Inzynierka/Lib/site-packages/pandas/tests/indexes/datetimes/test_formats.py
2023-06-02 12:51:02 +02:00

268 lines
9.1 KiB
Python

from datetime import datetime
import dateutil.tz
import numpy as np
import pytest
import pytz
import pandas as pd
from pandas import (
DatetimeIndex,
Series,
)
import pandas._testing as tm
def test_format_native_types():
index = pd.date_range(freq="1D", periods=3, start="2017-01-01")
# First, with no arguments.
expected = np.array(["2017-01-01", "2017-01-02", "2017-01-03"], dtype=object)
result = index._format_native_types()
tm.assert_numpy_array_equal(result, expected)
# No NaN values, so na_rep has no effect
result = index._format_native_types(na_rep="pandas")
tm.assert_numpy_array_equal(result, expected)
# Make sure date formatting works
expected = np.array(["01-2017-01", "01-2017-02", "01-2017-03"], dtype=object)
result = index._format_native_types(date_format="%m-%Y-%d")
tm.assert_numpy_array_equal(result, expected)
# NULL object handling should work
index = DatetimeIndex(["2017-01-01", pd.NaT, "2017-01-03"])
expected = np.array(["2017-01-01", "NaT", "2017-01-03"], dtype=object)
result = index._format_native_types()
tm.assert_numpy_array_equal(result, expected)
expected = np.array(["2017-01-01", "pandas", "2017-01-03"], dtype=object)
result = index._format_native_types(na_rep="pandas")
tm.assert_numpy_array_equal(result, expected)
result = index._format_native_types(date_format="%Y-%m-%d %H:%M:%S.%f")
expected = np.array(
["2017-01-01 00:00:00.000000", "NaT", "2017-01-03 00:00:00.000000"],
dtype=object,
)
tm.assert_numpy_array_equal(result, expected)
# invalid format
result = index._format_native_types(date_format="foo")
expected = np.array(["foo", "NaT", "foo"], dtype=object)
tm.assert_numpy_array_equal(result, expected)
class TestDatetimeIndexRendering:
def test_dti_repr_short(self):
dr = pd.date_range(start="1/1/2012", periods=1)
repr(dr)
dr = pd.date_range(start="1/1/2012", periods=2)
repr(dr)
dr = pd.date_range(start="1/1/2012", periods=3)
repr(dr)
@pytest.mark.parametrize("method", ["__repr__", "__str__"])
def test_dti_representation(self, method):
idxs = []
idxs.append(DatetimeIndex([], freq="D"))
idxs.append(DatetimeIndex(["2011-01-01"], freq="D"))
idxs.append(DatetimeIndex(["2011-01-01", "2011-01-02"], freq="D"))
idxs.append(DatetimeIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D"))
idxs.append(
DatetimeIndex(
["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"],
freq="H",
tz="Asia/Tokyo",
)
)
idxs.append(
DatetimeIndex(
["2011-01-01 09:00", "2011-01-01 10:00", pd.NaT], tz="US/Eastern"
)
)
idxs.append(
DatetimeIndex(["2011-01-01 09:00", "2011-01-01 10:00", pd.NaT], tz="UTC")
)
exp = []
exp.append("DatetimeIndex([], dtype='datetime64[ns]', freq='D')")
exp.append("DatetimeIndex(['2011-01-01'], dtype='datetime64[ns]', freq='D')")
exp.append(
"DatetimeIndex(['2011-01-01', '2011-01-02'], "
"dtype='datetime64[ns]', freq='D')"
)
exp.append(
"DatetimeIndex(['2011-01-01', '2011-01-02', '2011-01-03'], "
"dtype='datetime64[ns]', freq='D')"
)
exp.append(
"DatetimeIndex(['2011-01-01 09:00:00+09:00', "
"'2011-01-01 10:00:00+09:00', '2011-01-01 11:00:00+09:00']"
", dtype='datetime64[ns, Asia/Tokyo]', freq='H')"
)
exp.append(
"DatetimeIndex(['2011-01-01 09:00:00-05:00', "
"'2011-01-01 10:00:00-05:00', 'NaT'], "
"dtype='datetime64[ns, US/Eastern]', freq=None)"
)
exp.append(
"DatetimeIndex(['2011-01-01 09:00:00+00:00', "
"'2011-01-01 10:00:00+00:00', 'NaT'], "
"dtype='datetime64[ns, UTC]', freq=None)"
""
)
with pd.option_context("display.width", 300):
for indx, expected in zip(idxs, exp):
result = getattr(indx, method)()
assert result == expected
def test_dti_representation_to_series(self):
idx1 = DatetimeIndex([], freq="D")
idx2 = DatetimeIndex(["2011-01-01"], freq="D")
idx3 = DatetimeIndex(["2011-01-01", "2011-01-02"], freq="D")
idx4 = DatetimeIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D")
idx5 = DatetimeIndex(
["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"],
freq="H",
tz="Asia/Tokyo",
)
idx6 = DatetimeIndex(
["2011-01-01 09:00", "2011-01-01 10:00", pd.NaT], tz="US/Eastern"
)
idx7 = DatetimeIndex(["2011-01-01 09:00", "2011-01-02 10:15"])
exp1 = """Series([], dtype: datetime64[ns])"""
exp2 = "0 2011-01-01\ndtype: datetime64[ns]"
exp3 = "0 2011-01-01\n1 2011-01-02\ndtype: datetime64[ns]"
exp4 = (
"0 2011-01-01\n"
"1 2011-01-02\n"
"2 2011-01-03\n"
"dtype: datetime64[ns]"
)
exp5 = (
"0 2011-01-01 09:00:00+09:00\n"
"1 2011-01-01 10:00:00+09:00\n"
"2 2011-01-01 11:00:00+09:00\n"
"dtype: datetime64[ns, Asia/Tokyo]"
)
exp6 = (
"0 2011-01-01 09:00:00-05:00\n"
"1 2011-01-01 10:00:00-05:00\n"
"2 NaT\n"
"dtype: datetime64[ns, US/Eastern]"
)
exp7 = (
"0 2011-01-01 09:00:00\n"
"1 2011-01-02 10:15:00\n"
"dtype: datetime64[ns]"
)
with pd.option_context("display.width", 300):
for idx, expected in zip(
[idx1, idx2, idx3, idx4, idx5, idx6, idx7],
[exp1, exp2, exp3, exp4, exp5, exp6, exp7],
):
result = repr(Series(idx))
assert result == expected
def test_dti_summary(self):
# GH#9116
idx1 = DatetimeIndex([], freq="D")
idx2 = DatetimeIndex(["2011-01-01"], freq="D")
idx3 = DatetimeIndex(["2011-01-01", "2011-01-02"], freq="D")
idx4 = DatetimeIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D")
idx5 = DatetimeIndex(
["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"],
freq="H",
tz="Asia/Tokyo",
)
idx6 = DatetimeIndex(
["2011-01-01 09:00", "2011-01-01 10:00", pd.NaT], tz="US/Eastern"
)
exp1 = "DatetimeIndex: 0 entries\nFreq: D"
exp2 = "DatetimeIndex: 1 entries, 2011-01-01 to 2011-01-01\nFreq: D"
exp3 = "DatetimeIndex: 2 entries, 2011-01-01 to 2011-01-02\nFreq: D"
exp4 = "DatetimeIndex: 3 entries, 2011-01-01 to 2011-01-03\nFreq: D"
exp5 = (
"DatetimeIndex: 3 entries, 2011-01-01 09:00:00+09:00 "
"to 2011-01-01 11:00:00+09:00\n"
"Freq: H"
)
exp6 = """DatetimeIndex: 3 entries, 2011-01-01 09:00:00-05:00 to NaT"""
for idx, expected in zip(
[idx1, idx2, idx3, idx4, idx5, idx6], [exp1, exp2, exp3, exp4, exp5, exp6]
):
result = idx._summary()
assert result == expected
def test_dti_business_repr(self):
# only really care that it works
repr(pd.bdate_range(datetime(2009, 1, 1), datetime(2010, 1, 1)))
def test_dti_business_summary(self):
rng = pd.bdate_range(datetime(2009, 1, 1), datetime(2010, 1, 1))
rng._summary()
rng[2:2]._summary()
def test_dti_business_summary_pytz(self):
pd.bdate_range("1/1/2005", "1/1/2009", tz=pytz.utc)._summary()
def test_dti_business_summary_dateutil(self):
pd.bdate_range("1/1/2005", "1/1/2009", tz=dateutil.tz.tzutc())._summary()
def test_dti_custom_business_repr(self):
# only really care that it works
repr(pd.bdate_range(datetime(2009, 1, 1), datetime(2010, 1, 1), freq="C"))
def test_dti_custom_business_summary(self):
rng = pd.bdate_range(datetime(2009, 1, 1), datetime(2010, 1, 1), freq="C")
rng._summary()
rng[2:2]._summary()
def test_dti_custom_business_summary_pytz(self):
pd.bdate_range("1/1/2005", "1/1/2009", freq="C", tz=pytz.utc)._summary()
def test_dti_custom_business_summary_dateutil(self):
pd.bdate_range(
"1/1/2005", "1/1/2009", freq="C", tz=dateutil.tz.tzutc()
)._summary()
class TestFormat:
def test_format_with_name_time_info(self):
# bug I fixed 12/20/2011
dates = pd.date_range("2011-01-01 04:00:00", periods=10, name="something")
formatted = dates.format(name=True)
assert formatted[0] == "something"
def test_format_datetime_with_time(self):
dti = DatetimeIndex([datetime(2012, 2, 7), datetime(2012, 2, 7, 23)])
result = dti.format()
expected = ["2012-02-07 00:00:00", "2012-02-07 23:00:00"]
assert len(result) == 2
assert result == expected