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REF/TST: method-specific files for DataFrame timeseries methods #32230

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7 changes: 7 additions & 0 deletions pandas/tests/frame/conftest.py
Original file line number Diff line number Diff line change
@@ -1,10 +1,17 @@
from itertools import product

import numpy as np
import pytest

from pandas import DataFrame, NaT, date_range
import pandas._testing as tm


@pytest.fixture(params=product([True, False], [True, False]))
def close_open_fixture(request):
return request.param
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if this does not have utility beyond the one test in pandas/tests/frame/methods/test_between_time.py, I would remove in a follow-up

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agreed



@pytest.fixture
def float_frame_with_na():
"""
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58 changes: 58 additions & 0 deletions pandas/tests/frame/methods/test_asfreq.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,58 @@
from datetime import datetime

import numpy as np

from pandas import DataFrame, DatetimeIndex, Series, date_range
import pandas._testing as tm

from pandas.tseries import offsets


class TestAsFreq:
def test_asfreq(self, datetime_frame):
offset_monthly = datetime_frame.asfreq(offsets.BMonthEnd())
rule_monthly = datetime_frame.asfreq("BM")

tm.assert_almost_equal(offset_monthly["A"], rule_monthly["A"])

filled = rule_monthly.asfreq("B", method="pad") # noqa
# TODO: actually check that this worked.

# don't forget!
filled_dep = rule_monthly.asfreq("B", method="pad") # noqa

# test does not blow up on length-0 DataFrame
zero_length = datetime_frame.reindex([])
result = zero_length.asfreq("BM")
assert result is not zero_length

def test_asfreq_datetimeindex(self):
df = DataFrame(
{"A": [1, 2, 3]},
index=[datetime(2011, 11, 1), datetime(2011, 11, 2), datetime(2011, 11, 3)],
)
df = df.asfreq("B")
assert isinstance(df.index, DatetimeIndex)

ts = df["A"].asfreq("B")
assert isinstance(ts.index, DatetimeIndex)

def test_asfreq_fillvalue(self):
# test for fill value during upsampling, related to issue 3715

# setup
rng = date_range("1/1/2016", periods=10, freq="2S")
ts = Series(np.arange(len(rng)), index=rng)
df = DataFrame({"one": ts})

# insert pre-existing missing value
df.loc["2016-01-01 00:00:08", "one"] = None

actual_df = df.asfreq(freq="1S", fill_value=9.0)
expected_df = df.asfreq(freq="1S").fillna(9.0)
expected_df.loc["2016-01-01 00:00:08", "one"] = None
tm.assert_frame_equal(expected_df, actual_df)

expected_series = ts.asfreq(freq="1S").fillna(9.0)
actual_series = ts.asfreq(freq="1S", fill_value=9.0)
tm.assert_series_equal(expected_series, actual_series)
86 changes: 86 additions & 0 deletions pandas/tests/frame/methods/test_at_time.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,86 @@
from datetime import time

import numpy as np
import pytest
import pytz

from pandas import DataFrame, date_range
import pandas._testing as tm


class TestAtTime:
def test_at_time(self):
rng = date_range("1/1/2000", "1/5/2000", freq="5min")
ts = DataFrame(np.random.randn(len(rng), 2), index=rng)
rs = ts.at_time(rng[1])
assert (rs.index.hour == rng[1].hour).all()
assert (rs.index.minute == rng[1].minute).all()
assert (rs.index.second == rng[1].second).all()

result = ts.at_time("9:30")
expected = ts.at_time(time(9, 30))
tm.assert_frame_equal(result, expected)

result = ts.loc[time(9, 30)]
expected = ts.loc[(rng.hour == 9) & (rng.minute == 30)]

tm.assert_frame_equal(result, expected)

# midnight, everything
rng = date_range("1/1/2000", "1/31/2000")
ts = DataFrame(np.random.randn(len(rng), 3), index=rng)

result = ts.at_time(time(0, 0))
tm.assert_frame_equal(result, ts)

# time doesn't exist
rng = date_range("1/1/2012", freq="23Min", periods=384)
ts = DataFrame(np.random.randn(len(rng), 2), rng)
rs = ts.at_time("16:00")
assert len(rs) == 0

@pytest.mark.parametrize(
"hour", ["1:00", "1:00AM", time(1), time(1, tzinfo=pytz.UTC)]
)
def test_at_time_errors(self, hour):
# GH#24043
dti = date_range("2018", periods=3, freq="H")
df = DataFrame(list(range(len(dti))), index=dti)
if getattr(hour, "tzinfo", None) is None:
result = df.at_time(hour)
expected = df.iloc[1:2]
tm.assert_frame_equal(result, expected)
else:
with pytest.raises(ValueError, match="Index must be timezone"):
df.at_time(hour)

def test_at_time_tz(self):
# GH#24043
dti = date_range("2018", periods=3, freq="H", tz="US/Pacific")
df = DataFrame(list(range(len(dti))), index=dti)
result = df.at_time(time(4, tzinfo=pytz.timezone("US/Eastern")))
expected = df.iloc[1:2]
tm.assert_frame_equal(result, expected)

def test_at_time_raises(self):
# GH#20725
df = DataFrame([[1, 2, 3], [4, 5, 6]])
with pytest.raises(TypeError): # index is not a DatetimeIndex
df.at_time("00:00")

@pytest.mark.parametrize("axis", ["index", "columns", 0, 1])
def test_at_time_axis(self, axis):
# issue 8839
rng = date_range("1/1/2000", "1/5/2000", freq="5min")
ts = DataFrame(np.random.randn(len(rng), len(rng)))
ts.index, ts.columns = rng, rng

indices = rng[(rng.hour == 9) & (rng.minute == 30) & (rng.second == 0)]

if axis in ["index", 0]:
expected = ts.loc[indices, :]
elif axis in ["columns", 1]:
expected = ts.loc[:, indices]

result = ts.at_time("9:30", axis=axis)
tm.assert_frame_equal(result, expected)
110 changes: 110 additions & 0 deletions pandas/tests/frame/methods/test_between_time.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,110 @@
from datetime import time

import numpy as np
import pytest

from pandas import DataFrame, date_range
import pandas._testing as tm


class TestBetweenTime:
def test_between_time(self, close_open_fixture):
rng = date_range("1/1/2000", "1/5/2000", freq="5min")
ts = DataFrame(np.random.randn(len(rng), 2), index=rng)
stime = time(0, 0)
etime = time(1, 0)
inc_start, inc_end = close_open_fixture

filtered = ts.between_time(stime, etime, inc_start, inc_end)
exp_len = 13 * 4 + 1
if not inc_start:
exp_len -= 5
if not inc_end:
exp_len -= 4

assert len(filtered) == exp_len
for rs in filtered.index:
t = rs.time()
if inc_start:
assert t >= stime
else:
assert t > stime

if inc_end:
assert t <= etime
else:
assert t < etime

result = ts.between_time("00:00", "01:00")
expected = ts.between_time(stime, etime)
tm.assert_frame_equal(result, expected)

# across midnight
rng = date_range("1/1/2000", "1/5/2000", freq="5min")
ts = DataFrame(np.random.randn(len(rng), 2), index=rng)
stime = time(22, 0)
etime = time(9, 0)

filtered = ts.between_time(stime, etime, inc_start, inc_end)
exp_len = (12 * 11 + 1) * 4 + 1
if not inc_start:
exp_len -= 4
if not inc_end:
exp_len -= 4

assert len(filtered) == exp_len
for rs in filtered.index:
t = rs.time()
if inc_start:
assert (t >= stime) or (t <= etime)
else:
assert (t > stime) or (t <= etime)

if inc_end:
assert (t <= etime) or (t >= stime)
else:
assert (t < etime) or (t >= stime)

def test_between_time_raises(self):
# GH#20725
df = DataFrame([[1, 2, 3], [4, 5, 6]])
with pytest.raises(TypeError): # index is not a DatetimeIndex
df.between_time(start_time="00:00", end_time="12:00")

def test_between_time_axis(self, axis):
# GH#8839
rng = date_range("1/1/2000", periods=100, freq="10min")
ts = DataFrame(np.random.randn(len(rng), len(rng)))
stime, etime = ("08:00:00", "09:00:00")
exp_len = 7

if axis in ["index", 0]:
ts.index = rng
assert len(ts.between_time(stime, etime)) == exp_len
assert len(ts.between_time(stime, etime, axis=0)) == exp_len

if axis in ["columns", 1]:
ts.columns = rng
selected = ts.between_time(stime, etime, axis=1).columns
assert len(selected) == exp_len

def test_between_time_axis_raises(self, axis):
# issue 8839
rng = date_range("1/1/2000", periods=100, freq="10min")
mask = np.arange(0, len(rng))
rand_data = np.random.randn(len(rng), len(rng))
ts = DataFrame(rand_data, index=rng, columns=rng)
stime, etime = ("08:00:00", "09:00:00")

msg = "Index must be DatetimeIndex"
if axis in ["columns", 1]:
ts.index = mask
with pytest.raises(TypeError, match=msg):
ts.between_time(stime, etime)
with pytest.raises(TypeError, match=msg):
ts.between_time(stime, etime, axis=0)

if axis in ["index", 0]:
ts.columns = mask
with pytest.raises(TypeError, match=msg):
ts.between_time(stime, etime, axis=1)
36 changes: 36 additions & 0 deletions pandas/tests/frame/methods/test_to_period.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,36 @@
import numpy as np
import pytest

from pandas import DataFrame, date_range, period_range
import pandas._testing as tm


class TestToPeriod:
def test_frame_to_period(self):
K = 5

dr = date_range("1/1/2000", "1/1/2001")
pr = period_range("1/1/2000", "1/1/2001")
df = DataFrame(np.random.randn(len(dr), K), index=dr)
df["mix"] = "a"

pts = df.to_period()
exp = df.copy()
exp.index = pr
tm.assert_frame_equal(pts, exp)

pts = df.to_period("M")
tm.assert_index_equal(pts.index, exp.index.asfreq("M"))

df = df.T
pts = df.to_period(axis=1)
exp = df.copy()
exp.columns = pr
tm.assert_frame_equal(pts, exp)

pts = df.to_period("M", axis=1)
tm.assert_index_equal(pts.columns, exp.columns.asfreq("M"))

msg = "No axis named 2 for object type <class 'pandas.core.frame.DataFrame'>"
with pytest.raises(ValueError, match=msg):
df.to_period(axis=2)
84 changes: 84 additions & 0 deletions pandas/tests/frame/methods/test_tz_convert.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,84 @@
import numpy as np
import pytest

from pandas import DataFrame, Index, MultiIndex, date_range
import pandas._testing as tm


class TestTZConvert:
def test_frame_tz_convert(self):
rng = date_range("1/1/2011", periods=200, freq="D", tz="US/Eastern")

df = DataFrame({"a": 1}, index=rng)
result = df.tz_convert("Europe/Berlin")
expected = DataFrame({"a": 1}, rng.tz_convert("Europe/Berlin"))
assert result.index.tz.zone == "Europe/Berlin"
tm.assert_frame_equal(result, expected)

df = df.T
result = df.tz_convert("Europe/Berlin", axis=1)
assert result.columns.tz.zone == "Europe/Berlin"
tm.assert_frame_equal(result, expected.T)

@pytest.mark.parametrize("fn", ["tz_localize", "tz_convert"])
def test_tz_convert_and_localize(self, fn):
l0 = date_range("20140701", periods=5, freq="D")
l1 = date_range("20140701", periods=5, freq="D")

int_idx = Index(range(5))

if fn == "tz_convert":
l0 = l0.tz_localize("UTC")
l1 = l1.tz_localize("UTC")

for idx in [l0, l1]:

l0_expected = getattr(idx, fn)("US/Pacific")
l1_expected = getattr(idx, fn)("US/Pacific")

df1 = DataFrame(np.ones(5), index=l0)
df1 = getattr(df1, fn)("US/Pacific")
tm.assert_index_equal(df1.index, l0_expected)

# MultiIndex
# GH7846
df2 = DataFrame(np.ones(5), MultiIndex.from_arrays([l0, l1]))

df3 = getattr(df2, fn)("US/Pacific", level=0)
assert not df3.index.levels[0].equals(l0)
tm.assert_index_equal(df3.index.levels[0], l0_expected)
tm.assert_index_equal(df3.index.levels[1], l1)
assert not df3.index.levels[1].equals(l1_expected)

df3 = getattr(df2, fn)("US/Pacific", level=1)
tm.assert_index_equal(df3.index.levels[0], l0)
assert not df3.index.levels[0].equals(l0_expected)
tm.assert_index_equal(df3.index.levels[1], l1_expected)
assert not df3.index.levels[1].equals(l1)

df4 = DataFrame(np.ones(5), MultiIndex.from_arrays([int_idx, l0]))

# TODO: untested
df5 = getattr(df4, fn)("US/Pacific", level=1) # noqa

tm.assert_index_equal(df3.index.levels[0], l0)
assert not df3.index.levels[0].equals(l0_expected)
tm.assert_index_equal(df3.index.levels[1], l1_expected)
assert not df3.index.levels[1].equals(l1)

# Bad Inputs

# Not DatetimeIndex / PeriodIndex
with pytest.raises(TypeError, match="DatetimeIndex"):
df = DataFrame(index=int_idx)
df = getattr(df, fn)("US/Pacific")

# Not DatetimeIndex / PeriodIndex
with pytest.raises(TypeError, match="DatetimeIndex"):
df = DataFrame(np.ones(5), MultiIndex.from_arrays([int_idx, l0]))
df = getattr(df, fn)("US/Pacific", level=0)

# Invalid level
with pytest.raises(ValueError, match="not valid"):
df = DataFrame(index=l0)
df = getattr(df, fn)("US/Pacific", level=1)
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