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test_categorical.py
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test_categorical.py
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# -*- coding: utf-8 -*-
import pandas as pd
import numpy as np
from pandas import Series, DataFrame
from pandas.util.testing import assert_series_equal, assert_frame_equal
from pandas.util import testing as tm
class TestCategoricalIndex(tm.TestCase):
def setUp(self):
self.df = DataFrame({'A': np.arange(6, dtype='int64'),
'B': Series(list('aabbca')).astype(
'category', categories=list(
'cab'))}).set_index('B')
self.df2 = DataFrame({'A': np.arange(6, dtype='int64'),
'B': Series(list('aabbca')).astype(
'category', categories=list(
'cabe'))}).set_index('B')
self.df3 = DataFrame({'A': np.arange(6, dtype='int64'),
'B': (Series([1, 1, 2, 1, 3, 2])
.astype('category', categories=[3, 2, 1],
ordered=True))}).set_index('B')
self.df4 = DataFrame({'A': np.arange(6, dtype='int64'),
'B': (Series([1, 1, 2, 1, 3, 2])
.astype('category', categories=[3, 2, 1],
ordered=False))}).set_index('B')
def test_loc_scalar(self):
result = self.df.loc['a']
expected = (DataFrame({'A': [0, 1, 5],
'B': (Series(list('aaa'))
.astype('category',
categories=list('cab')))})
.set_index('B'))
assert_frame_equal(result, expected)
df = self.df.copy()
df.loc['a'] = 20
expected = (DataFrame({'A': [20, 20, 2, 3, 4, 20],
'B': (Series(list('aabbca'))
.astype('category',
categories=list('cab')))})
.set_index('B'))
assert_frame_equal(df, expected)
# value not in the categories
self.assertRaises(KeyError, lambda: df.loc['d'])
def f():
df.loc['d'] = 10
self.assertRaises(TypeError, f)
def f():
df.loc['d', 'A'] = 10
self.assertRaises(TypeError, f)
def f():
df.loc['d', 'C'] = 10
self.assertRaises(TypeError, f)
def test_loc_listlike(self):
# list of labels
result = self.df.loc[['c', 'a']]
expected = self.df.iloc[[4, 0, 1, 5]]
assert_frame_equal(result, expected, check_index_type=True)
result = self.df2.loc[['a', 'b', 'e']]
exp_index = pd.CategoricalIndex(
list('aaabbe'), categories=list('cabe'), name='B')
expected = DataFrame({'A': [0, 1, 5, 2, 3, np.nan]}, index=exp_index)
assert_frame_equal(result, expected, check_index_type=True)
# element in the categories but not in the values
self.assertRaises(KeyError, lambda: self.df2.loc['e'])
# assign is ok
df = self.df2.copy()
df.loc['e'] = 20
result = df.loc[['a', 'b', 'e']]
exp_index = pd.CategoricalIndex(
list('aaabbe'), categories=list('cabe'), name='B')
expected = DataFrame({'A': [0, 1, 5, 2, 3, 20]}, index=exp_index)
assert_frame_equal(result, expected)
df = self.df2.copy()
result = df.loc[['a', 'b', 'e']]
exp_index = pd.CategoricalIndex(
list('aaabbe'), categories=list('cabe'), name='B')
expected = DataFrame({'A': [0, 1, 5, 2, 3, np.nan]}, index=exp_index)
assert_frame_equal(result, expected, check_index_type=True)
# not all labels in the categories
self.assertRaises(KeyError, lambda: self.df2.loc[['a', 'd']])
def test_loc_listlike_dtypes(self):
# GH 11586
# unique categories and codes
index = pd.CategoricalIndex(['a', 'b', 'c'])
df = DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]}, index=index)
# unique slice
res = df.loc[['a', 'b']]
exp_index = pd.CategoricalIndex(['a', 'b'],
categories=index.categories)
exp = DataFrame({'A': [1, 2], 'B': [4, 5]}, index=exp_index)
tm.assert_frame_equal(res, exp, check_index_type=True)
# duplicated slice
res = df.loc[['a', 'a', 'b']]
exp_index = pd.CategoricalIndex(['a', 'a', 'b'],
categories=index.categories)
exp = DataFrame({'A': [1, 1, 2], 'B': [4, 4, 5]}, index=exp_index)
tm.assert_frame_equal(res, exp, check_index_type=True)
with tm.assertRaisesRegexp(
KeyError,
'a list-indexer must only include values that are '
'in the categories'):
df.loc[['a', 'x']]
# duplicated categories and codes
index = pd.CategoricalIndex(['a', 'b', 'a'])
df = DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]}, index=index)
# unique slice
res = df.loc[['a', 'b']]
exp = DataFrame({'A': [1, 3, 2],
'B': [4, 6, 5]},
index=pd.CategoricalIndex(['a', 'a', 'b']))
tm.assert_frame_equal(res, exp, check_index_type=True)
# duplicated slice
res = df.loc[['a', 'a', 'b']]
exp = DataFrame(
{'A': [1, 3, 1, 3, 2],
'B': [4, 6, 4, 6, 5
]}, index=pd.CategoricalIndex(['a', 'a', 'a', 'a', 'b']))
tm.assert_frame_equal(res, exp, check_index_type=True)
with tm.assertRaisesRegexp(
KeyError,
'a list-indexer must only include values '
'that are in the categories'):
df.loc[['a', 'x']]
# contains unused category
index = pd.CategoricalIndex(
['a', 'b', 'a', 'c'], categories=list('abcde'))
df = DataFrame({'A': [1, 2, 3, 4], 'B': [5, 6, 7, 8]}, index=index)
res = df.loc[['a', 'b']]
exp = DataFrame({'A': [1, 3, 2],
'B': [5, 7, 6]}, index=pd.CategoricalIndex(
['a', 'a', 'b'], categories=list('abcde')))
tm.assert_frame_equal(res, exp, check_index_type=True)
res = df.loc[['a', 'e']]
exp = DataFrame({'A': [1, 3, np.nan], 'B': [5, 7, np.nan]},
index=pd.CategoricalIndex(['a', 'a', 'e'],
categories=list('abcde')))
tm.assert_frame_equal(res, exp, check_index_type=True)
# duplicated slice
res = df.loc[['a', 'a', 'b']]
exp = DataFrame({'A': [1, 3, 1, 3, 2], 'B': [5, 7, 5, 7, 6]},
index=pd.CategoricalIndex(['a', 'a', 'a', 'a', 'b'],
categories=list('abcde')))
tm.assert_frame_equal(res, exp, check_index_type=True)
with tm.assertRaisesRegexp(
KeyError,
'a list-indexer must only include values '
'that are in the categories'):
df.loc[['a', 'x']]
def test_ix_categorical_index(self):
# GH 12531
df = pd.DataFrame(np.random.randn(3, 3),
index=list('ABC'), columns=list('XYZ'))
cdf = df.copy()
cdf.index = pd.CategoricalIndex(df.index)
cdf.columns = pd.CategoricalIndex(df.columns)
expect = pd.Series(df.ix['A', :], index=cdf.columns, name='A')
assert_series_equal(cdf.ix['A', :], expect)
expect = pd.Series(df.ix[:, 'X'], index=cdf.index, name='X')
assert_series_equal(cdf.ix[:, 'X'], expect)
exp_index = pd.CategoricalIndex(list('AB'), categories=['A', 'B', 'C'])
expect = pd.DataFrame(df.ix[['A', 'B'], :], columns=cdf.columns,
index=exp_index)
assert_frame_equal(cdf.ix[['A', 'B'], :], expect)
exp_columns = pd.CategoricalIndex(list('XY'),
categories=['X', 'Y', 'Z'])
expect = pd.DataFrame(df.ix[:, ['X', 'Y']], index=cdf.index,
columns=exp_columns)
assert_frame_equal(cdf.ix[:, ['X', 'Y']], expect)
# non-unique
df = pd.DataFrame(np.random.randn(3, 3),
index=list('ABA'), columns=list('XYX'))
cdf = df.copy()
cdf.index = pd.CategoricalIndex(df.index)
cdf.columns = pd.CategoricalIndex(df.columns)
exp_index = pd.CategoricalIndex(list('AA'), categories=['A', 'B'])
expect = pd.DataFrame(df.ix['A', :], columns=cdf.columns,
index=exp_index)
assert_frame_equal(cdf.ix['A', :], expect)
exp_columns = pd.CategoricalIndex(list('XX'), categories=['X', 'Y'])
expect = pd.DataFrame(df.ix[:, 'X'], index=cdf.index,
columns=exp_columns)
assert_frame_equal(cdf.ix[:, 'X'], expect)
expect = pd.DataFrame(df.ix[['A', 'B'], :], columns=cdf.columns,
index=pd.CategoricalIndex(list('AAB')))
assert_frame_equal(cdf.ix[['A', 'B'], :], expect)
expect = pd.DataFrame(df.ix[:, ['X', 'Y']], index=cdf.index,
columns=pd.CategoricalIndex(list('XXY')))
assert_frame_equal(cdf.ix[:, ['X', 'Y']], expect)
def test_read_only_source(self):
# GH 10043
rw_array = np.eye(10)
rw_df = DataFrame(rw_array)
ro_array = np.eye(10)
ro_array.setflags(write=False)
ro_df = DataFrame(ro_array)
assert_frame_equal(rw_df.iloc[[1, 2, 3]], ro_df.iloc[[1, 2, 3]])
assert_frame_equal(rw_df.iloc[[1]], ro_df.iloc[[1]])
assert_series_equal(rw_df.iloc[1], ro_df.iloc[1])
assert_frame_equal(rw_df.iloc[1:3], ro_df.iloc[1:3])
assert_frame_equal(rw_df.loc[[1, 2, 3]], ro_df.loc[[1, 2, 3]])
assert_frame_equal(rw_df.loc[[1]], ro_df.loc[[1]])
assert_series_equal(rw_df.loc[1], ro_df.loc[1])
assert_frame_equal(rw_df.loc[1:3], ro_df.loc[1:3])
def test_reindexing(self):
# reindexing
# convert to a regular index
result = self.df2.reindex(['a', 'b', 'e'])
expected = DataFrame({'A': [0, 1, 5, 2, 3, np.nan],
'B': Series(list('aaabbe'))}).set_index('B')
assert_frame_equal(result, expected, check_index_type=True)
result = self.df2.reindex(['a', 'b'])
expected = DataFrame({'A': [0, 1, 5, 2, 3],
'B': Series(list('aaabb'))}).set_index('B')
assert_frame_equal(result, expected, check_index_type=True)
result = self.df2.reindex(['e'])
expected = DataFrame({'A': [np.nan],
'B': Series(['e'])}).set_index('B')
assert_frame_equal(result, expected, check_index_type=True)
result = self.df2.reindex(['d'])
expected = DataFrame({'A': [np.nan],
'B': Series(['d'])}).set_index('B')
assert_frame_equal(result, expected, check_index_type=True)
# since we are actually reindexing with a Categorical
# then return a Categorical
cats = list('cabe')
result = self.df2.reindex(pd.Categorical(['a', 'd'], categories=cats))
expected = DataFrame({'A': [0, 1, 5, np.nan],
'B': Series(list('aaad')).astype(
'category', categories=cats)}).set_index('B')
assert_frame_equal(result, expected, check_index_type=True)
result = self.df2.reindex(pd.Categorical(['a'], categories=cats))
expected = DataFrame({'A': [0, 1, 5],
'B': Series(list('aaa')).astype(
'category', categories=cats)}).set_index('B')
assert_frame_equal(result, expected, check_index_type=True)
result = self.df2.reindex(['a', 'b', 'e'])
expected = DataFrame({'A': [0, 1, 5, 2, 3, np.nan],
'B': Series(list('aaabbe'))}).set_index('B')
assert_frame_equal(result, expected, check_index_type=True)
result = self.df2.reindex(['a', 'b'])
expected = DataFrame({'A': [0, 1, 5, 2, 3],
'B': Series(list('aaabb'))}).set_index('B')
assert_frame_equal(result, expected, check_index_type=True)
result = self.df2.reindex(['e'])
expected = DataFrame({'A': [np.nan],
'B': Series(['e'])}).set_index('B')
assert_frame_equal(result, expected, check_index_type=True)
# give back the type of categorical that we received
result = self.df2.reindex(pd.Categorical(
['a', 'd'], categories=cats, ordered=True))
expected = DataFrame(
{'A': [0, 1, 5, np.nan],
'B': Series(list('aaad')).astype('category', categories=cats,
ordered=True)}).set_index('B')
assert_frame_equal(result, expected, check_index_type=True)
result = self.df2.reindex(pd.Categorical(
['a', 'd'], categories=['a', 'd']))
expected = DataFrame({'A': [0, 1, 5, np.nan],
'B': Series(list('aaad')).astype(
'category', categories=['a', 'd'
])}).set_index('B')
assert_frame_equal(result, expected, check_index_type=True)
# passed duplicate indexers are not allowed
self.assertRaises(ValueError, lambda: self.df2.reindex(['a', 'a']))
# args NotImplemented ATM
self.assertRaises(NotImplementedError,
lambda: self.df2.reindex(['a'], method='ffill'))
self.assertRaises(NotImplementedError,
lambda: self.df2.reindex(['a'], level=1))
self.assertRaises(NotImplementedError,
lambda: self.df2.reindex(['a'], limit=2))
def test_loc_slice(self):
# slicing
# not implemented ATM
# GH9748
self.assertRaises(TypeError, lambda: self.df.loc[1:5])
# result = df.loc[1:5]
# expected = df.iloc[[1,2,3,4]]
# assert_frame_equal(result, expected)
def test_boolean_selection(self):
df3 = self.df3
df4 = self.df4
result = df3[df3.index == 'a']
expected = df3.iloc[[]]
assert_frame_equal(result, expected)
result = df4[df4.index == 'a']
expected = df4.iloc[[]]
assert_frame_equal(result, expected)
result = df3[df3.index == 1]
expected = df3.iloc[[0, 1, 3]]
assert_frame_equal(result, expected)
result = df4[df4.index == 1]
expected = df4.iloc[[0, 1, 3]]
assert_frame_equal(result, expected)
# since we have an ordered categorical
# CategoricalIndex([1, 1, 2, 1, 3, 2],
# categories=[3, 2, 1],
# ordered=True,
# name=u'B')
result = df3[df3.index < 2]
expected = df3.iloc[[4]]
assert_frame_equal(result, expected)
result = df3[df3.index > 1]
expected = df3.iloc[[]]
assert_frame_equal(result, expected)
# unordered
# cannot be compared
# CategoricalIndex([1, 1, 2, 1, 3, 2],
# categories=[3, 2, 1],
# ordered=False,
# name=u'B')
self.assertRaises(TypeError, lambda: df4[df4.index < 2])
self.assertRaises(TypeError, lambda: df4[df4.index > 1])
def test_indexing_with_category(self):
# https://github.com/pydata/pandas/issues/12564
# consistent result if comparing as Dataframe
cat = DataFrame({'A': ['foo', 'bar', 'baz']})
exp = DataFrame({'A': [True, False, False]})
res = (cat[['A']] == 'foo')
tm.assert_frame_equal(res, exp)
cat['A'] = cat['A'].astype('category')
res = (cat[['A']] == 'foo')
tm.assert_frame_equal(res, exp)