laywerrobot/lib/python3.6/site-packages/pandas/tests/frame/test_period.py

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2020-08-27 21:55:39 +02:00
import numpy as np
from numpy.random import randn
from datetime import timedelta
import pandas as pd
import pandas.util.testing as tm
from pandas import (PeriodIndex, period_range, DataFrame, date_range,
Index, to_datetime, DatetimeIndex)
def _permute(obj):
return obj.take(np.random.permutation(len(obj)))
class TestPeriodIndex(object):
def setup_method(self, method):
pass
def test_as_frame_columns(self):
rng = period_range('1/1/2000', periods=5)
df = DataFrame(randn(10, 5), columns=rng)
ts = df[rng[0]]
tm.assert_series_equal(ts, df.iloc[:, 0])
# GH # 1211
repr(df)
ts = df['1/1/2000']
tm.assert_series_equal(ts, df.iloc[:, 0])
def test_frame_setitem(self):
rng = period_range('1/1/2000', periods=5, name='index')
df = DataFrame(randn(5, 3), index=rng)
df['Index'] = rng
rs = Index(df['Index'])
tm.assert_index_equal(rs, rng, check_names=False)
assert rs.name == 'Index'
assert rng.name == 'index'
rs = df.reset_index().set_index('index')
assert isinstance(rs.index, PeriodIndex)
tm.assert_index_equal(rs.index, rng)
def test_frame_to_time_stamp(self):
K = 5
index = PeriodIndex(freq='A', start='1/1/2001', end='12/1/2009')
df = DataFrame(randn(len(index), K), index=index)
df['mix'] = 'a'
exp_index = date_range('1/1/2001', end='12/31/2009', freq='A-DEC')
result = df.to_timestamp('D', 'end')
tm.assert_index_equal(result.index, exp_index)
tm.assert_numpy_array_equal(result.values, df.values)
exp_index = date_range('1/1/2001', end='1/1/2009', freq='AS-JAN')
result = df.to_timestamp('D', 'start')
tm.assert_index_equal(result.index, exp_index)
def _get_with_delta(delta, freq='A-DEC'):
return date_range(to_datetime('1/1/2001') + delta,
to_datetime('12/31/2009') + delta, freq=freq)
delta = timedelta(hours=23)
result = df.to_timestamp('H', 'end')
exp_index = _get_with_delta(delta)
tm.assert_index_equal(result.index, exp_index)
delta = timedelta(hours=23, minutes=59)
result = df.to_timestamp('T', 'end')
exp_index = _get_with_delta(delta)
tm.assert_index_equal(result.index, exp_index)
result = df.to_timestamp('S', 'end')
delta = timedelta(hours=23, minutes=59, seconds=59)
exp_index = _get_with_delta(delta)
tm.assert_index_equal(result.index, exp_index)
# columns
df = df.T
exp_index = date_range('1/1/2001', end='12/31/2009', freq='A-DEC')
result = df.to_timestamp('D', 'end', axis=1)
tm.assert_index_equal(result.columns, exp_index)
tm.assert_numpy_array_equal(result.values, df.values)
exp_index = date_range('1/1/2001', end='1/1/2009', freq='AS-JAN')
result = df.to_timestamp('D', 'start', axis=1)
tm.assert_index_equal(result.columns, exp_index)
delta = timedelta(hours=23)
result = df.to_timestamp('H', 'end', axis=1)
exp_index = _get_with_delta(delta)
tm.assert_index_equal(result.columns, exp_index)
delta = timedelta(hours=23, minutes=59)
result = df.to_timestamp('T', 'end', axis=1)
exp_index = _get_with_delta(delta)
tm.assert_index_equal(result.columns, exp_index)
result = df.to_timestamp('S', 'end', axis=1)
delta = timedelta(hours=23, minutes=59, seconds=59)
exp_index = _get_with_delta(delta)
tm.assert_index_equal(result.columns, exp_index)
# invalid axis
tm.assert_raises_regex(
ValueError, 'axis', df.to_timestamp, axis=2)
result1 = df.to_timestamp('5t', axis=1)
result2 = df.to_timestamp('t', axis=1)
expected = pd.date_range('2001-01-01', '2009-01-01', freq='AS')
assert isinstance(result1.columns, DatetimeIndex)
assert isinstance(result2.columns, DatetimeIndex)
tm.assert_numpy_array_equal(result1.columns.asi8, expected.asi8)
tm.assert_numpy_array_equal(result2.columns.asi8, expected.asi8)
# PeriodIndex.to_timestamp always use 'infer'
assert result1.columns.freqstr == 'AS-JAN'
assert result2.columns.freqstr == 'AS-JAN'
def test_frame_index_to_string(self):
index = PeriodIndex(['2011-1', '2011-2', '2011-3'], freq='M')
frame = DataFrame(np.random.randn(3, 4), index=index)
# it works!
frame.to_string()
def test_align_frame(self):
rng = period_range('1/1/2000', '1/1/2010', freq='A')
ts = DataFrame(np.random.randn(len(rng), 3), index=rng)
result = ts + ts[::2]
expected = ts + ts
expected.values[1::2] = np.nan
tm.assert_frame_equal(result, expected)
result = ts + _permute(ts[::2])
tm.assert_frame_equal(result, expected)