| Current File : //usr/local/lib64/python3.6/site-packages/pandas/tests/series/methods/test_shift.py |
import numpy as np
import pytest
from pandas.errors import NullFrequencyError
import pandas as pd
from pandas import (
DatetimeIndex,
Index,
NaT,
Series,
TimedeltaIndex,
date_range,
offsets,
)
import pandas._testing as tm
from pandas.tseries.offsets import BDay
class TestShift:
def test_shift(self, datetime_series):
shifted = datetime_series.shift(1)
unshifted = shifted.shift(-1)
tm.assert_index_equal(shifted.index, datetime_series.index)
tm.assert_index_equal(unshifted.index, datetime_series.index)
tm.assert_numpy_array_equal(
unshifted.dropna().values, datetime_series.values[:-1]
)
offset = BDay()
shifted = datetime_series.shift(1, freq=offset)
unshifted = shifted.shift(-1, freq=offset)
tm.assert_series_equal(unshifted, datetime_series)
unshifted = datetime_series.shift(0, freq=offset)
tm.assert_series_equal(unshifted, datetime_series)
shifted = datetime_series.shift(1, freq="B")
unshifted = shifted.shift(-1, freq="B")
tm.assert_series_equal(unshifted, datetime_series)
# corner case
unshifted = datetime_series.shift(0)
tm.assert_series_equal(unshifted, datetime_series)
# Shifting with PeriodIndex
ps = tm.makePeriodSeries()
shifted = ps.shift(1)
unshifted = shifted.shift(-1)
tm.assert_index_equal(shifted.index, ps.index)
tm.assert_index_equal(unshifted.index, ps.index)
tm.assert_numpy_array_equal(unshifted.dropna().values, ps.values[:-1])
shifted2 = ps.shift(1, "B")
shifted3 = ps.shift(1, BDay())
tm.assert_series_equal(shifted2, shifted3)
tm.assert_series_equal(ps, shifted2.shift(-1, "B"))
msg = "Given freq D does not match PeriodIndex freq B"
with pytest.raises(ValueError, match=msg):
ps.shift(freq="D")
# legacy support
shifted4 = ps.shift(1, freq="B")
tm.assert_series_equal(shifted2, shifted4)
shifted5 = ps.shift(1, freq=BDay())
tm.assert_series_equal(shifted5, shifted4)
# 32-bit taking
# GH#8129
index = date_range("2000-01-01", periods=5)
for dtype in ["int32", "int64"]:
s1 = Series(np.arange(5, dtype=dtype), index=index)
p = s1.iloc[1]
result = s1.shift(periods=p)
expected = Series([np.nan, 0, 1, 2, 3], index=index)
tm.assert_series_equal(result, expected)
# GH#8260
# with tz
s = Series(
date_range("2000-01-01 09:00:00", periods=5, tz="US/Eastern"), name="foo"
)
result = s - s.shift()
exp = Series(TimedeltaIndex(["NaT"] + ["1 days"] * 4), name="foo")
tm.assert_series_equal(result, exp)
# incompat tz
s2 = Series(date_range("2000-01-01 09:00:00", periods=5, tz="CET"), name="foo")
msg = "DatetimeArray subtraction must have the same timezones or no timezones"
with pytest.raises(TypeError, match=msg):
s - s2
def test_shift2(self):
ts = Series(
np.random.randn(5), index=date_range("1/1/2000", periods=5, freq="H")
)
result = ts.shift(1, freq="5T")
exp_index = ts.index.shift(1, freq="5T")
tm.assert_index_equal(result.index, exp_index)
# GH#1063, multiple of same base
result = ts.shift(1, freq="4H")
exp_index = ts.index + offsets.Hour(4)
tm.assert_index_equal(result.index, exp_index)
idx = DatetimeIndex(["2000-01-01", "2000-01-02", "2000-01-04"])
msg = "Cannot shift with no freq"
with pytest.raises(NullFrequencyError, match=msg):
idx.shift(1)
def test_shift_fill_value(self):
# GH#24128
ts = Series(
[1.0, 2.0, 3.0, 4.0, 5.0], index=date_range("1/1/2000", periods=5, freq="H")
)
exp = Series(
[0.0, 1.0, 2.0, 3.0, 4.0], index=date_range("1/1/2000", periods=5, freq="H")
)
# check that fill value works
result = ts.shift(1, fill_value=0.0)
tm.assert_series_equal(result, exp)
exp = Series(
[0.0, 0.0, 1.0, 2.0, 3.0], index=date_range("1/1/2000", periods=5, freq="H")
)
result = ts.shift(2, fill_value=0.0)
tm.assert_series_equal(result, exp)
ts = pd.Series([1, 2, 3])
res = ts.shift(2, fill_value=0)
assert res.dtype == ts.dtype
def test_shift_categorical_fill_value(self):
ts = pd.Series(["a", "b", "c", "d"], dtype="category")
res = ts.shift(1, fill_value="a")
expected = pd.Series(
pd.Categorical(
["a", "a", "b", "c"], categories=["a", "b", "c", "d"], ordered=False
)
)
tm.assert_equal(res, expected)
# check for incorrect fill_value
msg = "'fill_value=f' is not present in this Categorical's categories"
with pytest.raises(ValueError, match=msg):
ts.shift(1, fill_value="f")
def test_shift_dst(self):
# GH#13926
dates = date_range("2016-11-06", freq="H", periods=10, tz="US/Eastern")
s = Series(dates)
res = s.shift(0)
tm.assert_series_equal(res, s)
assert res.dtype == "datetime64[ns, US/Eastern]"
res = s.shift(1)
exp_vals = [NaT] + dates.astype(object).values.tolist()[:9]
exp = Series(exp_vals)
tm.assert_series_equal(res, exp)
assert res.dtype == "datetime64[ns, US/Eastern]"
res = s.shift(-2)
exp_vals = dates.astype(object).values.tolist()[2:] + [NaT, NaT]
exp = Series(exp_vals)
tm.assert_series_equal(res, exp)
assert res.dtype == "datetime64[ns, US/Eastern]"
for ex in [10, -10, 20, -20]:
res = s.shift(ex)
exp = Series([NaT] * 10, dtype="datetime64[ns, US/Eastern]")
tm.assert_series_equal(res, exp)
assert res.dtype == "datetime64[ns, US/Eastern]"
@pytest.mark.filterwarnings("ignore:tshift is deprecated:FutureWarning")
def test_tshift(self, datetime_series):
# TODO: remove this test when tshift deprecation is enforced
# PeriodIndex
ps = tm.makePeriodSeries()
shifted = ps.tshift(1)
unshifted = shifted.tshift(-1)
tm.assert_series_equal(unshifted, ps)
shifted2 = ps.tshift(freq="B")
tm.assert_series_equal(shifted, shifted2)
shifted3 = ps.tshift(freq=BDay())
tm.assert_series_equal(shifted, shifted3)
msg = "Given freq M does not match PeriodIndex freq B"
with pytest.raises(ValueError, match=msg):
ps.tshift(freq="M")
# DatetimeIndex
shifted = datetime_series.tshift(1)
unshifted = shifted.tshift(-1)
tm.assert_series_equal(datetime_series, unshifted)
shifted2 = datetime_series.tshift(freq=datetime_series.index.freq)
tm.assert_series_equal(shifted, shifted2)
inferred_ts = Series(
datetime_series.values, Index(np.asarray(datetime_series.index)), name="ts"
)
shifted = inferred_ts.tshift(1)
expected = datetime_series.tshift(1)
expected.index = expected.index._with_freq(None)
tm.assert_series_equal(shifted, expected)
unshifted = shifted.tshift(-1)
tm.assert_series_equal(unshifted, inferred_ts)
no_freq = datetime_series[[0, 5, 7]]
msg = "Freq was not set in the index hence cannot be inferred"
with pytest.raises(ValueError, match=msg):
no_freq.tshift()
def test_tshift_deprecated(self, datetime_series):
# GH#11631
with tm.assert_produces_warning(FutureWarning):
datetime_series.tshift()
def test_period_index_series_shift_with_freq(self):
ps = tm.makePeriodSeries()
shifted = ps.shift(1, freq="infer")
unshifted = shifted.shift(-1, freq="infer")
tm.assert_series_equal(unshifted, ps)
shifted2 = ps.shift(freq="B")
tm.assert_series_equal(shifted, shifted2)
shifted3 = ps.shift(freq=BDay())
tm.assert_series_equal(shifted, shifted3)
def test_datetime_series_shift_with_freq(self, datetime_series):
shifted = datetime_series.shift(1, freq="infer")
unshifted = shifted.shift(-1, freq="infer")
tm.assert_series_equal(datetime_series, unshifted)
shifted2 = datetime_series.shift(freq=datetime_series.index.freq)
tm.assert_series_equal(shifted, shifted2)
inferred_ts = Series(
datetime_series.values, Index(np.asarray(datetime_series.index)), name="ts"
)
shifted = inferred_ts.shift(1, freq="infer")
expected = datetime_series.shift(1, freq="infer")
expected.index = expected.index._with_freq(None)
tm.assert_series_equal(shifted, expected)
unshifted = shifted.shift(-1, freq="infer")
tm.assert_series_equal(unshifted, inferred_ts)
def test_period_index_series_shift_with_freq_error(self):
ps = tm.makePeriodSeries()
msg = "Given freq M does not match PeriodIndex freq B"
with pytest.raises(ValueError, match=msg):
ps.shift(freq="M")
def test_datetime_series_shift_with_freq_error(self, datetime_series):
no_freq = datetime_series[[0, 5, 7]]
msg = "Freq was not set in the index hence cannot be inferred"
with pytest.raises(ValueError, match=msg):
no_freq.shift(freq="infer")
def test_shift_int(self, datetime_series):
ts = datetime_series.astype(int)
shifted = ts.shift(1)
expected = ts.astype(float).shift(1)
tm.assert_series_equal(shifted, expected)
def test_shift_object_non_scalar_fill(self):
# shift requires scalar fill_value except for object dtype
ser = Series(range(3))
with pytest.raises(ValueError, match="fill_value must be a scalar"):
ser.shift(1, fill_value=[])
df = ser.to_frame()
with pytest.raises(ValueError, match="fill_value must be a scalar"):
df.shift(1, fill_value=np.arange(3))
obj_ser = ser.astype(object)
result = obj_ser.shift(1, fill_value={})
assert result[0] == {}
obj_df = obj_ser.to_frame()
result = obj_df.shift(1, fill_value={})
assert result.iloc[0, 0] == {}
def test_shift_categorical(self):
# GH#9416
s = pd.Series(["a", "b", "c", "d"], dtype="category")
tm.assert_series_equal(s.iloc[:-1], s.shift(1).shift(-1).dropna())
sp1 = s.shift(1)
tm.assert_index_equal(s.index, sp1.index)
assert np.all(sp1.values.codes[:1] == -1)
assert np.all(s.values.codes[:-1] == sp1.values.codes[1:])
sn2 = s.shift(-2)
tm.assert_index_equal(s.index, sn2.index)
assert np.all(sn2.values.codes[-2:] == -1)
assert np.all(s.values.codes[2:] == sn2.values.codes[:-2])
tm.assert_index_equal(s.values.categories, sp1.values.categories)
tm.assert_index_equal(s.values.categories, sn2.values.categories)
def test_shift_dt64values_int_fill_deprecated(self):
# GH#31971
ser = pd.Series([pd.Timestamp("2020-01-01"), pd.Timestamp("2020-01-02")])
with tm.assert_produces_warning(FutureWarning):
result = ser.shift(1, fill_value=0)
expected = pd.Series([pd.Timestamp(0), ser[0]])
tm.assert_series_equal(result, expected)
@pytest.mark.parametrize("periods", [1, 2, 3, 4])
def test_shift_preserve_freqstr(self, periods):
# GH#21275
ser = pd.Series(
range(periods),
index=pd.date_range("2016-1-1 00:00:00", periods=periods, freq="H"),
)
result = ser.shift(1, "2H")
expected = pd.Series(
range(periods),
index=pd.date_range("2016-1-1 02:00:00", periods=periods, freq="H"),
)
tm.assert_series_equal(result, expected)
@pytest.mark.parametrize(
"input_data, output_data",
[(np.empty(shape=(0,)), []), (np.ones(shape=(2,)), [np.nan, 1.0])],
)
def test_shift_non_writable_array(self, input_data, output_data):
# GH21049 Verify whether non writable numpy array is shiftable
input_data.setflags(write=False)
result = pd.Series(input_data).shift(1)
expected = pd.Series(output_data, dtype="float64")
tm.assert_series_equal(result, expected)