178 lines
5.2 KiB
Python
178 lines
5.2 KiB
Python
# coding=utf-8
|
|
|
|
import pytest
|
|
|
|
import numpy as np
|
|
from pandas import (offsets, Series, notna,
|
|
isna, date_range, Timestamp)
|
|
|
|
import pandas.util.testing as tm
|
|
|
|
from .common import TestData
|
|
|
|
|
|
class TestSeriesAsof(TestData):
|
|
|
|
def test_basic(self):
|
|
|
|
# array or list or dates
|
|
N = 50
|
|
rng = date_range('1/1/1990', periods=N, freq='53s')
|
|
ts = Series(np.random.randn(N), index=rng)
|
|
ts[15:30] = np.nan
|
|
dates = date_range('1/1/1990', periods=N * 3, freq='25s')
|
|
|
|
result = ts.asof(dates)
|
|
assert notna(result).all()
|
|
lb = ts.index[14]
|
|
ub = ts.index[30]
|
|
|
|
result = ts.asof(list(dates))
|
|
assert notna(result).all()
|
|
lb = ts.index[14]
|
|
ub = ts.index[30]
|
|
|
|
mask = (result.index >= lb) & (result.index < ub)
|
|
rs = result[mask]
|
|
assert (rs == ts[lb]).all()
|
|
|
|
val = result[result.index[result.index >= ub][0]]
|
|
assert ts[ub] == val
|
|
|
|
def test_scalar(self):
|
|
|
|
N = 30
|
|
rng = date_range('1/1/1990', periods=N, freq='53s')
|
|
ts = Series(np.arange(N), index=rng)
|
|
ts[5:10] = np.NaN
|
|
ts[15:20] = np.NaN
|
|
|
|
val1 = ts.asof(ts.index[7])
|
|
val2 = ts.asof(ts.index[19])
|
|
|
|
assert val1 == ts[4]
|
|
assert val2 == ts[14]
|
|
|
|
# accepts strings
|
|
val1 = ts.asof(str(ts.index[7]))
|
|
assert val1 == ts[4]
|
|
|
|
# in there
|
|
result = ts.asof(ts.index[3])
|
|
assert result == ts[3]
|
|
|
|
# no as of value
|
|
d = ts.index[0] - offsets.BDay()
|
|
assert np.isnan(ts.asof(d))
|
|
|
|
def test_with_nan(self):
|
|
# basic asof test
|
|
rng = date_range('1/1/2000', '1/2/2000', freq='4h')
|
|
s = Series(np.arange(len(rng)), index=rng)
|
|
r = s.resample('2h').mean()
|
|
|
|
result = r.asof(r.index)
|
|
expected = Series([0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6.],
|
|
index=date_range('1/1/2000', '1/2/2000', freq='2h'))
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
r.iloc[3:5] = np.nan
|
|
result = r.asof(r.index)
|
|
expected = Series([0, 0, 1, 1, 1, 1, 3, 3, 4, 4, 5, 5, 6.],
|
|
index=date_range('1/1/2000', '1/2/2000', freq='2h'))
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
r.iloc[-3:] = np.nan
|
|
result = r.asof(r.index)
|
|
expected = Series([0, 0, 1, 1, 1, 1, 3, 3, 4, 4, 4, 4, 4.],
|
|
index=date_range('1/1/2000', '1/2/2000', freq='2h'))
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
def test_periodindex(self):
|
|
from pandas import period_range, PeriodIndex
|
|
# array or list or dates
|
|
N = 50
|
|
rng = period_range('1/1/1990', periods=N, freq='H')
|
|
ts = Series(np.random.randn(N), index=rng)
|
|
ts[15:30] = np.nan
|
|
dates = date_range('1/1/1990', periods=N * 3, freq='37min')
|
|
|
|
result = ts.asof(dates)
|
|
assert notna(result).all()
|
|
lb = ts.index[14]
|
|
ub = ts.index[30]
|
|
|
|
result = ts.asof(list(dates))
|
|
assert notna(result).all()
|
|
lb = ts.index[14]
|
|
ub = ts.index[30]
|
|
|
|
pix = PeriodIndex(result.index.values, freq='H')
|
|
mask = (pix >= lb) & (pix < ub)
|
|
rs = result[mask]
|
|
assert (rs == ts[lb]).all()
|
|
|
|
ts[5:10] = np.nan
|
|
ts[15:20] = np.nan
|
|
|
|
val1 = ts.asof(ts.index[7])
|
|
val2 = ts.asof(ts.index[19])
|
|
|
|
assert val1 == ts[4]
|
|
assert val2 == ts[14]
|
|
|
|
# accepts strings
|
|
val1 = ts.asof(str(ts.index[7]))
|
|
assert val1 == ts[4]
|
|
|
|
# in there
|
|
assert ts.asof(ts.index[3]) == ts[3]
|
|
|
|
# no as of value
|
|
d = ts.index[0].to_timestamp() - offsets.BDay()
|
|
assert isna(ts.asof(d))
|
|
|
|
def test_errors(self):
|
|
|
|
s = Series([1, 2, 3],
|
|
index=[Timestamp('20130101'),
|
|
Timestamp('20130103'),
|
|
Timestamp('20130102')])
|
|
|
|
# non-monotonic
|
|
assert not s.index.is_monotonic
|
|
with pytest.raises(ValueError):
|
|
s.asof(s.index[0])
|
|
|
|
# subset with Series
|
|
N = 10
|
|
rng = date_range('1/1/1990', periods=N, freq='53s')
|
|
s = Series(np.random.randn(N), index=rng)
|
|
with pytest.raises(ValueError):
|
|
s.asof(s.index[0], subset='foo')
|
|
|
|
def test_all_nans(self):
|
|
# GH 15713
|
|
# series is all nans
|
|
result = Series([np.nan]).asof([0])
|
|
expected = Series([np.nan])
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
# testing non-default indexes
|
|
N = 50
|
|
rng = date_range('1/1/1990', periods=N, freq='53s')
|
|
|
|
dates = date_range('1/1/1990', periods=N * 3, freq='25s')
|
|
result = Series(np.nan, index=rng).asof(dates)
|
|
expected = Series(np.nan, index=dates)
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
# testing scalar input
|
|
date = date_range('1/1/1990', periods=N * 3, freq='25s')[0]
|
|
result = Series(np.nan, index=rng).asof(date)
|
|
assert isna(result)
|
|
|
|
# test name is propagated
|
|
result = Series(np.nan, index=[1, 2, 3, 4], name='test').asof([4, 5])
|
|
expected = Series(np.nan, index=[4, 5], name='test')
|
|
tm.assert_series_equal(result, expected)
|