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Version:
0.23.4 ▾
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# -*- coding: utf-8 -*-
from __future__ import print_function
import pytest
from datetime import datetime
import re
from pandas.compat import (zip, range, lrange, StringIO)
from pandas import (DataFrame, Series, Index, date_range, compat,
Timestamp)
import pandas as pd
from numpy import nan
import numpy as np
from pandas.util.testing import (assert_series_equal,
assert_frame_equal)
import pandas.util.testing as tm
from pandas.tests.frame.common import TestData
class TestDataFrameReplace(TestData):
def test_replace_inplace(self):
self.tsframe['A'][:5] = nan
self.tsframe['A'][-5:] = nan
tsframe = self.tsframe.copy()
tsframe.replace(nan, 0, inplace=True)
assert_frame_equal(tsframe, self.tsframe.fillna(0))
# mixed type
mf = self.mixed_frame
mf.iloc[5:20, mf.columns.get_loc('foo')] = nan
mf.iloc[-10:, mf.columns.get_loc('A')] = nan
result = self.mixed_frame.replace(np.nan, 0)
expected = self.mixed_frame.fillna(value=0)
assert_frame_equal(result, expected)
tsframe = self.tsframe.copy()
tsframe.replace([nan], [0], inplace=True)
assert_frame_equal(tsframe, self.tsframe.fillna(0))
def test_regex_replace_scalar(self):
obj = {'a': list('ab..'), 'b': list('efgh')}
dfobj = DataFrame(obj)
mix = {'a': lrange(4), 'b': list('ab..')}
dfmix = DataFrame(mix)
# simplest cases
# regex -> value
# obj frame
res = dfobj.replace(r'\s*\.\s*', nan, regex=True)
assert_frame_equal(dfobj, res.fillna('.'))
# mixed
res = dfmix.replace(r'\s*\.\s*', nan, regex=True)
assert_frame_equal(dfmix, res.fillna('.'))
# regex -> regex
# obj frame
res = dfobj.replace(r'\s*(\.)\s*', r'\1\1\1', regex=True)
objc = obj.copy()
objc['a'] = ['a', 'b', '...', '...']
expec = DataFrame(objc)
assert_frame_equal(res, expec)
# with mixed
res = dfmix.replace(r'\s*(\.)\s*', r'\1\1\1', regex=True)
mixc = mix.copy()
mixc['b'] = ['a', 'b', '...', '...']
expec = DataFrame(mixc)
assert_frame_equal(res, expec)
# everything with compiled regexs as well
res = dfobj.replace(re.compile(r'\s*\.\s*'), nan, regex=True)
assert_frame_equal(dfobj, res.fillna('.'))
# mixed
res = dfmix.replace(re.compile(r'\s*\.\s*'), nan, regex=True)
assert_frame_equal(dfmix, res.fillna('.'))
# regex -> regex
# obj frame
res = dfobj.replace(re.compile(r'\s*(\.)\s*'), r'\1\1\1')
objc = obj.copy()
objc['a'] = ['a', 'b', '...', '...']
expec = DataFrame(objc)
assert_frame_equal(res, expec)
# with mixed
res = dfmix.replace(re.compile(r'\s*(\.)\s*'), r'\1\1\1')
mixc = mix.copy()
mixc['b'] = ['a', 'b', '...', '...']
expec = DataFrame(mixc)
assert_frame_equal(res, expec)
res = dfmix.replace(regex=re.compile(r'\s*(\.)\s*'), value=r'\1\1\1')
mixc = mix.copy()
mixc['b'] = ['a', 'b', '...', '...']
expec = DataFrame(mixc)
assert_frame_equal(res, expec)
res = dfmix.replace(regex=r'\s*(\.)\s*', value=r'\1\1\1')
mixc = mix.copy()
mixc['b'] = ['a', 'b', '...', '...']
expec = DataFrame(mixc)
assert_frame_equal(res, expec)
def test_regex_replace_scalar_inplace(self):
obj = {'a': list('ab..'), 'b': list('efgh')}
dfobj = DataFrame(obj)
mix = {'a': lrange(4), 'b': list('ab..')}
dfmix = DataFrame(mix)
# simplest cases
# regex -> value
# obj frame
res = dfobj.copy()
res.replace(r'\s*\.\s*', nan, regex=True, inplace=True)
assert_frame_equal(dfobj, res.fillna('.'))
# mixed
res = dfmix.copy()
res.replace(r'\s*\.\s*', nan, regex=True, inplace=True)
assert_frame_equal(dfmix, res.fillna('.'))
# regex -> regex
# obj frame
res = dfobj.copy()
res.replace(r'\s*(\.)\s*', r'\1\1\1', regex=True, inplace=True)
objc = obj.copy()
objc['a'] = ['a', 'b', '...', '...']
expec = DataFrame(objc)
assert_frame_equal(res, expec)
# with mixed
res = dfmix.copy()
res.replace(r'\s*(\.)\s*', r'\1\1\1', regex=True, inplace=True)
mixc = mix.copy()
mixc['b'] = ['a', 'b', '...', '...']
expec = DataFrame(mixc)
assert_frame_equal(res, expec)
# everything with compiled regexs as well
res = dfobj.copy()
res.replace(re.compile(r'\s*\.\s*'), nan, regex=True, inplace=True)
assert_frame_equal(dfobj, res.fillna('.'))
# mixed
res = dfmix.copy()
res.replace(re.compile(r'\s*\.\s*'), nan, regex=True, inplace=True)
assert_frame_equal(dfmix, res.fillna('.'))
# regex -> regex
# obj frame
res = dfobj.copy()
res.replace(re.compile(r'\s*(\.)\s*'), r'\1\1\1', regex=True,
inplace=True)
objc = obj.copy()
objc['a'] = ['a', 'b', '...', '...']
expec = DataFrame(objc)
assert_frame_equal(res, expec)
# with mixed
res = dfmix.copy()
res.replace(re.compile(r'\s*(\.)\s*'), r'\1\1\1', regex=True,
inplace=True)
mixc = mix.copy()
mixc['b'] = ['a', 'b', '...', '...']
expec = DataFrame(mixc)
assert_frame_equal(res, expec)
res = dfobj.copy()
res.replace(regex=r'\s*\.\s*', value=nan, inplace=True)
assert_frame_equal(dfobj, res.fillna('.'))
# mixed
res = dfmix.copy()
res.replace(regex=r'\s*\.\s*', value=nan, inplace=True)
assert_frame_equal(dfmix, res.fillna('.'))
# regex -> regex
# obj frame
res = dfobj.copy()
res.replace(regex=r'\s*(\.)\s*', value=r'\1\1\1', inplace=True)
objc = obj.copy()
objc['a'] = ['a', 'b', '...', '...']
expec = DataFrame(objc)
assert_frame_equal(res, expec)
# with mixed
res = dfmix.copy()
res.replace(regex=r'\s*(\.)\s*', value=r'\1\1\1', inplace=True)
mixc = mix.copy()
mixc['b'] = ['a', 'b', '...', '...']
expec = DataFrame(mixc)
assert_frame_equal(res, expec)
# everything with compiled regexs as well
res = dfobj.copy()
res.replace(regex=re.compile(r'\s*\.\s*'), value=nan, inplace=True)
assert_frame_equal(dfobj, res.fillna('.'))
# mixed
res = dfmix.copy()
res.replace(regex=re.compile(r'\s*\.\s*'), value=nan, inplace=True)
assert_frame_equal(dfmix, res.fillna('.'))
# regex -> regex
# obj frame
res = dfobj.copy()
res.replace(regex=re.compile(r'\s*(\.)\s*'), value=r'\1\1\1',
inplace=True)
objc = obj.copy()
objc['a'] = ['a', 'b', '...', '...']
expec = DataFrame(objc)
assert_frame_equal(res, expec)
# with mixed
res = dfmix.copy()
res.replace(regex=re.compile(r'\s*(\.)\s*'), value=r'\1\1\1',
inplace=True)
mixc = mix.copy()
mixc['b'] = ['a', 'b', '...', '...']
expec = DataFrame(mixc)
assert_frame_equal(res, expec)
def test_regex_replace_list_obj(self):
obj = {'a': list('ab..'), 'b': list('efgh'), 'c': list('helo')}
dfobj = DataFrame(obj)
# lists of regexes and values
# list of [re1, re2, ..., reN] -> [v1, v2, ..., vN]
to_replace_res = [r'\s*\.\s*', r'e|f|g']
values = [nan, 'crap']
res = dfobj.replace(to_replace_res, values, regex=True)
expec = DataFrame({'a': ['a', 'b', nan, nan], 'b': ['crap'] * 3 +
['h'], 'c': ['h', 'crap', 'l', 'o']})
assert_frame_equal(res, expec)
# list of [re1, re2, ..., reN] -> [re1, re2, .., reN]
to_replace_res = [r'\s*(\.)\s*', r'(e|f|g)']
values = [r'\1\1', r'\1_crap']
res = dfobj.replace(to_replace_res, values, regex=True)
expec = DataFrame({'a': ['a', 'b', '..', '..'], 'b': ['e_crap',
'f_crap',
'g_crap', 'h'],
'c': ['h', 'e_crap', 'l', 'o']})
assert_frame_equal(res, expec)
# list of [re1, re2, ..., reN] -> [(re1 or v1), (re2 or v2), ..., (reN
# or vN)]
to_replace_res = [r'\s*(\.)\s*', r'e']
values = [r'\1\1', r'crap']
res = dfobj.replace(to_replace_res, values, regex=True)
expec = DataFrame({'a': ['a', 'b', '..', '..'], 'b': ['crap', 'f', 'g',
'h'],
'c': ['h', 'crap', 'l', 'o']})
assert_frame_equal(res, expec)
to_replace_res = [r'\s*(\.)\s*', r'e']
values = [r'\1\1', r'crap']
res = dfobj.replace(value=values, regex=to_replace_res)
expec = DataFrame({'a': ['a', 'b', '..', '..'], 'b': ['crap', 'f', 'g',
'h'],
'c': ['h', 'crap', 'l', 'o']})
assert_frame_equal(res, expec)
def test_regex_replace_list_obj_inplace(self):
# same as above with inplace=True
# lists of regexes and values
obj = {'a': list('ab..'), 'b': list('efgh'), 'c': list('helo')}
dfobj = DataFrame(obj)
# lists of regexes and values
# list of [re1, re2, ..., reN] -> [v1, v2, ..., vN]
to_replace_res = [r'\s*\.\s*', r'e|f|g']
values = [nan, 'crap']
res = dfobj.copy()
res.replace(to_replace_res, values, inplace=True, regex=True)
expec = DataFrame({'a': ['a', 'b', nan, nan], 'b': ['crap'] * 3 +
['h'], 'c': ['h', 'crap', 'l', 'o']})
assert_frame_equal(res, expec)
# list of [re1, re2, ..., reN] -> [re1, re2, .., reN]
to_replace_res = [r'\s*(\.)\s*', r'(e|f|g)']
values = [r'\1\1', r'\1_crap']
res = dfobj.copy()
res.replace(to_replace_res, values, inplace=True, regex=True)
expec = DataFrame({'a': ['a', 'b', '..', '..'], 'b': ['e_crap',
'f_crap',
'g_crap', 'h'],
'c': ['h', 'e_crap', 'l', 'o']})
assert_frame_equal(res, expec)
# list of [re1, re2, ..., reN] -> [(re1 or v1), (re2 or v2), ..., (reN
# or vN)]
to_replace_res = [r'\s*(\.)\s*', r'e']
values = [r'\1\1', r'crap']
res = dfobj.copy()
res.replace(to_replace_res, values, inplace=True, regex=True)
expec = DataFrame({'a': ['a', 'b', '..', '..'], 'b': ['crap', 'f', 'g',
'h'],
'c': ['h', 'crap', 'l', 'o']})
assert_frame_equal(res, expec)
to_replace_res = [r'\s*(\.)\s*', r'e']
values = [r'\1\1', r'crap']
res = dfobj.copy()
res.replace(value=values, regex=to_replace_res, inplace=True)
expec = DataFrame({'a': ['a', 'b', '..', '..'], 'b': ['crap', 'f', 'g',
'h'],
'c': ['h', 'crap', 'l', 'o']})
assert_frame_equal(res, expec)
def test_regex_replace_list_mixed(self):
# mixed frame to make sure this doesn't break things
mix = {'a': lrange(4), 'b': list('ab..')}
dfmix = DataFrame(mix)
# lists of regexes and values
# list of [re1, re2, ..., reN] -> [v1, v2, ..., vN]
to_replace_res = [r'\s*\.\s*', r'a']
values = [nan, 'crap']
mix2 = {'a': lrange(4), 'b': list('ab..'), 'c': list('halo')}
dfmix2 = DataFrame(mix2)
res = dfmix2.replace(to_replace_res, values, regex=True)
expec = DataFrame({'a': mix2['a'], 'b': ['crap', 'b', nan, nan],
'c': ['h', 'crap', 'l', 'o']})
assert_frame_equal(res, expec)
# list of [re1, re2, ..., reN] -> [re1, re2, .., reN]
to_replace_res = [r'\s*(\.)\s*', r'(a|b)']
values = [r'\1\1', r'\1_crap']
res = dfmix.replace(to_replace_res, values, regex=True)
expec = DataFrame({'a': mix['a'], 'b': ['a_crap', 'b_crap', '..',
'..']})
assert_frame_equal(res, expec)
# list of [re1, re2, ..., reN] -> [(re1 or v1), (re2 or v2), ..., (reN
# or vN)]
to_replace_res = [r'\s*(\.)\s*', r'a', r'(b)']
values = [r'\1\1', r'crap', r'\1_crap']
res = dfmix.replace(to_replace_res, values, regex=True)
expec = DataFrame({'a': mix['a'], 'b': ['crap', 'b_crap', '..', '..']})
assert_frame_equal(res, expec)
to_replace_res = [r'\s*(\.)\s*', r'a', r'(b)']
values = [r'\1\1', r'crap', r'\1_crap']
res = dfmix.replace(regex=to_replace_res, value=values)
expec = DataFrame({'a': mix['a'], 'b': ['crap', 'b_crap', '..', '..']})
assert_frame_equal(res, expec)
def test_regex_replace_list_mixed_inplace(self):
mix = {'a': lrange(4), 'b': list('ab..')}
dfmix = DataFrame(mix)
# the same inplace
# lists of regexes and values
# list of [re1, re2, ..., reN] -> [v1, v2, ..., vN]
to_replace_res = [r'\s*\.\s*', r'a']
values = [nan, 'crap']
res = dfmix.copy()
res.replace(to_replace_res, values, inplace=True, regex=True)
expec = DataFrame({'a': mix['a'], 'b': ['crap', 'b', nan, nan]})
assert_frame_equal(res, expec)
# list of [re1, re2, ..., reN] -> [re1, re2, .., reN]
to_replace_res = [r'\s*(\.)\s*', r'(a|b)']
values = [r'\1\1', r'\1_crap']
res = dfmix.copy()
res.replace(to_replace_res, values, inplace=True, regex=True)
expec = DataFrame({'a': mix['a'], 'b': ['a_crap', 'b_crap', '..',
'..']})
assert_frame_equal(res, expec)
# list of [re1, re2, ..., reN] -> [(re1 or v1), (re2 or v2), ..., (reN
# or vN)]
to_replace_res = [r'\s*(\.)\s*', r'a', r'(b)']
values = [r'\1\1', r'crap', r'\1_crap']
res = dfmix.copy()
res.replace(to_replace_res, values, inplace=True, regex=True)
expec = DataFrame({'a': mix['a'], 'b': ['crap', 'b_crap', '..', '..']})
assert_frame_equal(res, expec)
to_replace_res = [r'\s*(\.)\s*', r'a', r'(b)']
values = [r'\1\1', r'crap', r'\1_crap']
res = dfmix.copy()
res.replace(regex=to_replace_res, value=values, inplace=True)
expec = DataFrame({'a': mix['a'], 'b': ['crap', 'b_crap', '..', '..']})
assert_frame_equal(res, expec)
def test_regex_replace_dict_mixed(self):
mix = {'a': lrange(4), 'b': list('ab..'), 'c': ['a', 'b', nan, 'd']}
dfmix = DataFrame(mix)
# dicts
# single dict {re1: v1}, search the whole frame
# need test for this...
# list of dicts {re1: v1, re2: v2, ..., re3: v3}, search the whole
# frame
res = dfmix.replace({'b': r'\s*\.\s*'}, {'b': nan}, regex=True)
res2 = dfmix.copy()
res2.replace({'b': r'\s*\.\s*'}, {'b': nan}, inplace=True, regex=True)
expec = DataFrame({'a': mix['a'], 'b': ['a', 'b', nan, nan], 'c':
mix['c']})
assert_frame_equal(res, expec)
assert_frame_equal(res2, expec)
# list of dicts {re1: re11, re2: re12, ..., reN: re1N}, search the
# whole frame
res = dfmix.replace({'b': r'\s*(\.)\s*'}, {'b': r'\1ty'}, regex=True)
res2 = dfmix.copy()
res2.replace({'b': r'\s*(\.)\s*'}, {'b': r'\1ty'}, inplace=True,
regex=True)
expec = DataFrame({'a': mix['a'], 'b': ['a', 'b', '.ty', '.ty'], 'c':
mix['c']})
assert_frame_equal(res, expec)
assert_frame_equal(res2, expec)
res = dfmix.replace(regex={'b': r'\s*(\.)\s*'}, value={'b': r'\1ty'})
res2 = dfmix.copy()
res2.replace(regex={'b': r'\s*(\.)\s*'}, value={'b': r'\1ty'},
inplace=True)
expec = DataFrame({'a': mix['a'], 'b': ['a', 'b', '.ty', '.ty'], 'c':
mix['c']})
assert_frame_equal(res, expec)
assert_frame_equal(res2, expec)
# scalar -> dict
# to_replace regex, {value: value}
expec = DataFrame({'a': mix['a'], 'b': [nan, 'b', '.', '.'], 'c':
mix['c']})
res = dfmix.replace('a', {'b': nan}, regex=True)
res2 = dfmix.copy()
res2.replace('a', {'b': nan}, regex=True, inplace=True)
assert_frame_equal(res, expec)
assert_frame_equal(res2, expec)
res = dfmix.replace('a', {'b': nan}, regex=True)
res2 = dfmix.copy()
res2.replace(regex='a', value={'b': nan}, inplace=True)
expec = DataFrame({'a': mix['a'], 'b': [nan, 'b', '.', '.'], 'c':
mix['c']})
assert_frame_equal(res, expec)
assert_frame_equal(res2, expec)
def test_regex_replace_dict_nested(self):
# nested dicts will not work until this is implemented for Series
mix = {'a': lrange(4), 'b': list('ab..'), 'c': ['a', 'b', nan, 'd']}
dfmix = DataFrame(mix)
res = dfmix.replace({'b': {r'\s*\.\s*': nan}}, regex=True)
res2 = dfmix.copy()
res4 = dfmix.copy()
res2.replace({'b': {r'\s*\.\s*': nan}}, inplace=True, regex=True)
res3 = dfmix.replace(regex={'b': {r'\s*\.\s*': nan}})
res4.replace(regex={'b': {r'\s*\.\s*': nan}}, inplace=True)
expec = DataFrame({'a': mix['a'], 'b': ['a', 'b', nan, nan], 'c':
mix['c']})
assert_frame_equal(res, expec)
assert_frame_equal(res2, expec)
assert_frame_equal(res3, expec)
assert_frame_equal(res4, expec)
def test_regex_replace_dict_nested_gh4115(self):
df = pd.DataFrame({'Type': ['Q', 'T', 'Q', 'Q', 'T'], 'tmp': 2})
expected = DataFrame({'Type': [0, 1, 0, 0, 1], 'tmp': 2})
result = df.replace({'Type': {'Q': 0, 'T': 1}})
assert_frame_equal(result, expected)
def test_regex_replace_list_to_scalar(self):
mix = {'a': lrange(4), 'b': list('ab..'), 'c': ['a', 'b', nan, 'd']}
df = DataFrame(mix)
expec = DataFrame({'a': mix['a'], 'b': np.array([nan] * 4),
'c': [nan, nan, nan, 'd']})
res = df.replace([r'\s*\.\s*', 'a|b'], nan, regex=True)
res2 = df.copy()
res3 = df.copy()
res2.replace([r'\s*\.\s*', 'a|b'], nan, regex=True, inplace=True)
res3.replace(regex=[r'\s*\.\s*', 'a|b'], value=nan, inplace=True)
assert_frame_equal(res, expec)
assert_frame_equal(res2, expec)
assert_frame_equal(res3, expec)
def test_regex_replace_str_to_numeric(self):
# what happens when you try to replace a numeric value with a regex?
mix = {'a': lrange(4), 'b': list('ab..'), 'c': ['a', 'b', nan, 'd']}
df = DataFrame(mix)
res = df.replace(r'\s*\.\s*', 0, regex=True)
res2 = df.copy()
res2.replace(r'\s*\.\s*', 0, inplace=True, regex=True)
res3 = df.copy()
res3.replace(regex=r'\s*\.\s*', value=0, inplace=True)
expec = DataFrame({'a': mix['a'], 'b': ['a', 'b', 0, 0], 'c':
mix['c']})
assert_frame_equal(res, expec)
assert_frame_equal(res2, expec)
assert_frame_equal(res3, expec)
def test_regex_replace_regex_list_to_numeric(self):
mix = {'a': lrange(4), 'b': list('ab..'), 'c': ['a', 'b', nan, 'd']}
df = DataFrame(mix)
res = df.replace([r'\s*\.\s*', 'b'], 0, regex=True)
res2 = df.copy()
res2.replace([r'\s*\.\s*', 'b'], 0, regex=True, inplace=True)
res3 = df.copy()
res3.replace(regex=[r'\s*\.\s*', 'b'], value=0, inplace=True)
expec = DataFrame({'a': mix['a'], 'b': ['a', 0, 0, 0], 'c': ['a', 0,
nan,
'd']})
assert_frame_equal(res, expec)
assert_frame_equal(res2, expec)
assert_frame_equal(res3, expec)
def test_regex_replace_series_of_regexes(self):
mix = {'a': lrange(4), 'b': list('ab..'), 'c': ['a', 'b', nan, 'd']}
df = DataFrame(mix)
s1 = Series({'b': r'\s*\.\s*'})
s2 = Series({'b': nan})
res = df.replace(s1, s2, regex=True)
res2 = df.copy()
res2.replace(s1, s2, inplace=True, regex=True)
res3 = df.copy()
res3.replace(regex=s1, value=s2, inplace=True)
expec = DataFrame({'a': mix['a'], 'b': ['a', 'b', nan, nan], 'c':
mix['c']})
assert_frame_equal(res, expec)
assert_frame_equal(res2, expec)
assert_frame_equal(res3, expec)
def test_regex_replace_numeric_to_object_conversion(self):
mix = {'a': lrange(4), 'b': list('ab..'), 'c': ['a', 'b', nan, 'd']}
df = DataFrame(mix)
expec = DataFrame({'a': ['a', 1, 2, 3], 'b': mix['b'], 'c': mix['c']})
res = df.replace(0, 'a')
assert_frame_equal(res, expec)
assert res.a.dtype == np.object_
def test_replace_regex_metachar(self):
metachars = '[]', '()', r'\d', r'\w', r'\s'
for metachar in metachars:
df = DataFrame({'a': [metachar, 'else']})
result = df.replace({'a': {metachar: 'paren'}})
expected = DataFrame({'a': ['paren', 'else']})
assert_frame_equal(result, expected)
def test_replace(self):
self.tsframe['A'][:5] = nan
self.tsframe['A'][-5:] = nan
zero_filled = self.tsframe.replace(nan, -1e8)
assert_frame_equal(zero_filled, self.tsframe.fillna(-1e8))
assert_frame_equal(zero_filled.replace(-1e8, nan), self.tsframe)
self.tsframe['A'][:5] = nan
self.tsframe['A'][-5:] = nan
self.tsframe['B'][:5] = -1e8
# empty
df = DataFrame(index=['a', 'b'])
assert_frame_equal(df, df.replace(5, 7))
# GH 11698
# test for mixed data types.
df = pd.DataFrame([('-', pd.to_datetime('20150101')),
('a', pd.to_datetime('20150102'))])
df1 = df.replace('-', np.nan)
expected_df = pd.DataFrame([(np.nan, pd.to_datetime('20150101')),
('a', pd.to_datetime('20150102'))])
assert_frame_equal(df1, expected_df)
def test_replace_list(self):
obj = {'a': list('ab..'), 'b': list('efgh'), 'c': list('helo')}
dfobj = DataFrame(obj)
# lists of regexes and values
# list of [v1, v2, ..., vN] -> [v1, v2, ..., vN]
to_replace_res = [r'.', r'e']
values = [nan, 'crap']
res = dfobj.replace(to_replace_res, values)
expec = DataFrame({'a': ['a', 'b', nan, nan],
'b': ['crap', 'f', 'g', 'h'], 'c': ['h', 'crap',
'l', 'o']})
assert_frame_equal(res, expec)
# list of [v1, v2, ..., vN] -> [v1, v2, .., vN]
to_replace_res = [r'.', r'f']
values = [r'..', r'crap']
res = dfobj.replace(to_replace_res, values)
expec = DataFrame({'a': ['a', 'b', '..', '..'], 'b': ['e', 'crap', 'g',
'h'],
'c': ['h', 'e', 'l', 'o']})
assert_frame_equal(res, expec)
def test_replace_series_dict(self):
# from GH 3064
df = DataFrame({'zero': {'a': 0.0, 'b': 1}, 'one': {'a': 2.0, 'b': 0}})
result = df.replace(0, {'zero': 0.5, 'one': 1.0})
expected = DataFrame(
{'zero': {'a': 0.5, 'b': 1}, 'one': {'a': 2.0, 'b': 1.0}})
assert_frame_equal(result, expected)
result = df.replace(0, df.mean())
assert_frame_equal(result, expected)
# series to series/dict
df = DataFrame({'zero': {'a': 0.0, 'b': 1}, 'one': {'a': 2.0, 'b': 0}})
s = Series({'zero': 0.0, 'one': 2.0})
result = df.replace(s, {'zero': 0.5, 'one': 1.0})
expected = DataFrame(
{'zero': {'a': 0.5, 'b': 1}, 'one': {'a': 1.0, 'b': 0.0}})
assert_frame_equal(result, expected)
result = df.replace(s, df.mean())
assert_frame_equal(result, expected)
def test_replace_convert(self):
# gh 3907
df = DataFrame([['foo', 'bar', 'bah'], ['bar', 'foo', 'bah']])
m = {'foo': 1, 'bar': 2, 'bah': 3}
rep = df.replace(m)
expec = Series([np.int64] * 3)
res = rep.dtypes
assert_series_equal(expec, res)
def test_replace_mixed(self):
mf = self.mixed_frame
mf.iloc[5:20, mf.columns.get_loc('foo')] = nan
mf.iloc[-10:, mf.columns.get_loc('A')] = nan
result = self.mixed_frame.replace(np.nan, -18)
expected = self.mixed_frame.fillna(value=-18)
assert_frame_equal(result, expected)
assert_frame_equal(result.replace(-18, nan), self.mixed_frame)
result = self.mixed_frame.replace(np.nan, -1e8)
expected = self.mixed_frame.fillna(value=-1e8)
assert_frame_equal(result, expected)
assert_frame_equal(result.replace(-1e8, nan), self.mixed_frame)
# int block upcasting
df = DataFrame({'A': Series([1.0, 2.0], dtype='float64'),
'B': Series([0, 1], dtype='int64')})
expected = DataFrame({'A': Series([1.0, 2.0], dtype='float64'),
'B': Series([0.5, 1], dtype='float64')})
result = df.replace(0, 0.5)
assert_frame_equal(result, expected)
df.replace(0, 0.5, inplace=True)
assert_frame_equal(df, expected)
# int block splitting
df = DataFrame({'A': Series([1.0, 2.0], dtype='float64'),
'B': Series([0, 1], dtype='int64'),
'C': Series([1, 2], dtype='int64')})
expected = DataFrame({'A': Series([1.0, 2.0], dtype='float64'),
'B': Series([0.5, 1], dtype='float64'),
'C': Series([1, 2], dtype='int64')})
result = df.replace(0, 0.5)
assert_frame_equal(result, expected)
# to object block upcasting
df = DataFrame({'A': Series([1.0, 2.0], dtype='float64'),
'B': Series([0, 1], dtype='int64')})
expected = DataFrame({'A': Series([1, 'foo'], dtype='object'),
'B': Series([0, 1], dtype='int64')})
result = df.replace(2, 'foo')
assert_frame_equal(result, expected)
expected = DataFrame({'A': Series(['foo', 'bar'], dtype='object'),
'B': Series([0, 'foo'], dtype='object')})
result = df.replace([1, 2], ['foo', 'bar'])
assert_frame_equal(result, expected)
# test case from
df = DataFrame({'A': Series([3, 0], dtype='int64'),
'B': Series([0, 3], dtype='int64')})
result = df.replace(3, df.mean().to_dict())
expected = df.copy().astype('float64')
m = df.mean()
expected.iloc[0, 0] = m[0]
expected.iloc[1, 1] = m[1]
assert_frame_equal(result, expected)
def test_replace_simple_nested_dict(self):
df = DataFrame({'col': range(1, 5)})
expected = DataFrame({'col': ['a', 2, 3, 'b']})
result = df.replace({'col': {1: 'a', 4: 'b'}})
assert_frame_equal(expected, result)
# in this case, should be the same as the not nested version
result = df.replace({1: 'a', 4: 'b'})
assert_frame_equal(expected, result)
def test_replace_simple_nested_dict_with_nonexistent_value(self):
df = DataFrame({'col': range(1, 5)})
expected = DataFrame({'col': ['a', 2, 3, 'b']})
result = df.replace({-1: '-', 1: 'a', 4: 'b'})
assert_frame_equal(expected, result)
result = df.replace({'col': {-1: '-', 1: 'a', 4: 'b'}})
assert_frame_equal(expected, result)
def test_replace_value_is_none(self):
orig_value = self.tsframe.iloc[0, 0]
orig2 = self.tsframe.iloc[1, 0]
self.tsframe.iloc[0, 0] = nan
self.tsframe.iloc[1, 0] = 1
result = self.tsframe.replace(to_replace={nan: 0})
expected = self.tsframe.T.replace(to_replace={nan: 0}).T
assert_frame_equal(result, expected)
result = self.tsframe.replace(to_replace={nan: 0, 1: -1e8})
tsframe = self.tsframe.copy()
tsframe.iloc[0, 0] = 0
tsframe.iloc[1, 0] = -1e8
expected = tsframe
assert_frame_equal(expected, result)
self.tsframe.iloc[0, 0] = orig_value
self.tsframe.iloc[1, 0] = orig2
def test_replace_for_new_dtypes(self):
# dtypes
tsframe = self.tsframe.copy().astype(np.float32)
tsframe['A'][:5] = nan
tsframe['A'][-5:] = nan
zero_filled = tsframe.replace(nan, -1e8)
assert_frame_equal(zero_filled, tsframe.fillna(-1e8))
assert_frame_equal(zero_filled.replace(-1e8, nan), tsframe)
tsframe['A'][:5] = nan
tsframe['A'][-5:] = nan
tsframe['B'][:5] = -1e8
b = tsframe['B']
b[b == -1e8] = nan
tsframe['B'] = b
result = tsframe.fillna(method='bfill')
assert_frame_equal(result, tsframe.fillna(method='bfill'))
def test_replace_dtypes(self):
# int
df = DataFrame({'ints': [1, 2, 3]})
result = df.replace(1, 0)
expected = DataFrame({'ints': [0, 2, 3]})
assert_frame_equal(result, expected)
df = DataFrame({'ints': [1, 2, 3]}, dtype=np.int32)
result = df.replace(1, 0)
expected = DataFrame({'ints': [0, 2, 3]}, dtype=np.int32)
assert_frame_equal(result, expected)
df = DataFrame({'ints': [1, 2, 3]}, dtype=np.int16)
result = df.replace(1, 0)
expected = DataFrame({'ints': [0, 2, 3]}, dtype=np.int16)
assert_frame_equal(result, expected)
# bools
df = DataFrame({'bools': [True, False, True]})
result = df.replace(False, True)
assert result.values.all()
# complex blocks
df = DataFrame({'complex': [1j, 2j, 3j]})
result = df.replace(1j, 0j)
expected = DataFrame({'complex': [0j, 2j, 3j]})
assert_frame_equal(result, expected)
# datetime blocks
prev = datetime.today()
now = datetime.today()
df = DataFrame({'datetime64': Index([prev, now, prev])})
result = df.replace(prev, now)
expected = DataFrame({'datetime64': Index([now] * 3)})
assert_frame_equal(result, expected)
def test_replace_input_formats_listlike(self):
# both dicts
to_rep = {'A': np.nan, 'B': 0, 'C': ''}
values = {'A': 0, 'B': -1, 'C': 'missing'}
df = DataFrame({'A': [np.nan, 0, np.inf], 'B': [0, 2, 5],
'C': ['', 'asdf', 'fd']})
filled = df.replace(to_rep, values)
expected = {}
for k, v in compat.iteritems(df):
expected[k] = v.replace(to_rep[k], values[k])
assert_frame_equal(filled, DataFrame(expected))
result = df.replace([0, 2, 5], [5, 2, 0])
expected = DataFrame({'A': [np.nan, 5, np.inf], 'B': [5, 2, 0],
'C': ['', 'asdf', 'fd']})
assert_frame_equal(result, expected)
# scalar to dict
values = {'A': 0, 'B': -1, 'C': 'missing'}
df = DataFrame({'A': [np.nan, 0, np.nan], 'B': [0, 2, 5],
'C': ['', 'asdf', 'fd']})
filled = df.replace(np.nan, values)
expected = {}
for k, v in compat.iteritems(df):
expected[k] = v.replace(np.nan, values[k])
assert_frame_equal(filled, DataFrame(expected))
# list to list
to_rep = [np.nan, 0, '']
values = [-2, -1, 'missing']
result = df.replace(to_rep, values)
expected = df.copy()
for i in range(len(to_rep)):
expected.replace(to_rep[i], values[i], inplace=True)
assert_frame_equal(result, expected)
pytest.raises(ValueError, df.replace, to_rep, values[1:])
def test_replace_input_formats_scalar(self):
df = DataFrame({'A': [np.nan, 0, np.inf], 'B': [0, 2, 5],
'C': ['', 'asdf', 'fd']})
# dict to scalar
to_rep = {'A': np.nan, 'B': 0, 'C': ''}
filled = df.replace(to_rep, 0)
expected = {}
for k, v in compat.iteritems(df):
expected[k] = v.replace(to_rep[k], 0)
assert_frame_equal(filled, DataFrame(expected))
pytest.raises(TypeError, df.replace, to_rep, [np.nan, 0, ''])
# list to scalar
to_rep = [np.nan, 0, '']
result = df.replace(to_rep, -1)
expected = df.copy()
for i in range(len(to_rep)):
expected.replace(to_rep[i], -1, inplace=True)
assert_frame_equal(result, expected)
def test_replace_limit(self):
pass
def test_replace_dict_no_regex(self):
answer = Series({0: 'Strongly Agree', 1: 'Agree', 2: 'Neutral', 3:
'Disagree', 4: 'Strongly Disagree'})
weights = {'Agree': 4, 'Disagree': 2, 'Neutral': 3, 'Strongly Agree':
5, 'Strongly Disagree': 1}
expected = Series({0: 5, 1: 4, 2: 3, 3: 2, 4: 1})
result = answer.replace(weights)
assert_series_equal(result, expected)
def test_replace_series_no_regex(self):
answer = Series({0: 'Strongly Agree', 1: 'Agree', 2: 'Neutral', 3:
'Disagree', 4: 'Strongly Disagree'})
weights = Series({'Agree': 4, 'Disagree': 2, 'Neutral': 3,
'Strongly Agree': 5, 'Strongly Disagree': 1})
expected = Series({0: 5, 1: 4, 2: 3, 3: 2, 4: 1})
result = answer.replace(weights)
assert_series_equal(result, expected)
def test_replace_dict_tuple_list_ordering_remains_the_same(self):
df = DataFrame(dict(A=[nan, 1]))
res1 = df.replace(to_replace={nan: 0, 1: -1e8})
res2 = df.replace(to_replace=(1, nan), value=[-1e8, 0])
res3 = df.replace(to_replace=[1, nan], value=[-1e8, 0])
expected = DataFrame({'A': [0, -1e8]})
assert_frame_equal(res1, res2)
assert_frame_equal(res2, res3)
assert_frame_equal(res3, expected)
def test_replace_doesnt_replace_without_regex(self):
raw = """fol T_opp T_Dir T_Enh
0 1 0 0 vo
1 2 vr 0 0
2 2 0 0 0
3 3 0 bt 0"""
df = pd.read_csv(StringIO(raw), sep=r'\s+')
res = df.replace({r'\D': 1})
assert_frame_equal(df, res)
def test_replace_bool_with_string(self):
df = DataFrame({'a': [True, False], 'b': list('ab')})
result = df.replace(True, 'a')
expected = DataFrame({'a': ['a', False], 'b': df.b})
assert_frame_equal(result, expected)
def test_replace_pure_bool_with_string_no_op(self):
df = DataFrame(np.random.rand(2, 2) > 0.5)
result = df.replace('asdf', 'fdsa')
assert_frame_equal(df, result)
def test_replace_bool_with_bool(self):
df = DataFrame(np.random.rand(2, 2) > 0.5)
result = df.replace(False, True)
expected = DataFrame(np.ones((2, 2), dtype=bool))
assert_frame_equal(result, expected)
def test_replace_with_dict_with_bool_keys(self):
df = DataFrame({0: [True, False], 1: [False, True]})
with tm.assert_raises_regex(TypeError, 'Cannot compare types .+'):
df.replace({'asdf': 'asdb', True: 'yes'})
def test_replace_truthy(self):
df = DataFrame({'a': [True, True]})
r = df.replace([np.inf, -np.inf], np.nan)
e = df
assert_frame_equal(r, e)
def test_replace_int_to_int_chain(self):
df = DataFrame({'a': lrange(1, 5)})
with tm.assert_raises_regex(ValueError,
"Replacement not allowed .+"):
df.replace({'a': dict(zip(range(1, 5), range(2, 6)))})
def test_replace_str_to_str_chain(self):
a = np.arange(1, 5)
astr = a.astype(str)
bstr = np.arange(2, 6).astype(str)
df = DataFrame({'a': astr})
with tm.assert_raises_regex(ValueError,
"Replacement not allowed .+"):
df.replace({'a': dict(zip(astr, bstr))})
def test_replace_swapping_bug(self):
df = pd.DataFrame({'a': [True, False, True]})
res = df.replace({'a': {True: 'Y', False: 'N'}})
expect = pd.DataFrame({'a': ['Y', 'N', 'Y']})
assert_frame_equal(res, expect)
df = pd.DataFrame({'a': [0, 1, 0]})
res = df.replace({'a': {0: 'Y', 1: 'N'}})
expect = pd.DataFrame({'a': ['Y', 'N', 'Y']})
assert_frame_equal(res, expect)
def test_replace_period(self):
d = {
'fname': {
'out_augmented_AUG_2011.json':
pd.Period(year=2011, month=8, freq='M'),
'out_augmented_JAN_2011.json':
pd.Period(year=2011, month=1, freq='M'),
'out_augmented_MAY_2012.json':
pd.Period(year=2012, month=5, freq='M'),
'out_augmented_SUBSIDY_WEEK.json':
pd.Period(year=2011, month=4, freq='M'),
'out_augmented_AUG_2012.json':
pd.Period(year=2012, month=8, freq='M'),
'out_augmented_MAY_2011.json':
pd.Period(year=2011, month=5, freq='M'),
'out_augmented_SEP_2013.json':
pd.Period(year=2013, month=9, freq='M')}}
df = pd.DataFrame(['out_augmented_AUG_2012.json',
'out_augmented_SEP_2013.json',
'out_augmented_SUBSIDY_WEEK.json',
'out_augmented_MAY_2012.json',
'out_augmented_MAY_2011.json',
'out_augmented_AUG_2011.json',
'out_augmented_JAN_2011.json'], columns=['fname'])
assert set(df.fname.values) == set(d['fname'].keys())
expected = DataFrame({'fname': [d['fname'][k]
for k in df.fname.values]})
result = df.replace(d)
assert_frame_equal(result, expected)
def test_replace_datetime(self):
d = {'fname':
{'out_augmented_AUG_2011.json': pd.Timestamp('2011-08'),
'out_augmented_JAN_2011.json': pd.Timestamp('2011-01'),
'out_augmented_MAY_2012.json': pd.Timestamp('2012-05'),
'out_augmented_SUBSIDY_WEEK.json': pd.Timestamp('2011-04'),
'out_augmented_AUG_2012.json': pd.Timestamp('2012-08'),
'out_augmented_MAY_2011.json': pd.Timestamp('2011-05'),
'out_augmented_SEP_2013.json': pd.Timestamp('2013-09')}}
df = pd.DataFrame(['out_augmented_AUG_2012.json',
'out_augmented_SEP_2013.json',
'out_augmented_SUBSIDY_WEEK.json',
'out_augmented_MAY_2012.json',
'out_augmented_MAY_2011.json',
'out_augmented_AUG_2011.json',
'out_augmented_JAN_2011.json'], columns=['fname'])
assert set(df.fname.values) == set(d['fname'].keys())
expected = DataFrame({'fname': [d['fname'][k]
for k in df.fname.values]})
result = df.replace(d)
assert_frame_equal(result, expected)
def test_replace_datetimetz(self):
# GH 11326
# behaving poorly when presented with a datetime64[ns, tz]
df = DataFrame({'A': date_range('20130101', periods=3,
tz='US/Eastern'),
'B': [0, np.nan, 2]})
result = df.replace(np.nan, 1)
expected = DataFrame({'A': date_range('20130101', periods=3,
tz='US/Eastern'),
'B': Series([0, 1, 2], dtype='float64')})
assert_frame_equal(result, expected)
result = df.fillna(1)
assert_frame_equal(result, expected)
result = df.replace(0, np.nan)
expected = DataFrame({'A': date_range('20130101', periods=3,
tz='US/Eastern'),
'B': [np.nan, np.nan, 2]})
assert_frame_equal(result, expected)
result = df.replace(Timestamp('20130102', tz='US/Eastern'),
Timestamp('20130104', tz='US/Eastern'))
expected = DataFrame({'A': [Timestamp('20130101', tz='US/Eastern'),
Timestamp('20130104', tz='US/Eastern'),
Timestamp('20130103', tz='US/Eastern')],
'B': [0, np.nan, 2]})
assert_frame_equal(result, expected)
result = df.copy()
result.iloc[1, 0] = np.nan
result = result.replace(
{'A': pd.NaT}, Timestamp('20130104', tz='US/Eastern'))
assert_frame_equal(result, expected)
# coerce to object
result = df.copy()
result.iloc[1, 0] = np.nan
result = result.replace(
{'A': pd.NaT}, Timestamp('20130104', tz='US/Pacific'))
expected = DataFrame({'A': [Timestamp('20130101', tz='US/Eastern'),
Timestamp('20130104', tz='US/Pacific'),
Timestamp('20130103', tz='US/Eastern')],
'B': [0, np.nan, 2]})
assert_frame_equal(result, expected)
result = df.copy()
result.iloc[1, 0] = np.nan
result = result.replace({'A': np.nan}, Timestamp('20130104'))
expected = DataFrame({'A': [Timestamp('20130101', tz='US/Eastern'),
Timestamp('20130104'),
Timestamp('20130103', tz='US/Eastern')],
'B': [0, np.nan, 2]})
assert_frame_equal(result, expected)
def test_replace_with_empty_dictlike(self):
# GH 15289
mix = {'a': lrange(4), 'b': list('ab..'), 'c': ['a', 'b', nan, 'd']}
df = DataFrame(mix)
assert_frame_equal(df, df.replace({}))
assert_frame_equal(df, df.replace(Series([])))
assert_frame_equal(df, df.replace({'b': {}}))
assert_frame_equal(df, df.replace(Series({'b': {}})))
@pytest.mark.parametrize("to_replace, method, expected", [
(0, 'bfill', {'A': [1, 1, 2],
'B': [5, nan, 7],
'C': ['a', 'b', 'c']}),
(nan, 'bfill', {'A': [0, 1, 2],
'B': [5.0, 7.0, 7.0],
'C': ['a', 'b', 'c']}),
('d', 'ffill', {'A': [0, 1, 2],
'B': [5, nan, 7],
'C': ['a', 'b', 'c']}),
([0, 2], 'bfill', {'A': [1, 1, 2],
'B': [5, nan, 7],
'C': ['a', 'b', 'c']}),
([1, 2], 'pad', {'A': [0, 0, 0],
'B': [5, nan, 7],
'C': ['a', 'b', 'c']}),
((1, 2), 'bfill', {'A': [0, 2, 2],
'B': [5, nan, 7],
'C': ['a', 'b', 'c']}),
(['b', 'c'], 'ffill', {'A': [0, 1, 2],
'B': [5, nan, 7],
'C': ['a', 'a', 'a']}),
])
def test_replace_method(self, to_replace, method, expected):
# GH 19632
df = DataFrame({'A': [0, 1, 2],
'B': [5, nan, 7],
'C': ['a', 'b', 'c']})
result = df.replace(to_replace=to_replace, value=None, method=method)
expected = DataFrame(expected)
assert_frame_equal(result, expected)