140 lines
4.9 KiB
Python
140 lines
4.9 KiB
Python
import numpy as np
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from numpy.random import randn
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from datetime import timedelta
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import pandas as pd
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import pandas.util.testing as tm
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from pandas import (PeriodIndex, period_range, DataFrame, date_range,
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Index, to_datetime, DatetimeIndex)
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def _permute(obj):
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return obj.take(np.random.permutation(len(obj)))
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class TestPeriodIndex(object):
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def setup_method(self, method):
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pass
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def test_as_frame_columns(self):
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rng = period_range('1/1/2000', periods=5)
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df = DataFrame(randn(10, 5), columns=rng)
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ts = df[rng[0]]
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tm.assert_series_equal(ts, df.iloc[:, 0])
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# GH # 1211
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repr(df)
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ts = df['1/1/2000']
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tm.assert_series_equal(ts, df.iloc[:, 0])
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def test_frame_setitem(self):
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rng = period_range('1/1/2000', periods=5, name='index')
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df = DataFrame(randn(5, 3), index=rng)
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df['Index'] = rng
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rs = Index(df['Index'])
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tm.assert_index_equal(rs, rng, check_names=False)
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assert rs.name == 'Index'
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assert rng.name == 'index'
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rs = df.reset_index().set_index('index')
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assert isinstance(rs.index, PeriodIndex)
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tm.assert_index_equal(rs.index, rng)
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def test_frame_to_time_stamp(self):
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K = 5
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index = PeriodIndex(freq='A', start='1/1/2001', end='12/1/2009')
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df = DataFrame(randn(len(index), K), index=index)
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df['mix'] = 'a'
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exp_index = date_range('1/1/2001', end='12/31/2009', freq='A-DEC')
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result = df.to_timestamp('D', 'end')
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tm.assert_index_equal(result.index, exp_index)
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tm.assert_numpy_array_equal(result.values, df.values)
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exp_index = date_range('1/1/2001', end='1/1/2009', freq='AS-JAN')
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result = df.to_timestamp('D', 'start')
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tm.assert_index_equal(result.index, exp_index)
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def _get_with_delta(delta, freq='A-DEC'):
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return date_range(to_datetime('1/1/2001') + delta,
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to_datetime('12/31/2009') + delta, freq=freq)
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delta = timedelta(hours=23)
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result = df.to_timestamp('H', 'end')
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exp_index = _get_with_delta(delta)
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tm.assert_index_equal(result.index, exp_index)
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delta = timedelta(hours=23, minutes=59)
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result = df.to_timestamp('T', 'end')
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exp_index = _get_with_delta(delta)
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tm.assert_index_equal(result.index, exp_index)
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result = df.to_timestamp('S', 'end')
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delta = timedelta(hours=23, minutes=59, seconds=59)
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exp_index = _get_with_delta(delta)
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tm.assert_index_equal(result.index, exp_index)
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# columns
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df = df.T
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exp_index = date_range('1/1/2001', end='12/31/2009', freq='A-DEC')
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result = df.to_timestamp('D', 'end', axis=1)
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tm.assert_index_equal(result.columns, exp_index)
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tm.assert_numpy_array_equal(result.values, df.values)
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exp_index = date_range('1/1/2001', end='1/1/2009', freq='AS-JAN')
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result = df.to_timestamp('D', 'start', axis=1)
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tm.assert_index_equal(result.columns, exp_index)
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delta = timedelta(hours=23)
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result = df.to_timestamp('H', 'end', axis=1)
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exp_index = _get_with_delta(delta)
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tm.assert_index_equal(result.columns, exp_index)
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delta = timedelta(hours=23, minutes=59)
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result = df.to_timestamp('T', 'end', axis=1)
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exp_index = _get_with_delta(delta)
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tm.assert_index_equal(result.columns, exp_index)
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result = df.to_timestamp('S', 'end', axis=1)
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delta = timedelta(hours=23, minutes=59, seconds=59)
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exp_index = _get_with_delta(delta)
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tm.assert_index_equal(result.columns, exp_index)
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# invalid axis
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tm.assert_raises_regex(
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ValueError, 'axis', df.to_timestamp, axis=2)
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result1 = df.to_timestamp('5t', axis=1)
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result2 = df.to_timestamp('t', axis=1)
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expected = pd.date_range('2001-01-01', '2009-01-01', freq='AS')
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assert isinstance(result1.columns, DatetimeIndex)
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assert isinstance(result2.columns, DatetimeIndex)
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tm.assert_numpy_array_equal(result1.columns.asi8, expected.asi8)
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tm.assert_numpy_array_equal(result2.columns.asi8, expected.asi8)
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# PeriodIndex.to_timestamp always use 'infer'
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assert result1.columns.freqstr == 'AS-JAN'
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assert result2.columns.freqstr == 'AS-JAN'
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def test_frame_index_to_string(self):
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index = PeriodIndex(['2011-1', '2011-2', '2011-3'], freq='M')
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frame = DataFrame(np.random.randn(3, 4), index=index)
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# it works!
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frame.to_string()
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def test_align_frame(self):
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rng = period_range('1/1/2000', '1/1/2010', freq='A')
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ts = DataFrame(np.random.randn(len(rng), 3), index=rng)
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result = ts + ts[::2]
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expected = ts + ts
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expected.values[1::2] = np.nan
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tm.assert_frame_equal(result, expected)
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result = ts + _permute(ts[::2])
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tm.assert_frame_equal(result, expected)
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