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- """ test scalar indexing, including at and iat """
- import numpy as np
- import pytest
- from pandas import DataFrame, Series, Timedelta, Timestamp, date_range
- from pandas.tests.indexing.common import Base
- from pandas.util import testing as tm
- class TestScalar(Base):
- def test_at_and_iat_get(self):
- def _check(f, func, values=False):
- if f is not None:
- indicies = self.generate_indices(f, values)
- for i in indicies:
- result = getattr(f, func)[i]
- expected = self.get_value(f, i, values)
- tm.assert_almost_equal(result, expected)
- for o in self._objs:
- d = getattr(self, o)
- # iat
- for f in [d['ints'], d['uints']]:
- _check(f, 'iat', values=True)
- for f in [d['labels'], d['ts'], d['floats']]:
- if f is not None:
- pytest.raises(ValueError, self.check_values, f, 'iat')
- # at
- for f in [d['ints'], d['uints'], d['labels'],
- d['ts'], d['floats']]:
- _check(f, 'at')
- def test_at_and_iat_set(self):
- def _check(f, func, values=False):
- if f is not None:
- indicies = self.generate_indices(f, values)
- for i in indicies:
- getattr(f, func)[i] = 1
- expected = self.get_value(f, i, values)
- tm.assert_almost_equal(expected, 1)
- for t in self._objs:
- d = getattr(self, t)
- # iat
- for f in [d['ints'], d['uints']]:
- _check(f, 'iat', values=True)
- for f in [d['labels'], d['ts'], d['floats']]:
- if f is not None:
- pytest.raises(ValueError, _check, f, 'iat')
- # at
- for f in [d['ints'], d['uints'], d['labels'],
- d['ts'], d['floats']]:
- _check(f, 'at')
- def test_at_iat_coercion(self):
- # as timestamp is not a tuple!
- dates = date_range('1/1/2000', periods=8)
- df = DataFrame(np.random.randn(8, 4),
- index=dates,
- columns=['A', 'B', 'C', 'D'])
- s = df['A']
- result = s.at[dates[5]]
- xp = s.values[5]
- assert result == xp
- # GH 7729
- # make sure we are boxing the returns
- s = Series(['2014-01-01', '2014-02-02'], dtype='datetime64[ns]')
- expected = Timestamp('2014-02-02')
- for r in [lambda: s.iat[1], lambda: s.iloc[1]]:
- result = r()
- assert result == expected
- s = Series(['1 days', '2 days'], dtype='timedelta64[ns]')
- expected = Timedelta('2 days')
- for r in [lambda: s.iat[1], lambda: s.iloc[1]]:
- result = r()
- assert result == expected
- def test_iat_invalid_args(self):
- pass
- def test_imethods_with_dups(self):
- # GH6493
- # iat/iloc with dups
- s = Series(range(5), index=[1, 1, 2, 2, 3], dtype='int64')
- result = s.iloc[2]
- assert result == 2
- result = s.iat[2]
- assert result == 2
- pytest.raises(IndexError, lambda: s.iat[10])
- pytest.raises(IndexError, lambda: s.iat[-10])
- result = s.iloc[[2, 3]]
- expected = Series([2, 3], [2, 2], dtype='int64')
- tm.assert_series_equal(result, expected)
- df = s.to_frame()
- result = df.iloc[2]
- expected = Series(2, index=[0], name=2)
- tm.assert_series_equal(result, expected)
- result = df.iat[2, 0]
- assert result == 2
- def test_at_to_fail(self):
- # at should not fallback
- # GH 7814
- s = Series([1, 2, 3], index=list('abc'))
- result = s.at['a']
- assert result == 1
- pytest.raises(ValueError, lambda: s.at[0])
- df = DataFrame({'A': [1, 2, 3]}, index=list('abc'))
- result = df.at['a', 'A']
- assert result == 1
- pytest.raises(ValueError, lambda: df.at['a', 0])
- s = Series([1, 2, 3], index=[3, 2, 1])
- result = s.at[1]
- assert result == 3
- pytest.raises(ValueError, lambda: s.at['a'])
- df = DataFrame({0: [1, 2, 3]}, index=[3, 2, 1])
- result = df.at[1, 0]
- assert result == 3
- pytest.raises(ValueError, lambda: df.at['a', 0])
- # GH 13822, incorrect error string with non-unique columns when missing
- # column is accessed
- df = DataFrame({'x': [1.], 'y': [2.], 'z': [3.]})
- df.columns = ['x', 'x', 'z']
- # Check that we get the correct value in the KeyError
- with pytest.raises(KeyError, match=r"\['y'\] not in index"):
- df[['x', 'y', 'z']]
- def test_at_with_tz(self):
- # gh-15822
- df = DataFrame({'name': ['John', 'Anderson'],
- 'date': [Timestamp(2017, 3, 13, 13, 32, 56),
- Timestamp(2017, 2, 16, 12, 10, 3)]})
- df['date'] = df['date'].dt.tz_localize('Asia/Shanghai')
- expected = Timestamp('2017-03-13 13:32:56+0800', tz='Asia/Shanghai')
- result = df.loc[0, 'date']
- assert result == expected
- result = df.at[0, 'date']
- assert result == expected
- def test_mixed_index_at_iat_loc_iloc_series(self):
- # GH 19860
- s = Series([1, 2, 3, 4, 5], index=['a', 'b', 'c', 1, 2])
- for el, item in s.iteritems():
- assert s.at[el] == s.loc[el] == item
- for i in range(len(s)):
- assert s.iat[i] == s.iloc[i] == i + 1
- with pytest.raises(KeyError):
- s.at[4]
- with pytest.raises(KeyError):
- s.loc[4]
- def test_mixed_index_at_iat_loc_iloc_dataframe(self):
- # GH 19860
- df = DataFrame([[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]],
- columns=['a', 'b', 'c', 1, 2])
- for rowIdx, row in df.iterrows():
- for el, item in row.iteritems():
- assert df.at[rowIdx, el] == df.loc[rowIdx, el] == item
- for row in range(2):
- for i in range(5):
- assert df.iat[row, i] == df.iloc[row, i] == row * 5 + i
- with pytest.raises(KeyError):
- df.at[0, 3]
- with pytest.raises(KeyError):
- df.loc[0, 3]
- def test_iat_setter_incompatible_assignment(self):
- # GH 23236
- result = DataFrame({'a': [0, 1], 'b': [4, 5]})
- result.iat[0, 0] = None
- expected = DataFrame({"a": [None, 1], "b": [4, 5]})
- tm.assert_frame_equal(result, expected)
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