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Oct 22, 2019
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Remove TestData from series-tests test_timeseries.py #29150

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118 changes: 63 additions & 55 deletions pandas/tests/series/test_timeseries.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,6 @@
)
from pandas.core.indexes.datetimes import DatetimeIndex
from pandas.core.indexes.timedeltas import TimedeltaIndex
from pandas.tests.series.common import TestData
import pandas.util.testing as tm
from pandas.util.testing import (
assert_almost_equal,
Expand All @@ -47,32 +46,34 @@ def assert_range_equal(left, right):
assert left.tz == right.tz


class TestTimeSeries(TestData):
def test_shift(self):
shifted = self.ts.shift(1)
class TestTimeSeries:
def test_shift(self, datetime_series):
shifted = datetime_series.shift(1)
unshifted = shifted.shift(-1)

tm.assert_index_equal(shifted.index, self.ts.index)
tm.assert_index_equal(unshifted.index, self.ts.index)
tm.assert_numpy_array_equal(unshifted.dropna().values, self.ts.values[:-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 = self.ts.shift(1, freq=offset)
shifted = datetime_series.shift(1, freq=offset)
unshifted = shifted.shift(-1, freq=offset)

assert_series_equal(unshifted, self.ts)
assert_series_equal(unshifted, datetime_series)

unshifted = self.ts.shift(0, freq=offset)
assert_series_equal(unshifted, self.ts)
unshifted = datetime_series.shift(0, freq=offset)
assert_series_equal(unshifted, datetime_series)

shifted = self.ts.shift(1, freq="B")
shifted = datetime_series.shift(1, freq="B")
unshifted = shifted.shift(-1, freq="B")

assert_series_equal(unshifted, self.ts)
assert_series_equal(unshifted, datetime_series)

# corner case
unshifted = self.ts.shift(0)
assert_series_equal(unshifted, self.ts)
unshifted = datetime_series.shift(0)
assert_series_equal(unshifted, datetime_series)

# Shifting with PeriodIndex
ps = tm.makePeriodSeries()
Expand Down Expand Up @@ -208,7 +209,7 @@ def test_shift_dst(self):
tm.assert_series_equal(res, exp)
assert res.dtype == "datetime64[ns, US/Eastern]"

def test_tshift(self):
def test_tshift(self, datetime_series):
# PeriodIndex
ps = tm.makePeriodSeries()
shifted = ps.tshift(1)
Expand All @@ -227,34 +228,34 @@ def test_tshift(self):
ps.tshift(freq="M")

# DatetimeIndex
shifted = self.ts.tshift(1)
shifted = datetime_series.tshift(1)
unshifted = shifted.tshift(-1)

assert_series_equal(self.ts, unshifted)
assert_series_equal(datetime_series, unshifted)

shifted2 = self.ts.tshift(freq=self.ts.index.freq)
shifted2 = datetime_series.tshift(freq=datetime_series.index.freq)
assert_series_equal(shifted, shifted2)

inferred_ts = Series(
self.ts.values, Index(np.asarray(self.ts.index)), name="ts"
datetime_series.values, Index(np.asarray(datetime_series.index)), name="ts"
)
shifted = inferred_ts.tshift(1)
unshifted = shifted.tshift(-1)
assert_series_equal(shifted, self.ts.tshift(1))
assert_series_equal(shifted, datetime_series.tshift(1))
assert_series_equal(unshifted, inferred_ts)

no_freq = self.ts[[0, 5, 7]]
no_freq = datetime_series[[0, 5, 7]]
msg = "Freq was not given and was not set in the index"
with pytest.raises(ValueError, match=msg):
no_freq.tshift()

def test_truncate(self):
def test_truncate(self, datetime_series):
offset = BDay()

ts = self.ts[::3]
ts = datetime_series[::3]

start, end = self.ts.index[3], self.ts.index[6]
start_missing, end_missing = self.ts.index[2], self.ts.index[7]
start, end = datetime_series.index[3], datetime_series.index[6]
start_missing, end_missing = datetime_series.index[2], datetime_series.index[7]

# neither specified
truncated = ts.truncate()
Expand Down Expand Up @@ -288,16 +289,17 @@ def test_truncate(self):
assert_series_equal(truncated, expected)

# corner case, empty series returned
truncated = ts.truncate(after=self.ts.index[0] - offset)
truncated = ts.truncate(after=datetime_series.index[0] - offset)
assert len(truncated) == 0

truncated = ts.truncate(before=self.ts.index[-1] + offset)
truncated = ts.truncate(before=datetime_series.index[-1] + offset)
assert len(truncated) == 0

msg = "Truncate: 1999-12-31 00:00:00 must be after 2000-02-14 00:00:00"
with pytest.raises(ValueError, match=msg):
ts.truncate(
before=self.ts.index[-1] + offset, after=self.ts.index[0] - offset
before=datetime_series.index[-1] + offset,
after=datetime_series.index[0] - offset,
)

def test_truncate_nonsortedindex(self):
Expand Down Expand Up @@ -355,20 +357,20 @@ def test_asfreq_datetimeindex_empty_series(self):
)
tm.assert_index_equal(expected.index, result.index)

def test_pct_change(self):
rs = self.ts.pct_change(fill_method=None)
assert_series_equal(rs, self.ts / self.ts.shift(1) - 1)
def test_pct_change(self, datetime_series):
rs = datetime_series.pct_change(fill_method=None)
assert_series_equal(rs, datetime_series / datetime_series.shift(1) - 1)

rs = self.ts.pct_change(2)
filled = self.ts.fillna(method="pad")
rs = datetime_series.pct_change(2)
filled = datetime_series.fillna(method="pad")
assert_series_equal(rs, filled / filled.shift(2) - 1)

rs = self.ts.pct_change(fill_method="bfill", limit=1)
filled = self.ts.fillna(method="bfill", limit=1)
rs = datetime_series.pct_change(fill_method="bfill", limit=1)
filled = datetime_series.fillna(method="bfill", limit=1)
assert_series_equal(rs, filled / filled.shift(1) - 1)

rs = self.ts.pct_change(freq="5D")
filled = self.ts.fillna(method="pad")
rs = datetime_series.pct_change(freq="5D")
filled = datetime_series.fillna(method="pad")
assert_series_equal(
rs, (filled / filled.shift(freq="5D") - 1).reindex_like(filled)
)
Expand All @@ -391,46 +393,52 @@ def test_pct_change_shift_over_nas(self):
("14B", 14, None, None),
],
)
def test_pct_change_periods_freq(self, freq, periods, fill_method, limit):
def test_pct_change_periods_freq(
self, freq, periods, fill_method, limit, datetime_series
):
# GH 7292
rs_freq = self.ts.pct_change(freq=freq, fill_method=fill_method, limit=limit)
rs_periods = self.ts.pct_change(periods, fill_method=fill_method, limit=limit)
rs_freq = datetime_series.pct_change(
freq=freq, fill_method=fill_method, limit=limit
)
rs_periods = datetime_series.pct_change(
periods, fill_method=fill_method, limit=limit
)
assert_series_equal(rs_freq, rs_periods)

empty_ts = Series(index=self.ts.index)
empty_ts = Series(index=datetime_series.index)
rs_freq = empty_ts.pct_change(freq=freq, fill_method=fill_method, limit=limit)
rs_periods = empty_ts.pct_change(periods, fill_method=fill_method, limit=limit)
assert_series_equal(rs_freq, rs_periods)

def test_autocorr(self):
def test_autocorr(self, datetime_series):
# Just run the function
corr1 = self.ts.autocorr()
corr1 = datetime_series.autocorr()

# Now run it with the lag parameter
corr2 = self.ts.autocorr(lag=1)
corr2 = datetime_series.autocorr(lag=1)

# corr() with lag needs Series of at least length 2
if len(self.ts) <= 2:
if len(datetime_series) <= 2:
assert np.isnan(corr1)
assert np.isnan(corr2)
else:
assert corr1 == corr2

# Choose a random lag between 1 and length of Series - 2
# and compare the result with the Series corr() function
n = 1 + np.random.randint(max(1, len(self.ts) - 2))
corr1 = self.ts.corr(self.ts.shift(n))
corr2 = self.ts.autocorr(lag=n)
n = 1 + np.random.randint(max(1, len(datetime_series) - 2))
corr1 = datetime_series.corr(datetime_series.shift(n))
corr2 = datetime_series.autocorr(lag=n)

# corr() with lag needs Series of at least length 2
if len(self.ts) <= 2:
if len(datetime_series) <= 2:
assert np.isnan(corr1)
assert np.isnan(corr2)
else:
assert corr1 == corr2

def test_first_last_valid(self):
ts = self.ts.copy()
def test_first_last_valid(self, datetime_series):
ts = datetime_series.copy()
ts[:5] = np.NaN

index = ts.first_valid_index()
Expand Down Expand Up @@ -462,9 +470,9 @@ def test_first_last_valid(self):
assert ts.first_valid_index().freq == ts.index.freq
assert ts.last_valid_index().freq == ts.index.freq

def test_mpl_compat_hack(self):
result = self.ts[:, np.newaxis]
expected = self.ts.values[:, np.newaxis]
def test_mpl_compat_hack(self, datetime_series):
result = datetime_series[:, np.newaxis]
expected = datetime_series.values[:, np.newaxis]
assert_almost_equal(result, expected)

def test_timeseries_coercion(self):
Expand Down