tm.assert_frame_equal(result, exp)
# one normal group followed by one optional group
result = Series(['A1', 'B2', 'C']).str.extract(
'(?P<letter>[ABC])(?P<number>[123])?', expand=False)
exp = DataFrame([['A', '1'], ['B', '2'], ['C', NA]],
columns=['letter', 'number'])
tm.assert_frame_equal(result, exp)
# GH6348
# not passing index to the extractor
def check_index(index):
data = ['A1', 'B2', 'C']
index = index[:len(data)]
s = Series(data, index=index)
result = s.str.extract(r'(\d)', expand=False)
exp = Series(['1', '2', NA], index=index)
tm.assert_series_equal(result, exp)
result = Series(data, index=index).str.extract(
r'(?P<letter>\D)(?P<number>\d)?', expand=False)
e_list = [
['A', '1'],
['B', '2'],
['C', NA]
]
exp = DataFrame(e_list, columns=['letter', 'number'], index=index)
tm.assert_frame_equal(result, exp)
i_funs = [
tm.makeStringIndex, tm.makeUnicodeIndex, tm.makeIntIndex,
tm.makeDateIndex, tm.makePeriodIndex, tm.makeRangeIndex
]
for index in i_funs:
check_index(index())
# single_series_name_is_preserved.
s = Series(['a3', 'b3', 'c2'], name='bob')
r = s.str.extract(r'(?P<sue>[a-z])', expand=False)
e = Series(['a', 'b', 'c'], name='sue')
tm.assert_series_equal(r, e)
assert r.name == e.name
def test_extract_expand_True(self):
# Contains tests like those in test_match and some others.
values = Series(['fooBAD__barBAD', NA, 'foo'])
er = [NA, NA] # empty row
result = values.str.extract('.*(BAD[_]+).*(BAD)', expand=True)
exp = DataFrame([['BAD__', 'BAD'], er, er])
tm.assert_frame_equal(result, exp)
# mixed
mixed = Series(['aBAD_BAD', NA, 'BAD_b_BAD', True, datetime.today(),
'foo', None, 1, 2.])
rs = Series(mixed).str.extract('.*(BAD[_]+).*(BAD)', expand=True)
exp = DataFrame([['BAD_', 'BAD'], er, ['BAD_', 'BAD'], er, er,
er, er, er, er])
tm.assert_frame_equal(rs, exp)
# unicode
values = Series([u('fooBAD__barBAD'), NA, u('foo')])
result = values.str.extract('.*(BAD[_]+).*(BAD)', expand=True)
exp = DataFrame([[u('BAD__'), u('BAD')], er, er])
tm.assert_frame_equal(result, exp)
# these should work for both Series and Index
for klass in [Series, Index]:
# no groups
s_or_idx = klass(['A1', 'B2', 'C3'])
f = lambda: s_or_idx.str.extract('[ABC][123]', expand=True)
pytest.raises(ValueError, f)
# only non-capturing groups
f = lambda: s_or_idx.str.extract('(?:[AB]).*', expand=True)
pytest.raises(ValueError, f)
# single group renames series/index properly
s_or_idx = klass(['A1', 'A2'])
result_df = s_or_idx.str.extract(r'(?P<uno>A)\d', expand=True)
assert isinstance(result_df, DataFrame)
result_series = result_df['uno']
assert_series_equal(result_series, Series(['A', 'A'], name='uno'))
def test_extract_series(self):
# extract should give the same result whether or not the
# series has a name.
for series_name in None, "series_name":
s = Series(['A1', 'B2', 'C3'], name=series_name)
# one group, no matches
result = s.str.extract('(_)', expand=True)
exp = DataFrame([NA, NA, NA], dtype=object)
tm.assert_frame_equal(result, exp)
# two groups, no matches
result = s.str.extract('(_)(_)', expand=True)
exp = DataFrame([[NA, NA], [NA, NA], [NA, NA]], dtype=object)
tm.assert_frame_equal(result, exp)
# one group, some matches
result = s.str.extract('([AB])[123]', expand=True)
exp = DataFrame(['A', 'B', NA])
tm.assert_frame_equal(result, exp)
# two groups, some matches
result = s.str.extract('([AB])([123])', expand=True)
exp = DataFrame([['A', '1'], ['B', '2'], [NA, NA]])
tm.assert_frame_equal(result, exp)
# one named group
result = s.str.extract('(?P<letter>[AB])', expand=True)
exp = DataFrame({"letter": ['A', 'B', NA]})
tm.assert_frame_equal(result, exp)
# two named groups
result = s.str.extract(
'(?P<letter>[AB])(?P<number>[123])',
expand=True)
e_list = [
['A', '1'],
['B', '2'],
[NA, NA]
]
exp = DataFrame(e_list, columns=['letter', 'number'])
tm.assert_frame_equal(result, exp)
# mix named and unnamed groups
result = s.str.extract('([AB])(?P<number>[123])', expand=True)
exp = DataFrame(e_list, columns=[0, 'number'])
tm.assert_frame_equal(result, exp)
# one normal group, one non-capturing group
result = s.str.extract('([AB])(?:[123])', expand=True)
exp = DataFrame(['A', 'B', NA])
tm.assert_frame_equal(result, exp)
def test_extract_optional_groups(self):
# two normal groups, one non-capturing group
result = Series(['A11', 'B22', 'C33']).str.extract(
'([AB])([123])(?:[123])', expand=True)
exp = DataFrame([['A', '1'], ['B', '2'], [NA, NA]])
tm.assert_frame_equal(result, exp)
# one optional group followed by one normal group
result = Series(['A1', 'B2', '3']).str.extract(
'(?P<letter>[AB])?(?P<number>[123])', expand=True)
e_list = [
['A', '1'],
['B', '2'],
[NA, '3']
]
exp = DataFrame(e_list, columns=['letter', 'number'])
tm.assert_frame_equal(result, exp)
# one normal group followed by one optional group
result = Series(['A1', 'B2', 'C']).str.extract(
'(?P<letter>[ABC])(?P<number>[123])?', expand=True)
e_list = [
['A', '1'],
['B', '2'],
['C', NA]
]
exp = DataFrame(e_list, columns=['letter', 'number'])
tm.assert_frame_equal(result, exp)
# GH6348
# not passing index to the extractor
def check_index(index):
data = ['A1', 'B2', 'C']
index = index[:len(data)]
result = Series(data, index=index).str.extract(
r'(\d)', expand=True)
exp = DataFrame(['1', '2', NA], index=index)
tm.assert_frame_equal(result, exp)
result = Series(data, index=index).str.extract(
r'(?P<letter>\D)(?P<number>\d)?', expand=True)
e_list = [
['A', '1'],
['B', '2'],
['C', NA]
]
exp = DataFrame(e_list, columns=['letter', 'number'], index=index)
tm.assert_frame_equal(result, exp)
i_funs = [
tm.makeStringIndex, tm.makeUnicodeIndex, tm.makeIntIndex,
tm.makeDateIndex, tm.makePeriodIndex, tm.makeRangeIndex
]
for index in i_funs:
check_index(index())
def test_extract_single_group_returns_frame(self):
# GH11386 extract should always return DataFrame, even when
# there is only one group. Prior to v0.18.0, extract returned
# Series when there was only one group in the regex.
s = Series(['a3', 'b3', 'c2'], name='series_name')
r = s.str.extract(r'(?P<letter>[a-z])', expand=True)
e = DataFrame({"letter": ['a', 'b', 'c']})
tm.assert_frame_equal(r, e)
def test_extractall(self):
subject_list = [
'dave@google.com',
'tdhock5@gmail.com',
'maudelaperriere@gmail.com',
'rob@gmail.com some text steve@gmail.com',
'a@b.com some text c@d.com and e@f.com',
np.nan,
"",
]
expected_tuples = [
("dave", "google", "com"),
("tdhock5", "gmail", "com"),
("maudelaperriere", "gmail", "com"),
("rob", "gmail", "com"), ("steve", "gmail", "com"),
("a", "b", "com"), ("c", "d", "com"), ("e", "f", "com"),
]
named_pattern = r"""
(?P<user>[a-z0-9]+)
@
(?P<domain>[a-z]+)
\.
(?P<tld>[a-z]{2,4})
"""
expected_columns = ["user", "domain", "tld"]
S = Series(subject_list)
# extractall should return a DataFrame with one row for each
# match, indexed by the subject from which the match came.
expected_index = MultiIndex.from_tuples([
(0, 0),
(1, 0),
(2, 0),
(3, 0),
(3, 1),
(4, 0),
(4, 1),
(4, 2),
], names=(None, "match"))
expected_df = DataFrame(
expected_tuples, expected_index, expected_columns)
computed_df = S.str.extractall(named_pattern, re.VERBOSE)
tm.assert_frame_equal(computed_df, expected_df)
# The index of the input Series should be used to construct
# the index of the output DataFrame:
series_index = MultiIndex.from_tuples([
("single", "Dave"),
("single", "Toby"),
("single", "Maude"),
("multiple", "robAndSteve"),
("multiple", "abcdef"),
("none", "missing"),
("none", "empty"),
])
Si = Series(subject_list, series_index)
expected_index = MultiIndex.from_tuples([
("single", "Dave", 0),
("single", "Toby", 0),
("single", "Maude", 0),
("multiple", "robAndSteve", 0),
("multiple", "robAndSteve", 1),
("multiple", "abcdef", 0),
("multiple", "abcdef", 1),
("multiple", "abcdef", 2),
], names=(None, None, "match"))
expected_df = DataFrame(
expected_tuples, expected_index, expected_columns)
computed_df = Si.str.extractall(named_pattern, re.VERBOSE)
tm.assert_frame_equal(computed_df, expected_df)
# MultiIndexed subject with names.
Sn = Series(subject_list, series_index)
Sn.index.names = ("matches", "description")
expected_index.names = ("matches", "description", "match")
expected_df = DataFrame(
expected_tuples, expected_index, expected_columns)
computed_df = Sn.str.extractall(named_pattern, re.VERBOSE)
tm.assert_frame_equal(computed_df, expected_df)
# optional groups.
subject_list = ['', 'A1', '32']
named_pattern = '(?P<letter>[AB])?(?P<number>[123])'
computed_df = Series(subject_list).str.extractall(named_pattern)
expected_index = MultiIndex.from_tuples([
(1, 0),
(2, 0),
(2, 1),
], names=(None, "match"))
expected_df = DataFrame([
('A', '1'),
(NA, '3'),
(NA, '2'),
], expected_index, columns=['letter', 'number'])
tm.assert_frame_equal(computed_df, expected_df)
# only one of two groups has a name.
pattern = '([AB])?(?P<number>[123])'
computed_df = Series(subject_list).str.extractall(pattern)
expected_df = DataFrame([
('A', '1'),
(NA, '3'),
(NA, '2'),
], expected_index, columns=[0, 'number'])
tm.assert_frame_equal(computed_df, expected_df)
def test_extractall_single_group(self):
# extractall(one named group) returns DataFrame with one named
# column.
s = Series(['a3', 'b3', 'd4c2'], name='series_name')
r = s.str.extractall(r'(?P<letter>[a-z])')
i = MultiIndex.from_tuples([
(0, 0),
(1, 0),
(2, 0),
(2, 1),
], names=(None, "match"))
e = DataFrame({"letter": ['a', 'b', 'd', 'c']}, i)
tm.assert_frame_equal(r, e)
# extractall(one un-named group) returns DataFrame with one
# un-named column.
r = s.str.extractall(r'([a-z])')
e = DataFrame(['a', 'b', 'd', 'c'], i)
tm.assert_frame_equal(r, e)
def test_extractall_single_group_with_quantifier(self):
# extractall(one un-named group with quantifier) returns
# DataFrame with one un-named column (GH13382).
s = Series(['ab3', 'abc3', 'd4cd2'], name='series_name')
r = s.str.extractall(r'([a-z]+)')
i = MultiIndex.from_tuples([
(0, 0),
(1, 0),
(2, 0),
(2, 1),
], names=(None, "match"))
e = DataFrame(['ab', 'abc', 'd', 'cd'], i)
tm.assert_frame_equal(r, e)
@pytest.mark.parametrize('data, names', [
([], (None, )),
([], ('i1', )),
([], (None, 'i2')),
([], ('i1', 'i2')),
(['a3', 'b3', 'd4c2'], (None, )),
(['a3', 'b3', 'd4c2'], ('i1', 'i2')),
(['a3', 'b3', 'd4c2'], (None, 'i2')),
(['a3', 'b3', 'd4c2'], ('i1', 'i2')),
])
def test_extractall_no_matches(self, data, names):
# GH19075 extractall with no matches should return a valid MultiIndex
n = len(data)
if len(names) == 1:
i = Index(range(n), name=names[0])
else:
a = (tuple([i] * (n - 1)) for i in range(n))
i = MultiIndex.from_tuples(a, names=names)
s = Series(data, name='series_name', index=i, dtype='object')
ei = MultiIndex.from_tuples([], names=(names + ('match',)))
# one un-named group.
r = s.str.extractall('(z)')
e = DataFrame(columns=[0], index=ei)
tm.assert_frame_equal(r, e)
# two un-named groups.
r = s.str.extractall('(z)(z)')
e = DataFrame(columns=[0, 1], index=ei)
tm.assert_frame_equal(r, e)
# one named group.
r = s.str.extractall('(?P<first>z)')
e = DataFrame(columns=["first"], index=ei)
tm.assert_frame_equal(r, e)
# two named groups.
r = s.str.extractall('(?P<first>z)(?P<second>z)')
e = DataFrame(columns=["first", "second"], index=ei)
tm.assert_frame_equal(r, e)
# one named, one un-named.
r = s.str.extractall('(z)(?P<second>z)')
e = DataFrame(columns=[0, "second"], index=ei)
tm.assert_frame_equal(r, e)
def test_extractall_stringindex(self):
s = Series(["a1a2", "b1", "c1"], name='xxx')
res = s.str.extractall(r"[ab](?P<digit>\d)")
exp_idx = MultiIndex.from_tuples([(0, 0), (0, 1), (1, 0)],
names=[None, 'match'])
exp = DataFrame({'digit': ["1", "2", "1"]}, index=exp_idx)
tm.assert_frame_equal(res, exp)
# index should return the same result as the default index without name
# thus index.name doesn't affect to the result
for idx in [Index(["a1a2", "b1", "c1"]),
Index(["a1a2", "b1", "c1"], name='xxx')]:
res = idx.str.extractall(r"[ab](?P<digit>\d)")
tm.assert_frame_equal(res, exp)
s = Series(["a1a2", "b1", "c1"], name='s_name',
index=Index(["XX", "yy", "zz"], name='idx_name'))
res = s.str.extractall(r"[ab](?P<digit>\d)")
exp_idx = MultiIndex.from_tuples([("XX", 0), ("XX", 1), ("yy", 0)],
names=["idx_name", 'match'])
exp = DataFrame({'digit': ["1", "2", "1"]}, index=exp_idx)
tm.assert_frame_equal(res, exp)
def test_extractall_errors(self):
# Does not make sense to use extractall with a regex that has
# no capture groups. (it returns DataFrame with one column for
# each capture group)
s = Series(['a3', 'b3', 'd4c2'], name='series_name')
with tm.assert_raises_regex(ValueError, "no capture groups"):
s.str.extractall(r'[a-z]')
def test_extract_index_one_two_groups(self):
s = Series(['a3', 'b3', 'd4c2'], index=["A3", "B3", "D4"],
name='series_name')
r = s.index.str.extract(r'([A-Z])', expand=True)
e = DataFrame(['A', "B", "D"])
tm.assert_frame_equal(r, e)
# Prior to v0.18.0, index.str.extract(regex with one group)
# returned Index. With more than one group, extract raised an
# error (GH9980). Now extract always returns DataFrame.
r = s.index.str.extract(
r'(?P<letter>[A-Z])(?P<digit>[0-9])', expand=True)
e_list = [
("A", "3"),
("B", "3"),
("D", "4"),
]
e = DataFrame(e_list, columns=["letter", "digit"])
tm.assert_frame_equal(r, e)
def test_extractall_same_as_extract(self):
s = Series(['a3', 'b3', 'c2'], name='series_name')
pattern_two_noname = r'([a-z])([0-9])'
extract_two_noname = s.str.extract(pattern_two_noname, expand=True)
has_multi_index = s.str.extractall(pattern_two_noname)
no_multi_index = has_multi_index.xs(0, level="match")
tm.assert_frame_equal(extract_two_noname, no_multi_index)
pattern_two_named = r'(?P<letter>[a-z])(?P<digit>[0-9])'
extract_two_named = s.str.extract(pattern_two_named, expand=True)
has_multi_index = s.str.extractall(pattern_two_named)
no_multi_index = has_multi_index.xs(0, level="match")
tm.assert_frame_equal(extract_two_named, no_multi_index)
pattern_one_named = r'(?P<group_name>[a-z])'
extract_one_named = s.str.extract(pattern_one_named, expand=True)
has_multi_index = s.str.extractall(pattern_one_named)
no_multi_index = has_multi_index.xs(0, level="match")
tm.assert_frame_equal(extract_one_named, no_multi_index)
pattern_one_noname = r'([a-z])'
extract_one_noname = s.str.extract(pattern_one_noname, expand=True)
has_multi_index = s.str.extractall(pattern_one_noname)
no_multi_index = has_multi_index.xs(0, level="match")
tm.assert_frame_equal(extract_one_noname, no_multi_index)
def test_extractall_same_as_extract_subject_index(self):
# same as above tests, but s has an MultiIndex.
i = MultiIndex.from_tuples([
("A", "first"),
("B", "second"),
("C", "third"),
], names=("capital", "ordinal"))
s = Series(['a3', 'b3', 'c2'], i, name='series_name')
pattern_two_noname = r'([a-z])([0-9])'
extract_two_noname = s.str.extract(pattern_two_noname, expand=True)
has_match_index = s.str.extractall(pattern_two_noname)
no_match_index = has_match_index.xs(0, level="match")
tm.assert_frame_equal(extract_two_noname, no_match_index)
pattern_two_named = r'(?P<letter>[a-z])(?P<digit>[0-9])'
extract_two_named = s.str.extract(pattern_two_named, expand=True)
has_match_index = s.str.extractall(pattern_two_named)
no_match_index = has_match_index.xs(0, level="match")
tm.assert_frame_equal(extract_two_named, no_match_index)
pattern_one_named = r'(?P<group_name>[a-z])'
extract_one_named = s.str.extract(pattern_one_named, expand=True)
has_match_index = s.str.extractall(pattern_one_named)
no_match_index = has_match_index.xs(0, level="match")
tm.assert_frame_equal(extract_one_named, no_match_index)
pattern_one_noname = r'([a-z])'
extract_one_noname = s.str.extract(pattern_one_noname, expand=True)
has_match_index = s.str.extractall(pattern_one_noname)
no_match_index = has_match_index.xs(0, level="match")
tm.assert_frame_equal(extract_one_noname, no_match_index)
def test_empty_str_methods(self):
empty_str = empty = Series(dtype=object)
empty_int = Series(dtype=int)
empty_bool = Series(dtype=bool)
empty_bytes = Series(dtype=object)
# GH7241
# (extract) on empty series
tm.assert_series_equal(empty_str, empty.str.cat(empty, join='left'))
assert '' == empty.str.cat()
tm.assert_series_equal(empty_str, empty.str.title())
tm.assert_series_equal(empty_int, empty.str.count('a'))
tm.assert_series_equal(empty_bool, empty.str.contains('a'))
tm.assert_series_equal(empty_bool, empty.str.startswith('a'))
tm.assert_series_equal(empty_bool, empty.str.endswith('a'))
tm.assert_series_equal(empty_str, empty.str.lower())
tm.assert_series_equal(empty_str, empty.str.upper())
tm.assert_series_equal(empty_str, empty.str.replace('a', 'b'))
tm.assert_series_equal(empty_str, empty.str.repeat(3))
tm.assert_series_equal(empty_bool, empty.str.match('^a'))
tm.assert_frame_equal(
DataFrame(columns=[0], dtype=str),
empty.str.extract('()', expand=True))
tm.assert_frame_equal(
DataFrame(columns=[0, 1], dtype=str),
empty.str.extract('()()', expand=True))
tm.assert_series_equal(
empty_str,
empty.str.extract('()', expand=False))
tm.assert_frame_equal(
DataFrame(columns=[0, 1], dtype=str),
empty.str.extract('()()', expand=False))
tm.assert_frame_equal(DataFrame(dtype=str), empty.str.get_dummies())
tm.assert_series_equal(empty_str, empty_str.str.join(''))
tm.assert_series_equal(empty_int, empty.str.len())
tm.assert_series_equal(empty_str, empty_str.str.findall('a'))
tm.assert_series_equal(empty_int, empty.str.find('a'))
tm.assert_series_equal(empty_int, empty.str.rfind('a'))
tm.assert_series_equal(empty_str, empty.str.pad(42))
tm.assert_series_equal(empty_str, empty.str.center(42))
tm.assert_series_equal(empty_str, empty.str.split('a'))
tm.assert_series_equal(empty_str, empty.str.rsplit('a'))
tm.assert_series_equal(empty_str,
empty.str.partition('a', expand=False))
tm.assert_series_equal(empty_str,
empty.str.rpartition('a', expand=False))
tm.assert_series_equal(empty_str, empty.str.slice(stop=1))
tm.assert_series_equal(empty_str, empty.str.slice(step=1))
tm.assert_series_equal(empty_str, empty.str.strip())
tm.assert_series_equal(empty_str, empty.str.lstrip())
tm.assert_series_equal(empty_str, empty.str.rstrip())
tm.assert_series_equal(empty_str, empty.str.wrap(42))
tm.assert_series_equal(empty_str, empty.str.get(0))
tm.assert_series_equal(empty_str, empty_bytes.str.decode('ascii'))
tm.assert_series_equal(empty_bytes, empty.str.encode('ascii'))
tm.assert_series_equal(empty_str, empty.str.isalnum())
tm.assert_series_equal(empty_str, empty.str.isalpha())
tm.assert_series_equal(empty_str, empty.str.isdigit())
tm.assert_series_equal(empty_str, empty.str.isspace())
tm.assert_series_equal(empty_str, empty.str.islower())
tm.assert_series_equal(empty_str, empty.str.isupper())
tm.assert_series_equal(empty_str, empty.str.istitle())
tm.assert_series_equal(empty_str, empty.str.isnumeric())
tm.assert_series_equal(empty_str, empty.str.isdecimal())
tm.assert_series_equal(empty_str, empty.str.capitalize())
tm.assert_series_equal(empty_str, empty.str.swapcase())
tm.assert_series_equal(empty_str, empty.str.normalize('NFC'))
if compat.PY3:
table = str.maketrans('a', 'b')
else:
import string
table = string.maketrans('a', 'b')
tm.assert_series_equal(empty_str, empty.str.translate(table))
def test_empty_str_methods_to_frame(self):
empty = Series(dtype=str)
empty_df = DataFrame([])
tm.assert_frame_equal(empty_df, empty.str.partition('a'))
tm.assert_frame_equal(empty_df, empty.str.rpartition('a'))
def test_ismethods(self):
values = ['A', 'b', 'Xy', '4', '3A', '', 'TT', '55', '-', ' ']
str_s = Series(values)
alnum_e = [True, True, True, True, True, False, True, True, False,
False]
alpha_e = [True, True, True, False, False, False, True, False, False,
False]
digit_e = [False, False, False, True, False, False, False, True, False,
False]
# TODO: unused
num_e = [False, False, False, True, False, False, # noqa
False, True, False, False]
space_e = [False, False, False, False, False, False, False, False,
False, True]
lower_e = [False, True, False, False, False, False, False, False,
False, False]
upper_e = [True, False, False, False, True, False, True, False, False,
False]
title_e = [True, False, True, False, True, False, False, False, False,
False]
tm.assert_series_equal(str_s.str.isalnum(), Series(alnum_e))
tm.assert_series_equal(str_s.str.isalpha(), Series(alpha_e))
tm.assert_series_equal(str_s.str.isdigit(), Series(digit_e))
tm.assert_series_equal(str_s.str.isspace(), Series(space_e))
tm.assert_series_equal(str_s.str.islower(), Series(lower_e))
tm.assert_series_equal(str_s.str.isupper(), Series(upper_e))
tm.assert_series_equal(str_s.str.istitle(), Series(title_e))
assert str_s.str.isalnum().tolist() == [v.isalnum() for v in values]
assert str_s.str.isalpha().tolist() == [v.isalpha() for v in values]
assert str_s.str.isdigit().tolist() == [v.isdigit() for v in values]
assert str_s.str.isspace().tolist() == [v.isspace() for v in values]
assert str_s.str.islower().tolist() == [v.islower() for v in values]
assert str_s.str.isupper().tolist() == [v.isupper() for v in values]
assert str_s.str.istitle().tolist() == [v.istitle() for v in values]
def test_isnumeric(self):
# 0x00bc: ¼ VULGAR FRACTION ONE QUARTER
# 0x2605: ★ not number
# 0x1378: ፸ ETHIOPIC NUMBER SEVENTY
# 0xFF13: ３ Em 3
values = ['A', '3', u'¼', u'★', u'፸', u'３', 'four']
s = Series(values)
numeric_e = [False, True, True, False, True, True, False]
decimal_e = [False, True, False, False, False, True, False]
tm.assert_series_equal(s.str.isnumeric(), Series(numeric_e))
tm.assert_series_equal(s.str.isdecimal(), Series(decimal_e))
unicodes = [u'A', u'3', u'¼', u'★', u'፸', u'３', u'four']
assert s.str.isnumeric().tolist() == [v.isnumeric() for v in unicodes]
assert s.str.isdecimal().tolist() == [v.isdecimal() for v in unicodes]
values = ['A', np.nan, u'¼', u'★', np.nan, u'３', 'four']
s = Series(values)
numeric_e = [False, np.nan, True, False, np.nan, True, False]
decimal_e = [False, np.nan, False, False, np.nan, True, False]
tm.assert_series_equal(s.str.isnumeric(), Series(numeric_e))
tm.assert_series_equal(s.str.isdecimal(), Series(decimal_e))
def test_get_dummies(self):
s = Series(['a|b', 'a|c', np.nan])
result = s.str.get_dummies('|')
expected = DataFrame([[1, 1, 0], [1, 0, 1], [0, 0, 0]],
columns=list('abc'))
tm.assert_frame_equal(result, expected)
s = Series(['a;b', 'a', 7])
result = s.str.get_dummies(';')
expected = DataFrame([[0, 1, 1], [0, 1, 0], [1, 0, 0]],
columns=list('7ab'))
tm.assert_frame_equal(result, expected)
# GH9980, GH8028
idx = Index(['a|b', 'a|c', 'b|c'])
result = idx.str.get_dummies('|')
expected = MultiIndex.from_tuples([(1, 1, 0), (1, 0, 1),
(0, 1, 1)], names=('a', 'b', 'c'))
tm.assert_index_equal(result, expected)
def test_get_dummies_with_name_dummy(self):
# GH 12180
# Dummies named 'name' should work as expected
s = Series(['a', 'b,name', 'b'])
result = s.str.get_dummies(',')
expected = DataFrame([[1, 0, 0], [0, 1, 1], [0, 1, 0]],
columns=['a', 'b', 'name'])
tm.assert_frame_equal(result, expected)
idx = Index(['a|b', 'name|c', 'b|name'])
result = idx.str.get_dummies('|')
expected = MultiIndex.from_tuples([(1, 1, 0, 0), (0, 0, 1, 1),
(0, 1, 0, 1)],
names=('a', 'b', 'c', 'name'))
tm.assert_index_equal(result, expected)
def test_join(self):
values = Series(['a_b_c', 'c_d_e', np.nan, 'f_g_h'])
result = values.str.split('_').str.join('_')
tm.assert_series_equal(values, result)
# mixed
mixed = Series(['a_b', NA, 'asdf_cas_asdf', True, datetime.today(),
'foo', None, 1, 2.])
rs = Series(mixed).str.split('_').str.join('_')
xp = Series(['a_b', NA, 'asdf_cas_asdf', NA, NA, 'foo', NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_almost_equal(rs, xp)
# unicode
values = Series([u('a_b_c'), u('c_d_e'), np.nan, u('f_g_h')])
result = values.str.split('_').str.join('_')
tm.assert_series_equal(values, result)
def test_len(self):
values = Series(['foo', 'fooo', 'fooooo', np.nan, 'fooooooo'])
result = values.str.len()
exp = values.map(lambda x: len(x) if notna(x) else NA)
tm.assert_series_equal(result, exp)
# mixed
mixed = Series(['a_b', NA, 'asdf_cas_asdf', True, datetime.today(),
'foo', None, 1, 2.])
rs = Series(mixed).str.len()
xp = Series([3, NA, 13, NA, NA, 3, NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_almost_equal(rs, xp)
# unicode
values = Series([u('foo'), u('fooo'), u('fooooo'), np.nan, u(
'fooooooo')])
result = values.str.len()
exp = values.map(lambda x: len(x) if notna(x) else NA)
tm.assert_series_equal(result, exp)
def test_findall(self):
values = Series(['fooBAD__barBAD', NA, 'foo', 'BAD'])
result = values.str.findall('BAD[_]*')
exp = Series([['BAD__', 'BAD'], NA, [], ['BAD']])
tm.assert_almost_equal(result, exp)
# mixed
mixed = Series(['fooBAD__barBAD', NA, 'foo', True, datetime.today(),
'BAD', None, 1, 2.])
rs = Series(mixed).str.findall('BAD[_]*')
xp = Series([['BAD__', 'BAD'], NA, [], NA, NA, ['BAD'], NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_almost_equal(rs, xp)
# unicode
values = Series([u('fooBAD__barBAD'), NA, u('foo'), u('BAD')])
result = values.str.findall('BAD[_]*')
exp = Series([[u('BAD__'), u('BAD')], NA, [], [u('BAD')]])
tm.assert_almost_equal(result, exp)
def test_find(self):
values = Series(['ABCDEFG', 'BCDEFEF', 'DEFGHIJEF', 'EFGHEF', 'XXXX'])
result = values.str.find('EF')
tm.assert_series_equal(result, Series([4, 3, 1, 0, -1]))
expected = np.array([v.find('EF') for v in values.values],
dtype=np.int64)
tm.assert_numpy_array_equal(result.values, expected)
result = values.str.rfind('EF')
tm.assert_series_equal(result, Series([4, 5, 7, 4, -1]))
expected = np.array([v.rfind('EF') for v in values.values],
dtype=np.int64)
tm.assert_numpy_array_equal(result.values, expected)
result = values.str.find('EF', 3)
tm.assert_series_equal(result, Series([4, 3, 7, 4, -1]))
expected = np.array([v.find('EF', 3) for v in values.values],
dtype=np.int64)
tm.assert_numpy_array_equal(result.values, expected)
result = values.str.rfind('EF', 3)
tm.assert_series_equal(result, Series([4, 5, 7, 4, -1]))
expected = np.array([v.rfind('EF', 3) for v in values.values],
dtype=np.int64)
tm.assert_numpy_array_equal(result.values, expected)
result = values.str.find('EF', 3, 6)
tm.assert_series_equal(result, Series([4, 3, -1, 4, -1]))
expected = np.array([v.find('EF', 3, 6) for v in values.values],
dtype=np.int64)
tm.assert_numpy_array_equal(result.values, expected)
result = values.str.rfind('EF', 3, 6)
tm.assert_series_equal(result, Series([4, 3, -1, 4, -1]))
expected = np.array([v.rfind('EF', 3, 6) for v in values.values],
dtype=np.int64)
tm.assert_numpy_array_equal(result.values, expected)
with tm.assert_raises_regex(TypeError,
"expected a string object, not int"):
result = values.str.find(0)
with tm.assert_raises_regex(TypeError,
"expected a string object, not int"):
result = values.str.rfind(0)
def test_find_nan(self):
values = Series(['ABCDEFG', np.nan, 'DEFGHIJEF', np.nan, 'XXXX'])
result = values.str.find('EF')
tm.assert_series_equal(result, Series([4, np.nan, 1, np.nan, -1]))
result = values.str.rfind('EF')
tm.assert_series_equal(result, Series([4, np.nan, 7, np.nan, -1]))
result = values.str.find('EF', 3)
tm.assert_series_equal(result, Series([4, np.nan, 7, np.nan, -1]))
result = values.str.rfind('EF', 3)
tm.assert_series_equal(result, Series([4, np.nan, 7, np.nan, -1]))
result = values.str.find('EF', 3, 6)
tm.assert_series_equal(result, Series([4, np.nan, -1, np.nan, -1]))
result = values.str.rfind('EF', 3, 6)
tm.assert_series_equal(result, Series([4, np.nan, -1, np.nan, -1]))
def test_index(self):
def _check(result, expected):
if isinstance(result, Series):
tm.assert_series_equal(result, expected)
else:
tm.assert_index_equal(result, expected)
for klass in [Series, Index]:
s = klass(['ABCDEFG', 'BCDEFEF', 'DEFGHIJEF', 'EFGHEF'])
result = s.str.index('EF')
_check(result, klass([4, 3, 1, 0]))
expected = np.array([v.index('EF') for v in s.values],
dtype=np.int64)
tm.assert_numpy_array_equal(result.values, expected)
result = s.str.rindex('EF')
_check(result, klass([4, 5, 7, 4]))
expected = np.array([v.rindex('EF') for v in s.values],
dtype=np.int64)
tm.assert_numpy_array_equal(result.values, expected)
result = s.str.index('EF', 3)
_check(result, klass([4, 3, 7, 4]))
expected = np.array([v.index('EF', 3) for v in s.values],
dtype=np.int64)
tm.assert_numpy_array_equal(result.values, expected)
result = s.str.rindex('EF', 3)
_check(result, klass([4, 5, 7, 4]))
expected = np.array([v.rindex('EF', 3) for v in s.values],
dtype=np.int64)
tm.assert_numpy_array_equal(result.values, expected)
result = s.str.index('E', 4, 8)
_check(result, klass([4, 5, 7, 4]))
expected = np.array([v.index('E', 4, 8) for v in s.values],
dtype=np.int64)
tm.assert_numpy_array_equal(result.values, expected)
result = s.str.rindex('E', 0, 5)
_check(result, klass([4, 3, 1, 4]))
expected = np.array([v.rindex('E', 0, 5) for v in s.values],
dtype=np.int64)
tm.assert_numpy_array_equal(result.values, expected)
with tm.assert_raises_regex(ValueError,
"substring not found"):
result = s.str.index('DE')
with tm.assert_raises_regex(TypeError,
"expected a string "
"object, not int"):
result = s.str.index(0)
# test with nan
s = Series(['abcb', 'ab', 'bcbe', np.nan])
result = s.str.index('b')
tm.assert_series_equal(result, Series([1, 1, 0, np.nan]))
result = s.str.rindex('b')
tm.assert_series_equal(result, Series([3, 1, 2, np.nan]))
def test_pad(self):
values = Series(['a', 'b', NA, 'c', NA, 'eeeeee'])
result = values.str.pad(5, side='left')
exp = Series([' a', ' b', NA, ' c', NA, 'eeeeee'])
tm.assert_almost_equal(result, exp)
result = values.str.pad(5, side='right')
exp = Series(['a ', 'b ', NA, 'c ', NA, 'eeeeee'])
tm.assert_almost_equal(result, exp)
result = values.str.pad(5, side='both')
exp = Series([' a ', ' b ', NA, ' c ', NA, 'eeeeee'])
tm.assert_almost_equal(result, exp)
# mixed
mixed = Series(['a', NA, 'b', True, datetime.today(), 'ee', None, 1, 2.
])
rs = Series(mixed).str.pad(5, side='left')
xp = Series([' a', NA, ' b', NA, NA, ' ee', NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_almost_equal(rs, xp)
mixed = Series(['a', NA, 'b', True, datetime.today(), 'ee', None, 1, 2.
])
rs = Series(mixed).str.pad(5, side='right')
xp = Series(['a ', NA, 'b ', NA, NA, 'ee ', NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_almost_equal(rs, xp)
mixed = Series(['a', NA, 'b', True, datetime.today(), 'ee', None, 1, 2.
])
rs = Series(mixed).str.pad(5, side='both')
xp = Series([' a ', NA, ' b ', NA, NA, ' ee ', NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_almost_equal(rs, xp)
# unicode
values = Series([u('a'), u('b'), NA, u('c'), NA, u('eeeeee')])
result = values.str.pad(5, side='left')
exp = Series([u(' a'), u(' b'), NA, u(' c'), NA, u('eeeeee')])
tm.assert_almost_equal(result, exp)
result = values.str.pad(5, side='right')
exp = Series([u('a '), u('b '), NA, u('c '), NA, u('eeeeee')])
tm.assert_almost_equal(result, exp)
result = values.str.pad(5, side='both')
exp = Series([u(' a '), u(' b '), NA, u(' c '), NA, u('eeeeee')])
tm.assert_almost_equal(result, exp)
def test_pad_fillchar(self):
values = Series(['a', 'b', NA, 'c', NA, 'eeeeee'])
result = values.str.pad(5, side='left', fillchar='X')
exp = Series(['XXXXa', 'XXXXb', NA, 'XXXXc', NA, 'eeeeee'])
tm.assert_almost_equal(result, exp)
result = values.str.pad(5, side='right', fillchar='X')
exp = Series(['aXXXX', 'bXXXX', NA, 'cXXXX', NA, 'eeeeee'])
tm.assert_almost_equal(result, exp)
result = values.str.pad(5, side='both', fillchar='X')
exp = Series(['XXaXX', 'XXbXX', NA, 'XXcXX', NA, 'eeeeee'])
tm.assert_almost_equal(result, exp)
with tm.assert_raises_regex(TypeError,
"fillchar must be a "
"character, not str"):
result = values.str.pad(5, fillchar='XY')
with tm.assert_raises_regex(TypeError,
"fillchar must be a "
"character, not int"):
result = values.str.pad(5, fillchar=5)
def test_pad_width(self):
# GH 13598
s = Series(['1', '22', 'a', 'bb'])
for f in ['center', 'ljust', 'rjust', 'zfill', 'pad']:
with tm.assert_raises_regex(TypeError,
"width must be of "
"integer type, not*"):
getattr(s.str, f)('f')
def test_translate(self):
def _check(result, expected):
if isinstance(result, Series):
tm.assert_series_equal(result, expected)
else:
tm.assert_index_equal(result, expected)
for klass in [Series, Index]:
s = klass(['abcdefg', 'abcc', 'cdddfg', 'cdefggg'])
if not compat.PY3:
import string
table = string.maketrans('abc', 'cde')
else:
table = str.maketrans('abc', 'cde')
result = s.str.translate(table)
expected = klass(['cdedefg', 'cdee', 'edddfg', 'edefggg'])
_check(result, expected)
# use of deletechars is python 2 only
if not compat.PY3:
result = s.str.translate(table, deletechars='fg')
expected = klass(['cdede', 'cdee', 'eddd', 'ede'])
_check(result, expected)
result = s.str.translate(None, deletechars='fg')
expected = klass(['abcde', 'abcc', 'cddd', 'cde'])
_check(result, expected)
else:
with tm.assert_raises_regex(
ValueError, "deletechars is not a valid argument"):
result = s.str.translate(table, deletechars='fg')
# Series with non-string values
s = Series(['a', 'b', 'c', 1.2])
expected = Series(['c', 'd', 'e', np.nan])
result = s.str.translate(table)
tm.assert_series_equal(result, expected)
def test_center_ljust_rjust(self):
values = Series(['a', 'b', NA, 'c', NA, 'eeeeee'])
result = values.str.center(5)
exp = Series([' a ', ' b ', NA, ' c ', NA, 'eeeeee'])
tm.assert_almost_equal(result, exp)
result = values.str.ljust(5)
exp = Series(['a ', 'b ', NA, 'c ', NA, 'eeeeee'])
tm.assert_almost_equal(result, exp)
result = values.str.rjust(5)
exp = Series([' a', ' b', NA, ' c', NA, 'eeeeee'])
tm.assert_almost_equal(result, exp)
# mixed
mixed = Series(['a', NA, 'b', True, datetime.today(), 'c', 'eee', None,
1, 2.])
rs = Series(mixed).str.center(5)
xp = Series([' a ', NA, ' b ', NA, NA, ' c ', ' eee ', NA, NA, NA
])
assert isinstance(rs, Series)
tm.assert_almost_equal(rs, xp)
rs = Series(mixed).str.ljust(5)
xp = Series(['a ', NA, 'b ', NA, NA, 'c ', 'eee ', NA, NA, NA
])
assert isinstance(rs, Series)
tm.assert_almost_equal(rs, xp)
rs = Series(mixed).str.rjust(5)
xp = Series([' a', NA, ' b', NA, NA, ' c', ' eee', NA, NA, NA
])
assert isinstance(rs, Series)
tm.assert_almost_equal(rs, xp)
# unicode
values = Series([u('a'), u('b'), NA, u('c'), NA, u('eeeeee')])
result = values.str.center(5)
exp = Series([u(' a '), u(' b '), NA, u(' c '), NA, u('eeeeee')])
tm.assert_almost_equal(result, exp)
result = values.str.ljust(5)
exp = Series([u('a '), u('b '), NA, u('c '), NA, u('eeeeee')])
tm.assert_almost_equal(result, exp)
result = values.str.rjust(5)
exp = Series([u(' a'), u(' b'), NA, u(' c'), NA, u('eeeeee')])
tm.assert_almost_equal(result, exp)
def test_center_ljust_rjust_fillchar(self):
values = Series(['a', 'bb', 'cccc', 'ddddd', 'eeeeee'])
result = values.str.center(5, fillchar='X')
expected = Series(['XXaXX', 'XXbbX', 'Xcccc', 'ddddd', 'eeeeee'])
tm.assert_series_equal(result, expected)
expected = np.array([v.center(5, 'X') for v in values.values],
dtype=np.object_)
tm.assert_numpy_array_equal(result.values, expected)
result = values.str.ljust(5, fillchar='X')
expected = Series(['aXXXX', 'bbXXX', 'ccccX', 'ddddd', 'eeeeee'])
tm.assert_series_equal(result, expected)
expected = np.array([v.ljust(5, 'X') for v in values.values],
dtype=np.object_)
tm.assert_numpy_array_equal(result.values, expected)
result = values.str.rjust(5, fillchar='X')
expected = Series(['XXXXa', 'XXXbb', 'Xcccc', 'ddddd', 'eeeeee'])
tm.assert_series_equal(result, expected)
expected = np.array([v.rjust(5, 'X') for v in values.values],
dtype=np.object_)
tm.assert_numpy_array_equal(result.values, expected)
# If fillchar is not a charatter, normal str raises TypeError
# 'aaa'.ljust(5, 'XY')
# TypeError: must be char, not str
with tm.assert_raises_regex(TypeError,
"fillchar must be a "
"character, not str"):
result = values.str.center(5, fillchar='XY')
with tm.assert_raises_regex(TypeError,
"fillchar must be a "
"character, not str"):
result = values.str.ljust(5, fillchar='XY')
with tm.assert_raises_regex(TypeError,
"fillchar must be a "
"character, not str"):
result = values.str.rjust(5, fillchar='XY')
with tm.assert_raises_regex(TypeError,
"fillchar must be a "
"character, not int"):
result = values.str.center(5, fillchar=1)
with tm.assert_raises_regex(TypeError,
"fillchar must be a "
"character, not int"):
result = values.str.ljust(5, fillchar=1)
with tm.assert_raises_regex(TypeError,
"fillchar must be a "
"character, not int"):
result = values.str.rjust(5, fillchar=1)
def test_zfill(self):
values = Series(['1', '22', 'aaa', '333', '45678'])
result = values.str.zfill(5)
expected = Series(['00001', '00022', '00aaa', '00333', '45678'])
tm.assert_series_equal(result, expected)
expected = np.array([v.zfill(5) for v in values.values],
dtype=np.object_)
tm.assert_numpy_array_equal(result.values, expected)
result = values.str.zfill(3)
expected = Series(['001', '022', 'aaa', '333', '45678'])
tm.assert_series_equal(result, expected)
expected = np.array([v.zfill(3) for v in values.values],
dtype=np.object_)
tm.assert_numpy_array_equal(result.values, expected)
values = Series(['1', np.nan, 'aaa', np.nan, '45678'])
result = values.str.zfill(5)
expected = Series(['00001', np.nan, '00aaa', np.nan, '45678'])
tm.assert_series_equal(result, expected)
def test_split(self):
values = Series(['a_b_c', 'c_d_e', NA, 'f_g_h'])
result = values.str.split('_')
exp = Series([['a', 'b', 'c'], ['c', 'd', 'e'], NA, ['f', 'g', 'h']])
tm.assert_series_equal(result, exp)
# more than one char
values = Series(['a__b__c', 'c__d__e', NA, 'f__g__h'])
result = values.str.split('__')
tm.assert_series_equal(result, exp)
result = values.str.split('__', expand=False)
tm.assert_series_equal(result, exp)
# mixed
mixed = Series(['a_b_c', NA, 'd_e_f', True, datetime.today(), None, 1,
2.])
result = mixed.str.split('_')
exp = Series([['a', 'b', 'c'], NA, ['d', 'e', 'f'], NA, NA, NA, NA, NA
])
assert isinstance(result, Series)
tm.assert_almost_equal(result, exp)
result = mixed.str.split('_', expand=False)
assert isinstance(result, Series)
tm.assert_almost_equal(result, exp)
# unicode
values = Series([u('a_b_c'), u('c_d_e'), NA, u('f_g_h')])
result = values.str.split('_')
exp = Series([[u('a'), u('b'), u('c')], [u('c'), u('d'), u('e')], NA,
[u('f'), u('g'), u('h')]])
tm.assert_series_equal(result, exp)
result = values.str.split('_', expand=False)
tm.assert_series_equal(result, exp)
# regex split
values = Series([u('a,b_c'), u('c_d,e'), NA, u('f,g,h')])
result = values.str.split('[,_]')
exp = Series([[u('a'), u('b'), u('c')], [u('c'), u('d'), u('e')], NA,
[u('f'), u('g'), u('h')]])
tm.assert_series_equal(result, exp)
def test_rsplit(self):
values = Series(['a_b_c', 'c_d_e', NA, 'f_g_h'])
result = values.str.rsplit('_')
exp = Series([['a', 'b', 'c'], ['c', 'd', 'e'], NA, ['f', 'g', 'h']])
tm.assert_series_equal(result, exp)
# more than one char
values = Series(['a__b__c', 'c__d__e', NA, 'f__g__h'])
result = values.str.rsplit('__')
tm.assert_series_equal(result, exp)
result = values.str.rsplit('__', expand=False)
tm.assert_series_equal(result, exp)
# mixed
mixed = Series(['a_b_c', NA, 'd_e_f', True, datetime.today(), None, 1,
2.])
result = mixed.str.rsplit('_')
exp = Series([['a', 'b', 'c'], NA, ['d', 'e', 'f'], NA, NA, NA, NA, NA
])
assert isinstance(result, Series)
tm.assert_almost_equal(result, exp)
result = mixed.str.rsplit('_', expand=False)
assert isinstance(result, Series)
tm.assert_almost_equal(result, exp)
# unicode
values = Series([u('a_b_c'), u('c_d_e'), NA, u('f_g_h')])
result = values.str.rsplit('_')
exp = Series([[u('a'), u('b'), u('c')], [u('c'), u('d'), u('e')], NA,
[u('f'), u('g'), u('h')]])
tm.assert_series_equal(result, exp)
result = values.str.rsplit('_', expand=False)
tm.assert_series_equal(result, exp)
# regex split is not supported by rsplit
values = Series([u('a,b_c'), u('c_d,e'), NA, u('f,g,h')])
result = values.str.rsplit('[,_]')
exp = Series([[u('a,b_c')], [u('c_d,e')], NA, [u('f,g,h')]])
tm.assert_series_equal(result, exp)
# setting max number of splits, make sure it's from reverse
values = Series(['a_b_c', 'c_d_e', NA, 'f_g_h'])
result = values.str.rsplit('_', n=1)
exp = Series([['a_b', 'c'], ['c_d', 'e'], NA, ['f_g', 'h']])
tm.assert_series_equal(result, exp)
def test_split_blank_string(self):
# expand blank split GH 20067
values = Series([''], name='test')
result = values.str.split(expand=True)
exp = DataFrame([[]])
tm.assert_frame_equal(result, exp)
values = Series(['a b c', 'a b', '', ' '], name='test')
result = values.str.split(expand=True)
exp = DataFrame([['a', 'b', 'c'], ['a', 'b', np.nan],
[np.nan, np.nan, np.nan], [np.nan, np.nan, np.nan]])
tm.assert_frame_equal(result, exp)
def test_split_noargs(self):
# #1859
s = Series(['Wes McKinney', 'Travis Oliphant'])
result = s.str.split()
expected = ['Travis', 'Oliphant']
assert result[1] == expected
result = s.str.rsplit()
assert result[1] == expected
def test_split_maxsplit(self):
# re.split 0, str.split -1
s = Series(['bd asdf jfg', 'kjasdflqw asdfnfk'])
result = s.str.split(n=-1)
xp = s.str.split()
tm.assert_series_equal(result, xp)
result = s.str.split(n=0)
tm.assert_series_equal(result, xp)
xp = s.str.split('asdf')
result = s.str.split('asdf', n=0)
tm.assert_series_equal(result, xp)
result = s.str.split('asdf', n=-1)
tm.assert_series_equal(result, xp)
def test_split_no_pat_with_nonzero_n(self):
s = Series(['split once', 'split once too!'])
result = s.str.split(n=1)
expected = Series({0: ['split', 'once'], 1: ['split', 'once too!']})
tm.assert_series_equal(expected, result, check_index_type=False)
def test_split_to_dataframe(self):
s = Series(['nosplit', 'alsonosplit'])
result = s.str.split('_', expand=True)
exp = DataFrame({0: Series(['nosplit', 'alsonosplit'])})
tm.assert_frame_equal(result, exp)
s = Series(['some_equal_splits', 'with_no_nans'])
result = s.str.split('_', expand=True)
exp = DataFrame({0: ['some', 'with'],
1: ['equal', 'no'],
2: ['splits', 'nans']})
tm.assert_frame_equal(result, exp)
s = Series(['some_unequal_splits', 'one_of_these_things_is_not'])
result = s.str.split('_', expand=True)
exp = DataFrame({0: ['some', 'one'],
1: ['unequal', 'of'],
2: ['splits', 'these'],
3: [NA, 'things'],
4: [NA, 'is'],
5: [NA, 'not']})
tm.assert_frame_equal(result, exp)
s = Series(['some_splits', 'with_index'], index=['preserve', 'me'])
result = s.str.split('_', expand=True)
exp = DataFrame({0: ['some', 'with'], 1: ['splits', 'index']},
index=['preserve', 'me'])
tm.assert_frame_equal(result, exp)
with tm.assert_raises_regex(ValueError, "expand must be"):
s.str.split('_', expand="not_a_boolean")
def test_split_to_multiindex_expand(self):
idx = Index(['nosplit', 'alsonosplit'])
result = idx.str.split('_', expand=True)
exp = idx
tm.assert_index_equal(result, exp)
assert result.nlevels == 1
idx = Index(['some_equal_splits', 'with_no_nans'])
result = idx.str.split('_', expand=True)
exp = MultiIndex.from_tuples([('some', 'equal', 'splits'), (
'with', 'no', 'nans')])
tm.assert_index_equal(result, exp)
assert result.nlevels == 3
idx = Index(['some_unequal_splits', 'one_of_these_things_is_not'])
result = idx.str.split('_', expand=True)
exp = MultiIndex.from_tuples([('some', 'unequal', 'splits', NA, NA, NA
), ('one', 'of', 'these', 'things',
'is', 'not')])
tm.assert_index_equal(result, exp)
assert result.nlevels == 6
with tm.assert_raises_regex(ValueError, "expand must be"):
idx.str.split('_', expand="not_a_boolean")
def test_rsplit_to_dataframe_expand(self):
s = Series(['nosplit', 'alsonosplit'])
result = s.str.rsplit('_', expand=True)
exp = DataFrame({0: Series(['nosplit', 'alsonosplit'])})
tm.assert_frame_equal(result, exp)
s = Series(['some_equal_splits', 'with_no_nans'])
result = s.str.rsplit('_', expand=True)
exp = DataFrame({0: ['some', 'with'],
1: ['equal', 'no'],
2: ['splits', 'nans']})
tm.assert_frame_equal(result, exp)
result = s.str.rsplit('_', expand=True, n=2)
exp = DataFrame({0: ['some', 'with'],
1: ['equal', 'no'],
2: ['splits', 'nans']})
tm.assert_frame_equal(result, exp)
result = s.str.rsplit('_', expand=True, n=1)
exp = DataFrame({0: ['some_equal', 'with_no'], 1: ['splits', 'nans']})
tm.assert_frame_equal(result, exp)
s = Series(['some_splits', 'with_index'], index=['preserve', 'me'])
result = s.str.rsplit('_', expand=True)
exp = DataFrame({0: ['some', 'with'], 1: ['splits', 'index']},
index=['preserve', 'me'])
tm.assert_frame_equal(result, exp)
def test_rsplit_to_multiindex_expand(self):
idx = Index(['nosplit', 'alsonosplit'])
result = idx.str.rsplit('_', expand=True)
exp = idx
tm.assert_index_equal(result, exp)
assert result.nlevels == 1
idx = Index(['some_equal_splits', 'with_no_nans'])
result = idx.str.rsplit('_', expand=True)
exp = MultiIndex.from_tuples([('some', 'equal', 'splits'), (
'with', 'no', 'nans')])
tm.assert_index_equal(result, exp)
assert result.nlevels == 3
idx = Index(['some_equal_splits', 'with_no_nans'])
result = idx.str.rsplit('_', expand=True, n=1)
exp = MultiIndex.from_tuples([('some_equal', 'splits'),
('with_no', 'nans')])
tm.assert_index_equal(result, exp)
assert result.nlevels == 2
def test_split_nan_expand(self):
# gh-18450
s = Series(["foo,bar,baz", NA])
result = s.str.split(",", expand=True)
exp = DataFrame([["foo", "bar", "baz"], [NA, NA, NA]])
tm.assert_frame_equal(result, exp)
# check that these are actually np.nan and not None
# TODO see GH 18463
# tm.assert_frame_equal does not differentiate
assert all(np.isnan(x) for x in result.iloc[1])
def test_split_with_name(self):
# GH 12617
# should preserve name
s = Series(['a,b', 'c,d'], name='xxx')
res = s.str.split(',')
exp = Series([['a', 'b'], ['c', 'd']], name='xxx')
tm.assert_series_equal(res, exp)
res = s.str.split(',', expand=True)
exp = DataFrame([['a', 'b'], ['c', 'd']])
tm.assert_frame_equal(res, exp)
idx = Index(['a,b', 'c,d'], name='xxx')
res = idx.str.split(',')
exp = Index([['a', 'b'], ['c', 'd']], name='xxx')
assert res.nlevels == 1
tm.assert_index_equal(res, exp)
res = idx.str.split(',', expand=True)
exp = MultiIndex.from_tuples([('a', 'b'), ('c', 'd')])
assert res.nlevels == 2
tm.assert_index_equal(res, exp)
def test_partition_series(self):
values = Series(['a_b_c', 'c_d_e', NA, 'f_g_h'])
result = values.str.partition('_', expand=False)
exp = Series([('a', '_', 'b_c'), ('c', '_', 'd_e'), NA,
('f', '_', 'g_h')])
tm.assert_series_equal(result, exp)
result = values.str.rpartition('_', expand=False)
exp = Series([('a_b', '_', 'c'), ('c_d', '_', 'e'), NA,
('f_g', '_', 'h')])
tm.assert_series_equal(result, exp)
# more than one char
values = Series(['a__b__c', 'c__d__e', NA, 'f__g__h'])
result = values.str.partition('__', expand=False)
exp = Series([('a', '__', 'b__c'), ('c', '__', 'd__e'), NA,
('f', '__', 'g__h')])
tm.assert_series_equal(result, exp)
result = values.str.rpartition('__', expand=False)
exp = Series([('a__b', '__', 'c'), ('c__d', '__', 'e'), NA,
('f__g', '__', 'h')])
tm.assert_series_equal(result, exp)
# None
values = Series(['a b c', 'c d e', NA, 'f g h'])
result = values.str.partition(expand=False)
exp = Series([('a', ' ', 'b c'), ('c', ' ', 'd e'), NA,
('f', ' ', 'g h')])
tm.assert_series_equal(result, exp)
result = values.str.rpartition(expand=False)
exp = Series([('a b', ' ', 'c'), ('c d', ' ', 'e'), NA,
('f g', ' ', 'h')])
tm.assert_series_equal(result, exp)
# Not splited
values = Series(['abc', 'cde', NA, 'fgh'])
result = values.str.partition('_', expand=False)
exp = Series([('abc', '', ''), ('cde', '', ''), NA, ('fgh', '', '')])
tm.assert_series_equal(result, exp)
result = values.str.rpartition('_', expand=False)
exp = Series([('', '', 'abc'), ('', '', 'cde'), NA, ('', '', 'fgh')])
tm.assert_series_equal(result, exp)
# unicode
values = Series([u'a_b_c', u'c_d_e', NA, u'f_g_h'])
result = values.str.partition('_', expand=False)
exp = Series([(u'a', u'_', u'b_c'), (u'c', u'_', u'd_e'),
NA, (u'f', u'_', u'g_h')])
tm.assert_series_equal(result, exp)
result = values.str.rpartition('_', expand=False)
exp = Series([(u'a_b', u'_', u'c'), (u'c_d', u'_', u'e'),
NA, (u'f_g', u'_', u'h')])
tm.assert_series_equal(result, exp)
# compare to standard lib
values = Series(['A_B_C', 'B_C_D', 'E_F_G', 'EFGHEF'])
result = values.str.partition('_', expand=False).tolist()
assert result == [v.partition('_') for v in values]
result = values.str.rpartition('_', expand=False).tolist()
assert result == [v.rpartition('_') for v in values]
def test_partition_index(self):
values = Index(['a_b_c', 'c_d_e', 'f_g_h'])
result = values.str.partition('_', expand=False)
exp = Index(np.array([('a', '_', 'b_c'), ('c', '_', 'd_e'), ('f', '_',
'g_h')]))
tm.assert_index_equal(result, exp)
assert result.nlevels == 1
result = values.str.rpartition('_', expand=False)
exp = Index(np.array([('a_b', '_', 'c'), ('c_d', '_', 'e'), (
'f_g', '_', 'h')]))
tm.assert_index_equal(result, exp)
assert result.nlevels == 1
result = values.str.partition('_')
exp = Index([('a', '_', 'b_c'), ('c', '_', 'd_e'), ('f', '_', 'g_h')])
tm.assert_index_equal(result, exp)
assert isinstance(result, MultiIndex)
assert result.nlevels == 3
result = values.str.rpartition('_')
exp = Index([('a_b', '_', 'c'), ('c_d', '_', 'e'), ('f_g', '_', 'h')])
tm.assert_index_equal(result, exp)
assert isinstance(result, MultiIndex)
assert result.nlevels == 3
def test_partition_to_dataframe(self):
values = Series(['a_b_c', 'c_d_e', NA, 'f_g_h'])
result = values.str.partition('_')
exp = DataFrame({0: ['a', 'c', np.nan, 'f'],
1: ['_', '_', np.nan, '_'],
2: ['b_c', 'd_e', np.nan, 'g_h']})
tm.assert_frame_equal(result, exp)
result = values.str.rpartition('_')
exp = DataFrame({0: ['a_b', 'c_d', np.nan, 'f_g'],
1: ['_', '_', np.nan, '_'],
2: ['c', 'e', np.nan, 'h']})
tm.assert_frame_equal(result, exp)
values = Series(['a_b_c', 'c_d_e', NA, 'f_g_h'])
result = values.str.partition('_', expand=True)
exp = DataFrame({0: ['a', 'c', np.nan, 'f'],
1: ['_', '_', np.nan, '_'],
2: ['b_c', 'd_e', np.nan, 'g_h']})
tm.assert_frame_equal(result, exp)
result = values.str.rpartition('_', expand=True)
exp = DataFrame({0: ['a_b', 'c_d', np.nan, 'f_g'],
1: ['_', '_', np.nan, '_'],
2: ['c', 'e', np.nan, 'h']})
tm.assert_frame_equal(result, exp)
def test_partition_with_name(self):
# GH 12617
s = Series(['a,b', 'c,d'], name='xxx')
res = s.str.partition(',')
exp = DataFrame({0: ['a', 'c'], 1: [',', ','], 2: ['b', 'd']})
tm.assert_frame_equal(res, exp)
# should preserve name
res = s.str.partition(',', expand=False)
exp = Series([('a', ',', 'b'), ('c', ',', 'd')], name='xxx')
tm.assert_series_equal(res, exp)
idx = Index(['a,b', 'c,d'], name='xxx')
res = idx.str.partition(',')
exp = MultiIndex.from_tuples([('a', ',', 'b'), ('c', ',', 'd')])
assert res.nlevels == 3
tm.assert_index_equal(res, exp)
# should preserve name
res = idx.str.partition(',', expand=False)
exp = Index(np.array([('a', ',', 'b'), ('c', ',', 'd')]), name='xxx')
assert res.nlevels == 1
tm.assert_index_equal(res, exp)
def test_pipe_failures(self):
# #2119
s = Series(['A|B|C'])
result = s.str.split('|')
exp = Series([['A', 'B', 'C']])
tm.assert_series_equal(result, exp)
result = s.str.replace('|', ' ')
exp = Series(['A B C'])
tm.assert_series_equal(result, exp)
def test_slice(self):
values = Series(['aafootwo', 'aabartwo', NA, 'aabazqux'])
result = values.str.slice(2, 5)
exp = Series(['foo', 'bar', NA, 'baz'])
tm.assert_series_equal(result, exp)
for start, stop, step in [(0, 3, -1), (None, None, -1), (3, 10, 2),
(3, 0, -1)]:
try:
result = values.str.slice(start, stop, step)
expected = Series([s[start:stop:step] if not isna(s) else NA
for s in values])
tm.assert_series_equal(result, expected)
except:
print('failed on %s:%s:%s' % (start, stop, step))
raise
# mixed
mixed = Series(['aafootwo', NA, 'aabartwo', True, datetime.today(),
None, 1, 2.])
rs = Series(mixed).str.slice(2, 5)
xp = Series(['foo', NA, 'bar', NA, NA, NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_almost_equal(rs, xp)
rs = Series(mixed).str.slice(2, 5, -1)
xp = Series(['oof', NA, 'rab', NA, NA, NA, NA, NA])
# unicode
values = Series([u('aafootwo'), u('aabartwo'), NA, u('aabazqux')])
result = values.str.slice(2, 5)
exp = Series([u('foo'), u('bar'), NA, u('baz')])
tm.assert_series_equal(result, exp)
result = values.str.slice(0, -1, 2)
exp = Series([u('afow'), u('abrw'), NA, u('abzu')])
tm.assert_series_equal(result, exp)
def test_slice_replace(self):
values = Series(['short', 'a bit longer', 'evenlongerthanthat', '', NA
])
exp = Series(['shrt', 'a it longer', 'evnlongerthanthat', '', NA])
result = values.str.slice_replace(2, 3)
tm.assert_series_equal(result, exp)
exp = Series(['shzrt', 'a zit longer', 'evznlongerthanthat', 'z', NA])
result = values.str.slice_replace(2, 3, 'z')
tm.assert_series_equal(result, exp)
exp = Series(['shzort', 'a zbit longer', 'evzenlongerthanthat', 'z', NA
])
result = values.str.slice_replace(2, 2, 'z')
tm.assert_series_equal(result, exp)
exp = Series(['shzort', 'a zbit longer', 'evzenlongerthanthat', 'z', NA
])
result = values.str.slice_replace(2, 1, 'z')
tm.assert_series_equal(result, exp)
exp = Series(['shorz', 'a bit longez', 'evenlongerthanthaz', 'z', NA])
result = values.str.slice_replace(-1, None, 'z')
tm.assert_series_equal(result, exp)
exp = Series(['zrt', 'zer', 'zat', 'z', NA])
result = values.str.slice_replace(None, -2, 'z')
tm.assert_series_equal(result, exp)
exp = Series(['shortz', 'a bit znger', 'evenlozerthanthat', 'z', NA])
result = values.str.slice_replace(6, 8, 'z')
tm.assert_series_equal(result, exp)
exp = Series(['zrt', 'a zit longer', 'evenlongzerthanthat', 'z', NA])
result = values.str.slice_replace(-10, 3, 'z')
tm.assert_series_equal(result, exp)
def test_strip_lstrip_rstrip(self):
values = Series([' aa ', ' bb \n', NA, 'cc '])
result = values.str.strip()
exp = Series(['aa', 'bb', NA, 'cc'])
tm.assert_series_equal(result, exp)
result = values.str.lstrip()
exp = Series(['aa ', 'bb \n', NA, 'cc '])
tm.assert_series_equal(result, exp)
result = values.str.rstrip()
exp = Series([' aa', ' bb', NA, 'cc'])
tm.assert_series_equal(result, exp)
def test_strip_lstrip_rstrip_mixed(self):
# mixed
mixed = Series([' aa ', NA, ' bb \t\n', True, datetime.today(), None,
1, 2.])
rs = Series(mixed).str.strip()
xp = Series(['aa', NA, 'bb', NA, NA, NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_almost_equal(rs, xp)
rs = Series(mixed).str.lstrip()
xp = Series(['aa ', NA, 'bb \t\n', NA, NA, NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_almost_equal(rs, xp)
rs = Series(mixed).str.rstrip()
xp = Series([' aa', NA, ' bb', NA, NA, NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_almost_equal(rs, xp)
def test_strip_lstrip_rstrip_unicode(self):
# unicode
values = Series([u(' aa '), u(' bb \n'), NA, u('cc ')])
result = values.str.strip()
exp = Series([u('aa'), u('bb'), NA, u('cc')])
tm.assert_series_equal(result, exp)
result = values.str.lstrip()
exp = Series([u('aa '), u('bb \n'), NA, u('cc ')])
tm.assert_series_equal(result, exp)
result = values.str.rstrip()
exp = Series([u(' aa'), u(' bb'), NA, u('cc')])
tm.assert_series_equal(result, exp)
def test_strip_lstrip_rstrip_args(self):
values = Series(['xxABCxx', 'xx BNSD', 'LDFJH xx'])
rs = values.str.strip('x')
xp = Series(['ABC', ' BNSD', 'LDFJH '])
assert_series_equal(rs, xp)
rs = values.str.lstrip('x')
xp = Series(['ABCxx', ' BNSD', 'LDFJH xx'])
assert_series_equal(rs, xp)
rs = values.str.rstrip('x')
xp = Series(['xxABC', 'xx BNSD', 'LDFJH '])
assert_series_equal(rs, xp)
def test_strip_lstrip_rstrip_args_unicode(self):
values = Series([u('xxABCxx'), u('xx BNSD'), u('LDFJH xx')])
rs = values.str.strip(u('x'))
xp = Series(['ABC', ' BNSD', 'LDFJH '])
assert_series_equal(rs, xp)
rs = values.str.lstrip(u('x'))
xp = Series(['ABCxx', ' BNSD', 'LDFJH xx'])
assert_series_equal(rs, xp)
rs = values.str.rstrip(u('x'))
xp = Series(['xxABC', 'xx BNSD', 'LDFJH '])
assert_series_equal(rs, xp)
def test_wrap(self):
# test values are: two words less than width, two words equal to width,
# two words greater than width, one word less than width, one word
# equal to width, one word greater than width, multiple tokens with
# trailing whitespace equal to width
values = Series([u('hello world'), u('hello world!'), u(
'hello world!!'), u('abcdefabcde'), u('abcdefabcdef'), u(
'abcdefabcdefa'), u('ab ab ab ab '), u('ab ab ab ab a'), u(
'\t')])
# expected values
xp = Series([u('hello world'), u('hello world!'), u('hello\nworld!!'),
u('abcdefabcde'), u('abcdefabcdef'), u('abcdefabcdef\na'),
u('ab ab ab ab'), u('ab ab ab ab\na'), u('')])
rs = values.str.wrap(12, break_long_words=True)
assert_series_equal(rs, xp)
# test with pre and post whitespace (non-unicode), NaN, and non-ascii
# Unicode
values = Series([' pre ', np.nan, u('\xac\u20ac\U00008000 abadcafe')
])
xp = Series([' pre', NA, u('\xac\u20ac\U00008000 ab\nadcafe')])
rs = values.str.wrap(6)
assert_series_equal(rs, xp)
def test_get(self):
values = Series(['a_b_c', 'c_d_e', np.nan, 'f_g_h'])
result = values.str.split('_').str.get(1)
expected = Series(['b', 'd', np.nan, 'g'])
tm.assert_series_equal(result, expected)
# mixed
mixed = Series(['a_b_c', NA, 'c_d_e', True, datetime.today(), None, 1,
2.])
rs = Series(mixed).str.split('_').str.get(1)
xp = Series(['b', NA, 'd', NA, NA, NA, NA, NA])
assert isinstance(rs, Series)
tm.assert_almost_equal(rs, xp)
# unicode
values = Series([u('a_b_c'), u('c_d_e'), np.nan, u('f_g_h')])
result = values.str.split('_').str.get(1)
expected = Series([u('b'), u('d'), np.nan, u('g')])
tm.assert_series_equal(result, expected)
# bounds testing
values = Series(['1_2_3_4_5', '6_7_8_9_10', '11_12'])
# positive index
result = values.str.split('_').str.get(2)
expected = Series(['3', '8', np.nan])
tm.assert_series_equal(result, expected)
# negative index
result = values.str.split('_').str.get(-3)
expected = Series(['3', '8', np.nan])
tm.assert_series_equal(result, expected)
def test_get_complex(self):
# GH 20671, getting value not in dict raising `KeyError`
values = Series([(1, 2, 3), [1, 2, 3], {1, 2, 3},
{1: 'a', 2: 'b', 3: 'c'}])
result = values.str.get(1)
expected = Series([2, 2, np.nan, 'a'])
tm.assert_series_equal(result, expected)
result = values.str.get(-1)
expected = Series([3, 3, np.nan, np.nan])
tm.assert_series_equal(result, expected)
@pytest.mark.parametrize('to_type', [tuple, list, np.array])
def test_get_complex_nested(self, to_type):
values = Series([to_type([to_type([1, 2])])])
result = values.str.get(0)
expected = Series([to_type([1, 2])])
tm.assert_series_equal(result, expected)
result = values.str.get(1)
expected = Series([np.nan])
tm.assert_series_equal(result, expected)
def test_more_contains(self):
# PR #1179
s = Series(['A', 'B', 'C', 'Aaba', 'Baca', '', NA,
'CABA', 'dog', 'cat'])
result = s.str.contains('a')
expected = Series([False, False, False, True, True, False, np.nan,
False, False, True])
assert_series_equal(result, expected)
result = s.str.contains('a', case=False)
expected = Series([True, False, False, True, True, False, np.nan, True,
False, True])
assert_series_equal(result, expected)
result = s.str.contains('Aa')
expected = Series([False, False, False, True, False, False, np.nan,
False, False, False])
assert_series_equal(result, expected)
result = s.str.contains('ba')
expected = Series([False, False, False, True, False, False, np.nan,
False, False, False])
assert_series_equal(result, expected)
result = s.str.contains('ba', case=False)
expected = Series([False, False, False, True, True, False, np.nan,
True, False, False])
assert_series_equal(result, expected)
def test_contains_nan(self):
# PR #14171
s = Series([np.nan, np.nan, np.nan], dtype=np.object_)
result = s.str.contains('foo', na=False)
expected = Series([False, False, False], dtype=np.bool_)
assert_series_equal(result, expected)
result = s.str.contains('foo', na=True)
expected = Series([True, True, True], dtype=np.bool_)
assert_series_equal(result, expected)
result = s.str.contains('foo', na="foo")
expected = Series(["foo", "foo", "foo"], dtype=np.object_)
assert_series_equal(result, expected)
result = s.str.contains('foo')
expected = Series([np.nan, np.nan, np.nan], dtype=np.object_)
assert_series_equal(result, expected)
def test_more_replace(self):
# PR #1179
s = Series(['A', 'B', 'C', 'Aaba', 'Baca', '', NA, 'CABA',
'dog', 'cat'])
result = s.str.replace('A', 'YYY')
expected = Series(['YYY', 'B', 'C', 'YYYaba', 'Baca', '', NA,
'CYYYBYYY', 'dog', 'cat'])
assert_series_equal(result, expected)
result = s.str.replace('A', 'YYY', case=False)
expected = Series(['YYY', 'B', 'C', 'YYYYYYbYYY', 'BYYYcYYY', '', NA,
'CYYYBYYY', 'dog', 'cYYYt'])
assert_series_equal(result, expected)
result = s.str.replace('^.a|dog', 'XX-XX ', case=False)
expected = Series(['A', 'B', 'C', 'XX-XX ba', 'XX-XX ca', '', NA,
'XX-XX BA', 'XX-XX ', 'XX-XX t'])
assert_series_equal(result, expected)
def test_string_slice_get_syntax(self):
s = Series(['YYY', 'B', 'C', 'YYYYYYbYYY', 'BYYYcYYY', NA, 'CYYYBYYY',
'dog', 'cYYYt'])
result = s.str[0]
expected = s.str.get(0)
assert_series_equal(result, expected)
result = s.str[:3]
expected = s.str.slice(stop=3)
assert_series_equal(result, expected)
result = s.str[2::-1]
expected = s.str.slice(start=2, step=-1)
assert_series_equal(result, expected)
def test_string_slice_out_of_bounds(self):
s = Series([(1, 2), (1, ), (3, 4, 5)])
result = s.str[1]
expected = Series([2, np.nan, 4])
assert_series_equal(result, expected)
s = Series(['foo', 'b', 'ba'])
result = s.str[1]
expected = Series(['o', np.nan, 'a'])
assert_series_equal(result, expected)
def test_match_findall_flags(self):
data = {'Dave': 'dave@google.com',
'Steve': 'steve@gmail.com',
'Rob': 'rob@gmail.com',
'Wes': np.nan}
data = Series(data)
pat = r'([A-Z0-9._%+-]+)@([A-Z0-9.-]+)\.([A-Z]{2,4})'
result = data.str.extract(pat, flags=re.IGNORECASE, expand=True)
assert result.iloc[0].tolist() == ['dave', 'google', 'com']
result = data.str.match(pat, flags=re.IGNORECASE)
assert result[0]
result = data.str.findall(pat, flags=re.IGNORECASE)
assert result[0][0] == ('dave', 'google', 'com')
result = data.str.count(pat, flags=re.IGNORECASE)
assert result[0] == 1
with tm.assert_produces_warning(UserWarning):
result = data.str.contains(pat, flags=re.IGNORECASE)
assert result[0]
def test_encode_decode(self):
base = Series([u('a'), u('b'), u('a\xe4')])
series = base.str.encode('utf-8')
f = lambda x: x.decode('utf-8')
result = series.str.decode('utf-8')
exp = series.map(f)
tm.assert_series_equal(result, exp)
def test_encode_decode_errors(self):
encodeBase = Series([u('a'), u('b'), u('a\x9d')])
pytest.raises(UnicodeEncodeError, encodeBase.str.encode, 'cp1252')
f = lambda x: x.encode('cp1252', 'ignore')
result = encodeBase.str.encode('cp1252', 'ignore')
exp = encodeBase.map(f)
tm.assert_series_equal(result, exp)
decodeBase = Series([b'a', b'b', b'a\x9d'])
pytest.raises(UnicodeDecodeError, decodeBase.str.decode, 'cp1252')
f = lambda x: x.decode('cp1252', 'ignore')
result = decodeBase.str.decode('cp1252', 'ignore')
exp = decodeBase.map(f)
tm.assert_series_equal(result, exp)
def test_normalize(self):
values = ['ABC', u'ＡＢＣ', u'１２３', np.nan, u'ｱｲｴ']
s = Series(values, index=['a', 'b', 'c', 'd', 'e'])
normed = [u'ABC', u'ABC', u'123', np.nan, u'アイエ']
expected = Series(normed, index=['a', 'b', 'c', 'd', 'e'])
result = s.str.normalize('NFKC')
tm.assert_series_equal(result, expected)
expected = Series([u'ABC', u'ＡＢＣ', u'１２３', np.nan, u'ｱｲｴ'],
index=['a', 'b', 'c', 'd', 'e'])
result = s.str.normalize('NFC')
tm.assert_series_equal(result, expected)
with tm.assert_raises_regex(ValueError,
"invalid normalization form"):
s.str.normalize('xxx')
s = Index([u'ＡＢＣ', u'１２３', u'ｱｲｴ'])
expected = Index([u'ABC', u'123', u'アイエ'])
result = s.str.normalize('NFKC')
tm.assert_index_equal(result, expected)
def test_index_str_accessor_visibility(self):
from pandas.core.strings import StringMethods
if not compat.PY3:
cases = [(['a', 'b'], 'string'), (['a', u('b')], 'mixed'),
([u('a'), u('b')], 'unicode'),
(['a', 'b', 1], 'mixed-integer'),
(['a', 'b', 1.3], 'mixed'),
(['a', 'b', 1.3, 1], 'mixed-integer'),
(['aa', datetime(2011, 1, 1)], 'mixed')]
else:
cases = [(['a', 'b'], 'string'), (['a', u('b')], 'string'),
([u('a'), u('b')], 'string'),
(['a', 'b', 1], 'mixed-integer'),
(['a', 'b', 1.3], 'mixed'),
(['a', 'b', 1.3, 1], 'mixed-integer'),
(['aa', datetime(2011, 1, 1)], 'mixed')]
for values, tp in cases:
idx = Index(values)
assert isinstance(Series(values).str, StringMethods)
assert isinstance(idx.str, StringMethods)
assert idx.inferred_type == tp
for values, tp in cases:
idx = Index(values)
assert isinstance(Series(values).str, StringMethods)
assert isinstance(idx.str, StringMethods)
assert idx.inferred_type == tp
cases = [([1, np.nan], 'floating'),
([datetime(2011, 1, 1)], 'datetime64'),
([timedelta(1)], 'timedelta64')]
for values, tp in cases:
idx = Index(values)
message = 'Can only use .str accessor with string values'
with tm.assert_raises_regex(AttributeError, message):
Series(values).str
with tm.assert_raises_regex(AttributeError, message):
idx.str
assert idx.inferred_type == tp
# MultiIndex has mixed dtype, but not allow to use accessor
idx = MultiIndex.from_tuples([('a', 'b'), ('a', 'b')])
assert idx.inferred_type == 'mixed'
message = 'Can only use .str accessor with Index, not MultiIndex'
with tm.assert_raises_regex(AttributeError, message):
idx.str
def test_str_accessor_no_new_attributes(self):
# https://github.com/pandas-dev/pandas/issues/10673
s = Series(list('aabbcde'))
with tm.assert_raises_regex(AttributeError,
"You cannot add any new attribute"):
s.str.xlabel = "a"
def test_method_on_bytes(self):
lhs = Series(np.array(list('abc'), 'S1').astype(object))
rhs = Series(np.array(list('def'), 'S1').astype(object))
if compat.PY3:
pytest.raises(TypeError, lhs.str.cat, rhs, join='left')
else:
result = lhs.str.cat(rhs, join='left')
expected = Series(np.array(
['ad', 'be', 'cf'], 'S2').astype(object))
tm.assert_series_equal(result, expected)
Reference in a new issue Copy permalink