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- # coding=utf-8
- # pylint: disable-msg=E1101,W0612
- import numpy as np
- import pytest
- from pandas.compat import lrange, range
- import pandas as pd
- from pandas import DataFrame, Index, Series
- import pandas.util.testing as tm
- from pandas.util.testing import assert_series_equal
- def test_get():
- # GH 6383
- s = Series(np.array([43, 48, 60, 48, 50, 51, 50, 45, 57, 48, 56, 45,
- 51, 39, 55, 43, 54, 52, 51, 54]))
- result = s.get(25, 0)
- expected = 0
- assert result == expected
- s = Series(np.array([43, 48, 60, 48, 50, 51, 50, 45, 57, 48, 56,
- 45, 51, 39, 55, 43, 54, 52, 51, 54]),
- index=pd.Float64Index(
- [25.0, 36.0, 49.0, 64.0, 81.0, 100.0,
- 121.0, 144.0, 169.0, 196.0, 1225.0,
- 1296.0, 1369.0, 1444.0, 1521.0, 1600.0,
- 1681.0, 1764.0, 1849.0, 1936.0],
- dtype='object'))
- result = s.get(25, 0)
- expected = 43
- assert result == expected
- # GH 7407
- # with a boolean accessor
- df = pd.DataFrame({'i': [0] * 3, 'b': [False] * 3})
- vc = df.i.value_counts()
- result = vc.get(99, default='Missing')
- assert result == 'Missing'
- vc = df.b.value_counts()
- result = vc.get(False, default='Missing')
- assert result == 3
- result = vc.get(True, default='Missing')
- assert result == 'Missing'
- def test_get_nan():
- # GH 8569
- s = pd.Float64Index(range(10)).to_series()
- assert s.get(np.nan) is None
- assert s.get(np.nan, default='Missing') == 'Missing'
- def test_get_nan_multiple():
- # GH 8569
- # ensure that fixing "test_get_nan" above hasn't broken get
- # with multiple elements
- s = pd.Float64Index(range(10)).to_series()
- idx = [2, 30]
- with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
- assert_series_equal(s.get(idx),
- Series([2, np.nan], index=idx))
- idx = [2, np.nan]
- with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
- assert_series_equal(s.get(idx),
- Series([2, np.nan], index=idx))
- # GH 17295 - all missing keys
- idx = [20, 30]
- assert(s.get(idx) is None)
- idx = [np.nan, np.nan]
- assert(s.get(idx) is None)
- def test_delitem():
- # GH 5542
- # should delete the item inplace
- s = Series(lrange(5))
- del s[0]
- expected = Series(lrange(1, 5), index=lrange(1, 5))
- assert_series_equal(s, expected)
- del s[1]
- expected = Series(lrange(2, 5), index=lrange(2, 5))
- assert_series_equal(s, expected)
- # empty
- s = Series()
- with pytest.raises(KeyError, match=r"^0$"):
- del s[0]
- # only 1 left, del, add, del
- s = Series(1)
- del s[0]
- assert_series_equal(s, Series(dtype='int64', index=Index(
- [], dtype='int64')))
- s[0] = 1
- assert_series_equal(s, Series(1))
- del s[0]
- assert_series_equal(s, Series(dtype='int64', index=Index(
- [], dtype='int64')))
- # Index(dtype=object)
- s = Series(1, index=['a'])
- del s['a']
- assert_series_equal(s, Series(dtype='int64', index=Index(
- [], dtype='object')))
- s['a'] = 1
- assert_series_equal(s, Series(1, index=['a']))
- del s['a']
- assert_series_equal(s, Series(dtype='int64', index=Index(
- [], dtype='object')))
- def test_slice_float64():
- values = np.arange(10., 50., 2)
- index = Index(values)
- start, end = values[[5, 15]]
- s = Series(np.random.randn(20), index=index)
- result = s[start:end]
- expected = s.iloc[5:16]
- assert_series_equal(result, expected)
- result = s.loc[start:end]
- assert_series_equal(result, expected)
- df = DataFrame(np.random.randn(20, 3), index=index)
- result = df[start:end]
- expected = df.iloc[5:16]
- tm.assert_frame_equal(result, expected)
- result = df.loc[start:end]
- tm.assert_frame_equal(result, expected)
- def test_getitem_negative_out_of_bounds():
- s = Series(tm.rands_array(5, 10), index=tm.rands_array(10, 10))
- msg = "index out of bounds"
- with pytest.raises(IndexError, match=msg):
- s[-11]
- msg = "index -11 is out of bounds for axis 0 with size 10"
- with pytest.raises(IndexError, match=msg):
- s[-11] = 'foo'
- def test_getitem_regression():
- s = Series(lrange(5), index=lrange(5))
- result = s[lrange(5)]
- assert_series_equal(result, s)
- def test_getitem_setitem_slice_bug():
- s = Series(lrange(10), lrange(10))
- result = s[-12:]
- assert_series_equal(result, s)
- result = s[-7:]
- assert_series_equal(result, s[3:])
- result = s[:-12]
- assert_series_equal(result, s[:0])
- s = Series(lrange(10), lrange(10))
- s[-12:] = 0
- assert (s == 0).all()
- s[:-12] = 5
- assert (s == 0).all()
- def test_getitem_setitem_slice_integers():
- s = Series(np.random.randn(8), index=[2, 4, 6, 8, 10, 12, 14, 16])
- result = s[:4]
- expected = s.reindex([2, 4, 6, 8])
- assert_series_equal(result, expected)
- s[:4] = 0
- assert (s[:4] == 0).all()
- assert not (s[4:] == 0).any()
- def test_setitem_float_labels():
- # note labels are floats
- s = Series(['a', 'b', 'c'], index=[0, 0.5, 1])
- tmp = s.copy()
- s.loc[1] = 'zoo'
- tmp.iloc[2] = 'zoo'
- assert_series_equal(s, tmp)
- def test_slice_float_get_set(test_data):
- msg = (r"cannot do slice indexing on <class 'pandas\.core\.indexes"
- r"\.datetimes\.DatetimeIndex'> with these indexers \[{key}\]"
- r" of <(class|type) 'float'>")
- with pytest.raises(TypeError, match=msg.format(key=r"4\.0")):
- test_data.ts[4.0:10.0]
- with pytest.raises(TypeError, match=msg.format(key=r"4\.0")):
- test_data.ts[4.0:10.0] = 0
- with pytest.raises(TypeError, match=msg.format(key=r"4\.5")):
- test_data.ts[4.5:10.0]
- with pytest.raises(TypeError, match=msg.format(key=r"4\.5")):
- test_data.ts[4.5:10.0] = 0
- def test_slice_floats2():
- s = Series(np.random.rand(10), index=np.arange(10, 20, dtype=float))
- assert len(s.loc[12.0:]) == 8
- assert len(s.loc[12.5:]) == 7
- i = np.arange(10, 20, dtype=float)
- i[2] = 12.2
- s.index = i
- assert len(s.loc[12.0:]) == 8
- assert len(s.loc[12.5:]) == 7
- def test_int_indexing():
- s = Series(np.random.randn(6), index=[0, 0, 1, 1, 2, 2])
- with pytest.raises(KeyError, match=r"^5$"):
- s[5]
- with pytest.raises(KeyError, match=r"^'c'$"):
- s['c']
- # not monotonic
- s = Series(np.random.randn(6), index=[2, 2, 0, 0, 1, 1])
- with pytest.raises(KeyError, match=r"^5$"):
- s[5]
- with pytest.raises(KeyError, match=r"^'c'$"):
- s['c']
- def test_getitem_int64(test_data):
- idx = np.int64(5)
- assert test_data.ts[idx] == test_data.ts[5]
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