mirror of
https://github.com/PiBrewing/craftbeerpi4.git
synced 2024-11-23 07:28:13 +01:00
509 lines
15 KiB
Python
509 lines
15 KiB
Python
|
from datetime import datetime, timedelta
|
||
|
|
|
||
|
|
import numpy as np
|
||
|
|
import pytest
|
||
|
|
|
||
|
|
import pandas as pd
|
||
|
|
from pandas import (
|
||
|
|
Categorical,
|
||
|
|
DataFrame,
|
||
|
|
Index,
|
||
|
|
MultiIndex,
|
||
|
|
Series,
|
||
|
|
date_range,
|
||
|
|
option_context,
|
||
|
|
period_range,
|
||
|
|
timedelta_range,
|
||
|
|
)
|
||
|
|
import pandas._testing as tm
|
||
|
|
|
||
|
|
|
||
|
|
class TestSeriesRepr:
|
||
|
|
def test_multilevel_name_print(self):
|
||
|
|
index = MultiIndex(
|
||
|
|
levels=[["foo", "bar", "baz", "qux"], ["one", "two", "three"]],
|
||
|
|
codes=[[0, 0, 0, 1, 1, 2, 2, 3, 3, 3], [0, 1, 2, 0, 1, 1, 2, 0, 1, 2]],
|
||
|
|
names=["first", "second"],
|
||
|
|
)
|
||
|
|
s = Series(range(len(index)), index=index, name="sth")
|
||
|
|
expected = [
|
||
|
|
"first second",
|
||
|
|
"foo one 0",
|
||
|
|
" two 1",
|
||
|
|
" three 2",
|
||
|
|
"bar one 3",
|
||
|
|
" two 4",
|
||
|
|
"baz two 5",
|
||
|
|
" three 6",
|
||
|
|
"qux one 7",
|
||
|
|
" two 8",
|
||
|
|
" three 9",
|
||
|
|
"Name: sth, dtype: int64",
|
||
|
|
]
|
||
|
|
expected = "\n".join(expected)
|
||
|
|
assert repr(s) == expected
|
||
|
|
|
||
|
|
def test_name_printing(self):
|
||
|
|
# Test small Series.
|
||
|
|
s = Series([0, 1, 2])
|
||
|
|
|
||
|
|
s.name = "test"
|
||
|
|
assert "Name: test" in repr(s)
|
||
|
|
|
||
|
|
s.name = None
|
||
|
|
assert "Name:" not in repr(s)
|
||
|
|
|
||
|
|
# Test big Series (diff code path).
|
||
|
|
s = Series(range(1000))
|
||
|
|
|
||
|
|
s.name = "test"
|
||
|
|
assert "Name: test" in repr(s)
|
||
|
|
|
||
|
|
s.name = None
|
||
|
|
assert "Name:" not in repr(s)
|
||
|
|
|
||
|
|
s = Series(index=date_range("20010101", "20020101"), name="test", dtype=object)
|
||
|
|
assert "Name: test" in repr(s)
|
||
|
|
|
||
|
|
def test_repr(self, datetime_series, string_series, object_series):
|
||
|
|
str(datetime_series)
|
||
|
|
str(string_series)
|
||
|
|
str(string_series.astype(int))
|
||
|
|
str(object_series)
|
||
|
|
|
||
|
|
str(Series(tm.randn(1000), index=np.arange(1000)))
|
||
|
|
str(Series(tm.randn(1000), index=np.arange(1000, 0, step=-1)))
|
||
|
|
|
||
|
|
# empty
|
||
|
|
str(Series(dtype=object))
|
||
|
|
|
||
|
|
# with NaNs
|
||
|
|
string_series[5:7] = np.NaN
|
||
|
|
str(string_series)
|
||
|
|
|
||
|
|
# with Nones
|
||
|
|
ots = datetime_series.astype("O")
|
||
|
|
ots[::2] = None
|
||
|
|
repr(ots)
|
||
|
|
|
||
|
|
# various names
|
||
|
|
for name in [
|
||
|
|
"",
|
||
|
|
1,
|
||
|
|
1.2,
|
||
|
|
"foo",
|
||
|
|
"\u03B1\u03B2\u03B3",
|
||
|
|
"loooooooooooooooooooooooooooooooooooooooooooooooooooong",
|
||
|
|
("foo", "bar", "baz"),
|
||
|
|
(1, 2),
|
||
|
|
("foo", 1, 2.3),
|
||
|
|
("\u03B1", "\u03B2", "\u03B3"),
|
||
|
|
("\u03B1", "bar"),
|
||
|
|
]:
|
||
|
|
string_series.name = name
|
||
|
|
repr(string_series)
|
||
|
|
|
||
|
|
biggie = Series(
|
||
|
|
tm.randn(1000), index=np.arange(1000), name=("foo", "bar", "baz")
|
||
|
|
)
|
||
|
|
repr(biggie)
|
||
|
|
|
||
|
|
# 0 as name
|
||
|
|
ser = Series(np.random.randn(100), name=0)
|
||
|
|
rep_str = repr(ser)
|
||
|
|
assert "Name: 0" in rep_str
|
||
|
|
|
||
|
|
# tidy repr
|
||
|
|
ser = Series(np.random.randn(1001), name=0)
|
||
|
|
rep_str = repr(ser)
|
||
|
|
assert "Name: 0" in rep_str
|
||
|
|
|
||
|
|
ser = Series(["a\n\r\tb"], name="a\n\r\td", index=["a\n\r\tf"])
|
||
|
|
assert "\t" not in repr(ser)
|
||
|
|
assert "\r" not in repr(ser)
|
||
|
|
assert "a\n" not in repr(ser)
|
||
|
|
|
||
|
|
# with empty series (#4651)
|
||
|
|
s = Series([], dtype=np.int64, name="foo")
|
||
|
|
assert repr(s) == "Series([], Name: foo, dtype: int64)"
|
||
|
|
|
||
|
|
s = Series([], dtype=np.int64, name=None)
|
||
|
|
assert repr(s) == "Series([], dtype: int64)"
|
||
|
|
|
||
|
|
def test_tidy_repr(self):
|
||
|
|
a = Series(["\u05d0"] * 1000)
|
||
|
|
a.name = "title1"
|
||
|
|
repr(a) # should not raise exception
|
||
|
|
|
||
|
|
def test_repr_bool_fails(self, capsys):
|
||
|
|
s = Series([DataFrame(np.random.randn(2, 2)) for i in range(5)])
|
||
|
|
|
||
|
|
# It works (with no Cython exception barf)!
|
||
|
|
repr(s)
|
||
|
|
|
||
|
|
captured = capsys.readouterr()
|
||
|
|
assert captured.err == ""
|
||
|
|
|
||
|
|
def test_repr_name_iterable_indexable(self):
|
||
|
|
s = Series([1, 2, 3], name=np.int64(3))
|
||
|
|
|
||
|
|
# it works!
|
||
|
|
repr(s)
|
||
|
|
|
||
|
|
s.name = ("\u05d0",) * 2
|
||
|
|
repr(s)
|
||
|
|
|
||
|
|
def test_repr_should_return_str(self):
|
||
|
|
# https://docs.python.org/3/reference/datamodel.html#object.__repr__
|
||
|
|
# ...The return value must be a string object.
|
||
|
|
|
||
|
|
# (str on py2.x, str (unicode) on py3)
|
||
|
|
|
||
|
|
data = [8, 5, 3, 5]
|
||
|
|
index1 = ["\u03c3", "\u03c4", "\u03c5", "\u03c6"]
|
||
|
|
df = Series(data, index=index1)
|
||
|
|
assert type(df.__repr__() == str) # both py2 / 3
|
||
|
|
|
||
|
|
def test_repr_max_rows(self):
|
||
|
|
# GH 6863
|
||
|
|
with pd.option_context("max_rows", None):
|
||
|
|
str(Series(range(1001))) # should not raise exception
|
||
|
|
|
||
|
|
def test_unicode_string_with_unicode(self):
|
||
|
|
df = Series(["\u05d0"], name="\u05d1")
|
||
|
|
str(df)
|
||
|
|
|
||
|
|
def test_str_to_bytes_raises(self):
|
||
|
|
# GH 26447
|
||
|
|
df = Series(["abc"], name="abc")
|
||
|
|
msg = "^'str' object cannot be interpreted as an integer$"
|
||
|
|
with pytest.raises(TypeError, match=msg):
|
||
|
|
bytes(df)
|
||
|
|
|
||
|
|
def test_timeseries_repr_object_dtype(self):
|
||
|
|
index = Index(
|
||
|
|
[datetime(2000, 1, 1) + timedelta(i) for i in range(1000)], dtype=object
|
||
|
|
)
|
||
|
|
ts = Series(np.random.randn(len(index)), index)
|
||
|
|
repr(ts)
|
||
|
|
|
||
|
|
ts = tm.makeTimeSeries(1000)
|
||
|
|
assert repr(ts).splitlines()[-1].startswith("Freq:")
|
||
|
|
|
||
|
|
ts2 = ts.iloc[np.random.randint(0, len(ts) - 1, 400)]
|
||
|
|
repr(ts2).splitlines()[-1]
|
||
|
|
|
||
|
|
def test_latex_repr(self):
|
||
|
|
result = r"""\begin{tabular}{ll}
|
||
|
|
\toprule
|
||
|
|
{} & 0 \\
|
||
|
|
\midrule
|
||
|
|
0 & $\alpha$ \\
|
||
|
|
1 & b \\
|
||
|
|
2 & c \\
|
||
|
|
\bottomrule
|
||
|
|
\end{tabular}
|
||
|
|
"""
|
||
|
|
with option_context("display.latex.escape", False, "display.latex.repr", True):
|
||
|
|
s = Series([r"$\alpha$", "b", "c"])
|
||
|
|
assert result == s._repr_latex_()
|
||
|
|
|
||
|
|
assert s._repr_latex_() is None
|
||
|
|
|
||
|
|
def test_index_repr_in_frame_with_nan(self):
|
||
|
|
# see gh-25061
|
||
|
|
i = Index([1, np.nan])
|
||
|
|
s = Series([1, 2], index=i)
|
||
|
|
exp = """1.0 1\nNaN 2\ndtype: int64"""
|
||
|
|
|
||
|
|
assert repr(s) == exp
|
||
|
|
|
||
|
|
def test_format_pre_1900_dates(self):
|
||
|
|
rng = date_range("1/1/1850", "1/1/1950", freq="A-DEC")
|
||
|
|
rng.format()
|
||
|
|
ts = Series(1, index=rng)
|
||
|
|
repr(ts)
|
||
|
|
|
||
|
|
def test_series_repr_nat(self):
|
||
|
|
series = Series([0, 1000, 2000, pd.NaT.value], dtype="M8[ns]")
|
||
|
|
|
||
|
|
result = repr(series)
|
||
|
|
expected = (
|
||
|
|
"0 1970-01-01 00:00:00.000000\n"
|
||
|
|
"1 1970-01-01 00:00:00.000001\n"
|
||
|
|
"2 1970-01-01 00:00:00.000002\n"
|
||
|
|
"3 NaT\n"
|
||
|
|
"dtype: datetime64[ns]"
|
||
|
|
)
|
||
|
|
assert result == expected
|
||
|
|
|
||
|
|
|
||
|
|
class TestCategoricalRepr:
|
||
|
|
def test_categorical_repr_unicode(self):
|
||
|
|
# see gh-21002
|
||
|
|
|
||
|
|
class County:
|
||
|
|
name = "San Sebastián"
|
||
|
|
state = "PR"
|
||
|
|
|
||
|
|
def __repr__(self) -> str:
|
||
|
|
return self.name + ", " + self.state
|
||
|
|
|
||
|
|
cat = pd.Categorical([County() for _ in range(61)])
|
||
|
|
idx = pd.Index(cat)
|
||
|
|
ser = idx.to_series()
|
||
|
|
|
||
|
|
repr(ser)
|
||
|
|
str(ser)
|
||
|
|
|
||
|
|
def test_categorical_repr(self):
|
||
|
|
a = Series(Categorical([1, 2, 3, 4]))
|
||
|
|
exp = (
|
||
|
|
"0 1\n1 2\n2 3\n3 4\n"
|
||
|
|
+ "dtype: category\nCategories (4, int64): [1, 2, 3, 4]"
|
||
|
|
)
|
||
|
|
|
||
|
|
assert exp == a.__str__()
|
||
|
|
|
||
|
|
a = Series(Categorical(["a", "b"] * 25))
|
||
|
|
exp = (
|
||
|
|
"0 a\n1 b\n"
|
||
|
|
+ " ..\n"
|
||
|
|
+ "48 a\n49 b\n"
|
||
|
|
+ "Length: 50, dtype: category\nCategories (2, object): ['a', 'b']"
|
||
|
|
)
|
||
|
|
with option_context("display.max_rows", 5):
|
||
|
|
assert exp == repr(a)
|
||
|
|
|
||
|
|
levs = list("abcdefghijklmnopqrstuvwxyz")
|
||
|
|
a = Series(Categorical(["a", "b"], categories=levs, ordered=True))
|
||
|
|
exp = (
|
||
|
|
"0 a\n1 b\n" + "dtype: category\n"
|
||
|
|
"Categories (26, object): ['a' < 'b' < 'c' < 'd' ... 'w' < 'x' < 'y' < 'z']"
|
||
|
|
)
|
||
|
|
assert exp == a.__str__()
|
||
|
|
|
||
|
|
def test_categorical_series_repr(self):
|
||
|
|
s = Series(Categorical([1, 2, 3]))
|
||
|
|
exp = """0 1
|
||
|
|
1 2
|
||
|
|
2 3
|
||
|
|
dtype: category
|
||
|
|
Categories (3, int64): [1, 2, 3]"""
|
||
|
|
|
||
|
|
assert repr(s) == exp
|
||
|
|
|
||
|
|
s = Series(Categorical(np.arange(10)))
|
||
|
|
exp = """0 0
|
||
|
|
1 1
|
||
|
|
2 2
|
||
|
|
3 3
|
||
|
|
4 4
|
||
|
|
5 5
|
||
|
|
6 6
|
||
|
|
7 7
|
||
|
|
8 8
|
||
|
|
9 9
|
||
|
|
dtype: category
|
||
|
|
Categories (10, int64): [0, 1, 2, 3, ..., 6, 7, 8, 9]"""
|
||
|
|
|
||
|
|
assert repr(s) == exp
|
||
|
|
|
||
|
|
def test_categorical_series_repr_ordered(self):
|
||
|
|
s = Series(Categorical([1, 2, 3], ordered=True))
|
||
|
|
exp = """0 1
|
||
|
|
1 2
|
||
|
|
2 3
|
||
|
|
dtype: category
|
||
|
|
Categories (3, int64): [1 < 2 < 3]"""
|
||
|
|
|
||
|
|
assert repr(s) == exp
|
||
|
|
|
||
|
|
s = Series(Categorical(np.arange(10), ordered=True))
|
||
|
|
exp = """0 0
|
||
|
|
1 1
|
||
|
|
2 2
|
||
|
|
3 3
|
||
|
|
4 4
|
||
|
|
5 5
|
||
|
|
6 6
|
||
|
|
7 7
|
||
|
|
8 8
|
||
|
|
9 9
|
||
|
|
dtype: category
|
||
|
|
Categories (10, int64): [0 < 1 < 2 < 3 ... 6 < 7 < 8 < 9]"""
|
||
|
|
|
||
|
|
assert repr(s) == exp
|
||
|
|
|
||
|
|
def test_categorical_series_repr_datetime(self):
|
||
|
|
idx = date_range("2011-01-01 09:00", freq="H", periods=5)
|
||
|
|
s = Series(Categorical(idx))
|
||
|
|
exp = """0 2011-01-01 09:00:00
|
||
|
|
1 2011-01-01 10:00:00
|
||
|
|
2 2011-01-01 11:00:00
|
||
|
|
3 2011-01-01 12:00:00
|
||
|
|
4 2011-01-01 13:00:00
|
||
|
|
dtype: category
|
||
|
|
Categories (5, datetime64[ns]): [2011-01-01 09:00:00, 2011-01-01 10:00:00, 2011-01-01 11:00:00,
|
||
|
|
2011-01-01 12:00:00, 2011-01-01 13:00:00]""" # noqa
|
||
|
|
|
||
|
|
assert repr(s) == exp
|
||
|
|
|
||
|
|
idx = date_range("2011-01-01 09:00", freq="H", periods=5, tz="US/Eastern")
|
||
|
|
s = Series(Categorical(idx))
|
||
|
|
exp = """0 2011-01-01 09:00:00-05:00
|
||
|
|
1 2011-01-01 10:00:00-05:00
|
||
|
|
2 2011-01-01 11:00:00-05:00
|
||
|
|
3 2011-01-01 12:00:00-05:00
|
||
|
|
4 2011-01-01 13:00:00-05:00
|
||
|
|
dtype: category
|
||
|
|
Categories (5, datetime64[ns, US/Eastern]): [2011-01-01 09:00:00-05:00, 2011-01-01 10:00:00-05:00,
|
||
|
|
2011-01-01 11:00:00-05:00, 2011-01-01 12:00:00-05:00,
|
||
|
|
2011-01-01 13:00:00-05:00]""" # noqa
|
||
|
|
|
||
|
|
assert repr(s) == exp
|
||
|
|
|
||
|
|
def test_categorical_series_repr_datetime_ordered(self):
|
||
|
|
idx = date_range("2011-01-01 09:00", freq="H", periods=5)
|
||
|
|
s = Series(Categorical(idx, ordered=True))
|
||
|
|
exp = """0 2011-01-01 09:00:00
|
||
|
|
1 2011-01-01 10:00:00
|
||
|
|
2 2011-01-01 11:00:00
|
||
|
|
3 2011-01-01 12:00:00
|
||
|
|
4 2011-01-01 13:00:00
|
||
|
|
dtype: category
|
||
|
|
Categories (5, datetime64[ns]): [2011-01-01 09:00:00 < 2011-01-01 10:00:00 < 2011-01-01 11:00:00 <
|
||
|
|
2011-01-01 12:00:00 < 2011-01-01 13:00:00]""" # noqa
|
||
|
|
|
||
|
|
assert repr(s) == exp
|
||
|
|
|
||
|
|
idx = date_range("2011-01-01 09:00", freq="H", periods=5, tz="US/Eastern")
|
||
|
|
s = Series(Categorical(idx, ordered=True))
|
||
|
|
exp = """0 2011-01-01 09:00:00-05:00
|
||
|
|
1 2011-01-01 10:00:00-05:00
|
||
|
|
2 2011-01-01 11:00:00-05:00
|
||
|
|
3 2011-01-01 12:00:00-05:00
|
||
|
|
4 2011-01-01 13:00:00-05:00
|
||
|
|
dtype: category
|
||
|
|
Categories (5, datetime64[ns, US/Eastern]): [2011-01-01 09:00:00-05:00 < 2011-01-01 10:00:00-05:00 <
|
||
|
|
2011-01-01 11:00:00-05:00 < 2011-01-01 12:00:00-05:00 <
|
||
|
|
2011-01-01 13:00:00-05:00]""" # noqa
|
||
|
|
|
||
|
|
assert repr(s) == exp
|
||
|
|
|
||
|
|
def test_categorical_series_repr_period(self):
|
||
|
|
idx = period_range("2011-01-01 09:00", freq="H", periods=5)
|
||
|
|
s = Series(Categorical(idx))
|
||
|
|
exp = """0 2011-01-01 09:00
|
||
|
|
1 2011-01-01 10:00
|
||
|
|
2 2011-01-01 11:00
|
||
|
|
3 2011-01-01 12:00
|
||
|
|
4 2011-01-01 13:00
|
||
|
|
dtype: category
|
||
|
|
Categories (5, period[H]): [2011-01-01 09:00, 2011-01-01 10:00, 2011-01-01 11:00, 2011-01-01 12:00,
|
||
|
|
2011-01-01 13:00]""" # noqa
|
||
|
|
|
||
|
|
assert repr(s) == exp
|
||
|
|
|
||
|
|
idx = period_range("2011-01", freq="M", periods=5)
|
||
|
|
s = Series(Categorical(idx))
|
||
|
|
exp = """0 2011-01
|
||
|
|
1 2011-02
|
||
|
|
2 2011-03
|
||
|
|
3 2011-04
|
||
|
|
4 2011-05
|
||
|
|
dtype: category
|
||
|
|
Categories (5, period[M]): [2011-01, 2011-02, 2011-03, 2011-04, 2011-05]"""
|
||
|
|
|
||
|
|
assert repr(s) == exp
|
||
|
|
|
||
|
|
def test_categorical_series_repr_period_ordered(self):
|
||
|
|
idx = period_range("2011-01-01 09:00", freq="H", periods=5)
|
||
|
|
s = Series(Categorical(idx, ordered=True))
|
||
|
|
exp = """0 2011-01-01 09:00
|
||
|
|
1 2011-01-01 10:00
|
||
|
|
2 2011-01-01 11:00
|
||
|
|
3 2011-01-01 12:00
|
||
|
|
4 2011-01-01 13:00
|
||
|
|
dtype: category
|
||
|
|
Categories (5, period[H]): [2011-01-01 09:00 < 2011-01-01 10:00 < 2011-01-01 11:00 < 2011-01-01 12:00 <
|
||
|
|
2011-01-01 13:00]""" # noqa
|
||
|
|
|
||
|
|
assert repr(s) == exp
|
||
|
|
|
||
|
|
idx = period_range("2011-01", freq="M", periods=5)
|
||
|
|
s = Series(Categorical(idx, ordered=True))
|
||
|
|
exp = """0 2011-01
|
||
|
|
1 2011-02
|
||
|
|
2 2011-03
|
||
|
|
3 2011-04
|
||
|
|
4 2011-05
|
||
|
|
dtype: category
|
||
|
|
Categories (5, period[M]): [2011-01 < 2011-02 < 2011-03 < 2011-04 < 2011-05]"""
|
||
|
|
|
||
|
|
assert repr(s) == exp
|
||
|
|
|
||
|
|
def test_categorical_series_repr_timedelta(self):
|
||
|
|
idx = timedelta_range("1 days", periods=5)
|
||
|
|
s = Series(Categorical(idx))
|
||
|
|
exp = """0 1 days
|
||
|
|
1 2 days
|
||
|
|
2 3 days
|
||
|
|
3 4 days
|
||
|
|
4 5 days
|
||
|
|
dtype: category
|
||
|
|
Categories (5, timedelta64[ns]): [1 days, 2 days, 3 days, 4 days, 5 days]"""
|
||
|
|
|
||
|
|
assert repr(s) == exp
|
||
|
|
|
||
|
|
idx = timedelta_range("1 hours", periods=10)
|
||
|
|
s = Series(Categorical(idx))
|
||
|
|
exp = """0 0 days 01:00:00
|
||
|
|
1 1 days 01:00:00
|
||
|
|
2 2 days 01:00:00
|
||
|
|
3 3 days 01:00:00
|
||
|
|
4 4 days 01:00:00
|
||
|
|
5 5 days 01:00:00
|
||
|
|
6 6 days 01:00:00
|
||
|
|
7 7 days 01:00:00
|
||
|
|
8 8 days 01:00:00
|
||
|
|
9 9 days 01:00:00
|
||
|
|
dtype: category
|
||
|
|
Categories (10, timedelta64[ns]): [0 days 01:00:00, 1 days 01:00:00, 2 days 01:00:00,
|
||
|
|
3 days 01:00:00, ..., 6 days 01:00:00, 7 days 01:00:00,
|
||
|
|
8 days 01:00:00, 9 days 01:00:00]""" # noqa
|
||
|
|
|
||
|
|
assert repr(s) == exp
|
||
|
|
|
||
|
|
def test_categorical_series_repr_timedelta_ordered(self):
|
||
|
|
idx = timedelta_range("1 days", periods=5)
|
||
|
|
s = Series(Categorical(idx, ordered=True))
|
||
|
|
exp = """0 1 days
|
||
|
|
1 2 days
|
||
|
|
2 3 days
|
||
|
|
3 4 days
|
||
|
|
4 5 days
|
||
|
|
dtype: category
|
||
|
|
Categories (5, timedelta64[ns]): [1 days < 2 days < 3 days < 4 days < 5 days]""" # noqa
|
||
|
|
|
||
|
|
assert repr(s) == exp
|
||
|
|
|
||
|
|
idx = timedelta_range("1 hours", periods=10)
|
||
|
|
s = Series(Categorical(idx, ordered=True))
|
||
|
|
exp = """0 0 days 01:00:00
|
||
|
|
1 1 days 01:00:00
|
||
|
|
2 2 days 01:00:00
|
||
|
|
3 3 days 01:00:00
|
||
|
|
4 4 days 01:00:00
|
||
|
|
5 5 days 01:00:00
|
||
|
|
6 6 days 01:00:00
|
||
|
|
7 7 days 01:00:00
|
||
|
|
8 8 days 01:00:00
|
||
|
|
9 9 days 01:00:00
|
||
|
|
dtype: category
|
||
|
|
Categories (10, timedelta64[ns]): [0 days 01:00:00 < 1 days 01:00:00 < 2 days 01:00:00 <
|
||
|
|
3 days 01:00:00 ... 6 days 01:00:00 < 7 days 01:00:00 <
|
||
|
|
8 days 01:00:00 < 9 days 01:00:00]""" # noqa
|
||
|
|
|
||
|
|
assert repr(s) == exp
|