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from datetime import timedelta
import numpy as np
import pytest
import pandas as pd
from pandas import Series, TimedeltaIndex, timedelta_range
import pandas._testing as tm
from pandas.tseries.offsets import DateOffset, Day, Hour
class TestTimedeltaIndexOps:
def test_value_counts_unique(self):
# GH 7735
idx = timedelta_range("1 days 09:00:00", freq="H", periods=10)
# create repeated values, 'n'th element is repeated by n+1 times
idx = TimedeltaIndex(np.repeat(idx.values, range(1, len(idx) + 1)))
exp_idx = timedelta_range("1 days 18:00:00", freq="-1H", periods=10)
exp_idx = exp_idx._with_freq(None)
expected = Series(range(10, 0, -1), index=exp_idx, dtype="int64")
obj = idx
tm.assert_series_equal(obj.value_counts(), expected)
obj = Series(idx)
tm.assert_series_equal(obj.value_counts(), expected)
expected = timedelta_range("1 days 09:00:00", freq="H", periods=10)
tm.assert_index_equal(idx.unique(), expected)
idx = TimedeltaIndex(
[
"1 days 09:00:00",
"1 days 09:00:00",
"1 days 09:00:00",
"1 days 08:00:00",
"1 days 08:00:00",
pd.NaT,
]
)
exp_idx = TimedeltaIndex(["1 days 09:00:00", "1 days 08:00:00"])
expected = Series([3, 2], index=exp_idx)
for obj in [idx, Series(idx)]:
tm.assert_series_equal(obj.value_counts(), expected)
exp_idx = TimedeltaIndex(["1 days 09:00:00", "1 days 08:00:00", pd.NaT])
expected = Series([3, 2, 1], index=exp_idx)
for obj in [idx, Series(idx)]:
tm.assert_series_equal(obj.value_counts(dropna=False), expected)
tm.assert_index_equal(idx.unique(), exp_idx)
def test_nonunique_contains(self):
# GH 9512
for idx in map(
TimedeltaIndex,
(
[0, 1, 0],
[0, 0, -1],
[0, -1, -1],
["00:01:00", "00:01:00", "00:02:00"],
["00:01:00", "00:01:00", "00:00:01"],
),
):
assert idx[0] in idx
def test_unknown_attribute(self):
# see gh-9680
tdi = pd.timedelta_range(start=0, periods=10, freq="1s")
ts = pd.Series(np.random.normal(size=10), index=tdi)
assert "foo" not in ts.__dict__.keys()
msg = "'Series' object has no attribute 'foo'"
with pytest.raises(AttributeError, match=msg):
ts.foo
def test_order(self):
# GH 10295
idx1 = TimedeltaIndex(["1 day", "2 day", "3 day"], freq="D", name="idx")
idx2 = TimedeltaIndex(["1 hour", "2 hour", "3 hour"], freq="H", name="idx")
for idx in [idx1, idx2]:
ordered = idx.sort_values()
tm.assert_index_equal(ordered, idx)
assert ordered.freq == idx.freq
ordered = idx.sort_values(ascending=False)
expected = idx[::-1]
tm.assert_index_equal(ordered, expected)
assert ordered.freq == expected.freq
assert ordered.freq.n == -1
ordered, indexer = idx.sort_values(return_indexer=True)
tm.assert_index_equal(ordered, idx)
tm.assert_numpy_array_equal(indexer, np.array([0, 1, 2]), check_dtype=False)
assert ordered.freq == idx.freq
ordered, indexer = idx.sort_values(return_indexer=True, ascending=False)
tm.assert_index_equal(ordered, idx[::-1])
assert ordered.freq == expected.freq
assert ordered.freq.n == -1
idx1 = TimedeltaIndex(
["1 hour", "3 hour", "5 hour", "2 hour ", "1 hour"], name="idx1"
)
exp1 = TimedeltaIndex(
["1 hour", "1 hour", "2 hour", "3 hour", "5 hour"], name="idx1"
)
idx2 = TimedeltaIndex(
["1 day", "3 day", "5 day", "2 day", "1 day"], name="idx2"
)
for idx, expected in [(idx1, exp1), (idx1, exp1), (idx1, exp1)]:
ordered = idx.sort_values()
tm.assert_index_equal(ordered, expected)
assert ordered.freq is None
ordered = idx.sort_values(ascending=False)
tm.assert_index_equal(ordered, expected[::-1])
assert ordered.freq is None
ordered, indexer = idx.sort_values(return_indexer=True)
tm.assert_index_equal(ordered, expected)
exp = np.array([0, 4, 3, 1, 2])
tm.assert_numpy_array_equal(indexer, exp, check_dtype=False)
assert ordered.freq is None
ordered, indexer = idx.sort_values(return_indexer=True, ascending=False)
tm.assert_index_equal(ordered, expected[::-1])
exp = np.array([2, 1, 3, 4, 0])
tm.assert_numpy_array_equal(indexer, exp, check_dtype=False)
assert ordered.freq is None
def test_drop_duplicates_metadata(self, freq_sample):
# GH 10115
idx = pd.timedelta_range("1 day", periods=10, freq=freq_sample, name="idx")
result = idx.drop_duplicates()
tm.assert_index_equal(idx, result)
assert idx.freq == result.freq
idx_dup = idx.append(idx)
assert idx_dup.freq is None # freq is reset
result = idx_dup.drop_duplicates()
expected = idx._with_freq(None)
tm.assert_index_equal(expected, result)
assert result.freq is None
@pytest.mark.parametrize(
"keep, expected, index",
[
("first", np.concatenate(([False] * 10, [True] * 5)), np.arange(0, 10)),
("last", np.concatenate(([True] * 5, [False] * 10)), np.arange(5, 15)),
(
False,
np.concatenate(([True] * 5, [False] * 5, [True] * 5)),
np.arange(5, 10),
),
],
)
def test_drop_duplicates(self, freq_sample, keep, expected, index):
# to check Index/Series compat
idx = pd.timedelta_range("1 day", periods=10, freq=freq_sample, name="idx")
idx = idx.append(idx[:5])
tm.assert_numpy_array_equal(idx.duplicated(keep=keep), expected)
expected = idx[~expected]
result = idx.drop_duplicates(keep=keep)
tm.assert_index_equal(result, expected)
result = Series(idx).drop_duplicates(keep=keep)
tm.assert_series_equal(result, Series(expected, index=index))
def test_infer_freq(self, freq_sample):
# GH#11018
idx = pd.timedelta_range("1", freq=freq_sample, periods=10)
result = pd.TimedeltaIndex(idx.asi8, freq="infer")
tm.assert_index_equal(idx, result)
assert result.freq == freq_sample
def test_repeat(self):
index = pd.timedelta_range("1 days", periods=2, freq="D")
exp = pd.TimedeltaIndex(["1 days", "1 days", "2 days", "2 days"])
for res in [index.repeat(2), np.repeat(index, 2)]:
tm.assert_index_equal(res, exp)
assert res.freq is None
index = TimedeltaIndex(["1 days", "NaT", "3 days"])
exp = TimedeltaIndex(
[
"1 days",
"1 days",
"1 days",
"NaT",
"NaT",
"NaT",
"3 days",
"3 days",
"3 days",
]
)
for res in [index.repeat(3), np.repeat(index, 3)]:
tm.assert_index_equal(res, exp)
assert res.freq is None
def test_nat(self):
assert pd.TimedeltaIndex._na_value is pd.NaT
assert pd.TimedeltaIndex([])._na_value is pd.NaT
idx = pd.TimedeltaIndex(["1 days", "2 days"])
assert idx._can_hold_na
tm.assert_numpy_array_equal(idx._isnan, np.array([False, False]))
assert idx.hasnans is False
tm.assert_numpy_array_equal(idx._nan_idxs, np.array([], dtype=np.intp))
idx = pd.TimedeltaIndex(["1 days", "NaT"])
assert idx._can_hold_na
tm.assert_numpy_array_equal(idx._isnan, np.array([False, True]))
assert idx.hasnans is True
tm.assert_numpy_array_equal(idx._nan_idxs, np.array([1], dtype=np.intp))
def test_equals(self):
# GH 13107
idx = pd.TimedeltaIndex(["1 days", "2 days", "NaT"])
assert idx.equals(idx)
assert idx.equals(idx.copy())
assert idx.equals(idx.astype(object))
assert idx.astype(object).equals(idx)
assert idx.astype(object).equals(idx.astype(object))
assert not idx.equals(list(idx))
assert not idx.equals(pd.Series(idx))
idx2 = pd.TimedeltaIndex(["2 days", "1 days", "NaT"])
assert not idx.equals(idx2)
assert not idx.equals(idx2.copy())
assert not idx.equals(idx2.astype(object))
assert not idx.astype(object).equals(idx2)
assert not idx.astype(object).equals(idx2.astype(object))
assert not idx.equals(list(idx2))
assert not idx.equals(pd.Series(idx2))
# Check that we dont raise OverflowError on comparisons outside the
# implementation range
oob = pd.Index([timedelta(days=10 ** 6)] * 3, dtype=object)
assert not idx.equals(oob)
assert not idx2.equals(oob)
# FIXME: oob.apply(np.timedelta64) incorrectly overflows
oob2 = pd.Index([np.timedelta64(x) for x in oob], dtype=object)
assert not idx.equals(oob2)
assert not idx2.equals(oob2)
@pytest.mark.parametrize("values", [["0 days", "2 days", "4 days"], []])
@pytest.mark.parametrize("freq", ["2D", Day(2), "48H", Hour(48)])
def test_freq_setter(self, values, freq):
# GH 20678
idx = TimedeltaIndex(values)
# can set to an offset, converting from string if necessary
idx._data.freq = freq
assert idx.freq == freq
assert isinstance(idx.freq, DateOffset)
# can reset to None
idx._data.freq = None
assert idx.freq is None
def test_freq_setter_errors(self):
# GH 20678
idx = TimedeltaIndex(["0 days", "2 days", "4 days"])
# setting with an incompatible freq
msg = (
"Inferred frequency 2D from passed values does not conform to "
"passed frequency 5D"
)
with pytest.raises(ValueError, match=msg):
idx._data.freq = "5D"
# setting with a non-fixed frequency
msg = r"<2 \* BusinessDays> is a non-fixed frequency"
with pytest.raises(ValueError, match=msg):
idx._data.freq = "2B"
# setting with non-freq string
with pytest.raises(ValueError, match="Invalid frequency"):
idx._data.freq = "foo"
def test_freq_view_safe(self):
# Setting the freq for one TimedeltaIndex shouldn't alter the freq
# for another that views the same data
tdi = TimedeltaIndex(["0 days", "2 days", "4 days"], freq="2D")
tda = tdi._data
tdi2 = TimedeltaIndex(tda)._with_freq(None)
assert tdi2.freq is None
# Original was not altered
assert tdi.freq == "2D"
assert tda.freq == "2D"