Updated script that can be controled by Nodejs web app
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from datetime import datetime
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import dateutil.tz
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import numpy as np
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import pytest
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import pytz
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import pandas as pd
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from pandas import (
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DatetimeIndex,
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NaT,
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Series,
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)
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import pandas._testing as tm
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@pytest.fixture(params=["s", "ms", "us", "ns"])
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def unit(request):
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return request.param
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def test_get_values_for_csv():
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index = pd.date_range(freq="1D", periods=3, start="2017-01-01")
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# First, with no arguments.
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expected = np.array(["2017-01-01", "2017-01-02", "2017-01-03"], dtype=object)
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result = index._get_values_for_csv()
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tm.assert_numpy_array_equal(result, expected)
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# No NaN values, so na_rep has no effect
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result = index._get_values_for_csv(na_rep="pandas")
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tm.assert_numpy_array_equal(result, expected)
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# Make sure date formatting works
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expected = np.array(["01-2017-01", "01-2017-02", "01-2017-03"], dtype=object)
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result = index._get_values_for_csv(date_format="%m-%Y-%d")
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tm.assert_numpy_array_equal(result, expected)
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# NULL object handling should work
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index = DatetimeIndex(["2017-01-01", NaT, "2017-01-03"])
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expected = np.array(["2017-01-01", "NaT", "2017-01-03"], dtype=object)
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result = index._get_values_for_csv(na_rep="NaT")
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tm.assert_numpy_array_equal(result, expected)
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expected = np.array(["2017-01-01", "pandas", "2017-01-03"], dtype=object)
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result = index._get_values_for_csv(na_rep="pandas")
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tm.assert_numpy_array_equal(result, expected)
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result = index._get_values_for_csv(na_rep="NaT", date_format="%Y-%m-%d %H:%M:%S.%f")
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expected = np.array(
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["2017-01-01 00:00:00.000000", "NaT", "2017-01-03 00:00:00.000000"],
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dtype=object,
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)
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tm.assert_numpy_array_equal(result, expected)
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# invalid format
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result = index._get_values_for_csv(na_rep="NaT", date_format="foo")
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expected = np.array(["foo", "NaT", "foo"], dtype=object)
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tm.assert_numpy_array_equal(result, expected)
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class TestDatetimeIndexRendering:
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@pytest.mark.parametrize("tzstr", ["US/Eastern", "dateutil/US/Eastern"])
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def test_dti_with_timezone_repr(self, tzstr):
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rng = pd.date_range("4/13/2010", "5/6/2010")
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rng_eastern = rng.tz_localize(tzstr)
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rng_repr = repr(rng_eastern)
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assert "2010-04-13 00:00:00" in rng_repr
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def test_dti_repr_dates(self):
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text = str(pd.to_datetime([datetime(2013, 1, 1), datetime(2014, 1, 1)]))
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assert "['2013-01-01'," in text
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assert ", '2014-01-01']" in text
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def test_dti_repr_mixed(self):
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text = str(
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pd.to_datetime(
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[datetime(2013, 1, 1), datetime(2014, 1, 1, 12), datetime(2014, 1, 1)]
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)
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)
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assert "'2013-01-01 00:00:00'," in text
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assert "'2014-01-01 00:00:00']" in text
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def test_dti_repr_short(self):
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dr = pd.date_range(start="1/1/2012", periods=1)
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repr(dr)
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dr = pd.date_range(start="1/1/2012", periods=2)
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repr(dr)
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dr = pd.date_range(start="1/1/2012", periods=3)
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repr(dr)
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@pytest.mark.parametrize(
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"dates, freq, expected_repr",
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[
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(
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["2012-01-01 00:00:00"],
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"60min",
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(
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"DatetimeIndex(['2012-01-01 00:00:00'], "
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"dtype='datetime64[ns]', freq='60min')"
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),
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),
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(
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["2012-01-01 00:00:00", "2012-01-01 01:00:00"],
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"60min",
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"DatetimeIndex(['2012-01-01 00:00:00', '2012-01-01 01:00:00'], "
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"dtype='datetime64[ns]', freq='60min')",
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),
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(
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["2012-01-01"],
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"24h",
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"DatetimeIndex(['2012-01-01'], dtype='datetime64[ns]', freq='24h')",
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),
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],
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)
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def test_dti_repr_time_midnight(self, dates, freq, expected_repr, unit):
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# GH53634
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dti = DatetimeIndex(dates, freq).as_unit(unit)
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actual_repr = repr(dti)
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assert actual_repr == expected_repr.replace("[ns]", f"[{unit}]")
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def test_dti_representation(self, unit):
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idxs = []
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idxs.append(DatetimeIndex([], freq="D"))
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idxs.append(DatetimeIndex(["2011-01-01"], freq="D"))
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idxs.append(DatetimeIndex(["2011-01-01", "2011-01-02"], freq="D"))
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idxs.append(DatetimeIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D"))
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idxs.append(
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DatetimeIndex(
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["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"],
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freq="h",
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tz="Asia/Tokyo",
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)
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)
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idxs.append(
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DatetimeIndex(
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["2011-01-01 09:00", "2011-01-01 10:00", NaT], tz="US/Eastern"
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)
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)
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idxs.append(
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DatetimeIndex(["2011-01-01 09:00", "2011-01-01 10:00", NaT], tz="UTC")
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)
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exp = []
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exp.append("DatetimeIndex([], dtype='datetime64[ns]', freq='D')")
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exp.append("DatetimeIndex(['2011-01-01'], dtype='datetime64[ns]', freq='D')")
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exp.append(
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"DatetimeIndex(['2011-01-01', '2011-01-02'], "
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"dtype='datetime64[ns]', freq='D')"
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)
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exp.append(
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"DatetimeIndex(['2011-01-01', '2011-01-02', '2011-01-03'], "
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"dtype='datetime64[ns]', freq='D')"
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)
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exp.append(
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"DatetimeIndex(['2011-01-01 09:00:00+09:00', "
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"'2011-01-01 10:00:00+09:00', '2011-01-01 11:00:00+09:00']"
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", dtype='datetime64[ns, Asia/Tokyo]', freq='h')"
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)
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exp.append(
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"DatetimeIndex(['2011-01-01 09:00:00-05:00', "
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"'2011-01-01 10:00:00-05:00', 'NaT'], "
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"dtype='datetime64[ns, US/Eastern]', freq=None)"
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)
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exp.append(
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"DatetimeIndex(['2011-01-01 09:00:00+00:00', "
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"'2011-01-01 10:00:00+00:00', 'NaT'], "
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"dtype='datetime64[ns, UTC]', freq=None)"
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""
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)
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with pd.option_context("display.width", 300):
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for index, expected in zip(idxs, exp):
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index = index.as_unit(unit)
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expected = expected.replace("[ns", f"[{unit}")
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result = repr(index)
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assert result == expected
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result = str(index)
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assert result == expected
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# TODO: this is a Series.__repr__ test
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def test_dti_representation_to_series(self, unit):
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idx1 = DatetimeIndex([], freq="D")
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idx2 = DatetimeIndex(["2011-01-01"], freq="D")
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idx3 = DatetimeIndex(["2011-01-01", "2011-01-02"], freq="D")
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idx4 = DatetimeIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D")
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idx5 = DatetimeIndex(
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["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"],
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freq="h",
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tz="Asia/Tokyo",
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)
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idx6 = DatetimeIndex(
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["2011-01-01 09:00", "2011-01-01 10:00", NaT], tz="US/Eastern"
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)
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idx7 = DatetimeIndex(["2011-01-01 09:00", "2011-01-02 10:15"])
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exp1 = """Series([], dtype: datetime64[ns])"""
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exp2 = "0 2011-01-01\ndtype: datetime64[ns]"
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exp3 = "0 2011-01-01\n1 2011-01-02\ndtype: datetime64[ns]"
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exp4 = (
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"0 2011-01-01\n"
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"1 2011-01-02\n"
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"2 2011-01-03\n"
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"dtype: datetime64[ns]"
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)
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exp5 = (
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"0 2011-01-01 09:00:00+09:00\n"
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"1 2011-01-01 10:00:00+09:00\n"
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"2 2011-01-01 11:00:00+09:00\n"
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"dtype: datetime64[ns, Asia/Tokyo]"
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)
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exp6 = (
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"0 2011-01-01 09:00:00-05:00\n"
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"1 2011-01-01 10:00:00-05:00\n"
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"2 NaT\n"
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"dtype: datetime64[ns, US/Eastern]"
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)
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exp7 = (
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"0 2011-01-01 09:00:00\n"
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"1 2011-01-02 10:15:00\n"
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"dtype: datetime64[ns]"
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)
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with pd.option_context("display.width", 300):
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for idx, expected in zip(
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[idx1, idx2, idx3, idx4, idx5, idx6, idx7],
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[exp1, exp2, exp3, exp4, exp5, exp6, exp7],
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):
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ser = Series(idx.as_unit(unit))
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result = repr(ser)
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assert result == expected.replace("[ns", f"[{unit}")
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def test_dti_summary(self):
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# GH#9116
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idx1 = DatetimeIndex([], freq="D")
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idx2 = DatetimeIndex(["2011-01-01"], freq="D")
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idx3 = DatetimeIndex(["2011-01-01", "2011-01-02"], freq="D")
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idx4 = DatetimeIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D")
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idx5 = DatetimeIndex(
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["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"],
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freq="h",
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tz="Asia/Tokyo",
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)
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idx6 = DatetimeIndex(
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["2011-01-01 09:00", "2011-01-01 10:00", NaT], tz="US/Eastern"
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)
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exp1 = "DatetimeIndex: 0 entries\nFreq: D"
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exp2 = "DatetimeIndex: 1 entries, 2011-01-01 to 2011-01-01\nFreq: D"
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exp3 = "DatetimeIndex: 2 entries, 2011-01-01 to 2011-01-02\nFreq: D"
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exp4 = "DatetimeIndex: 3 entries, 2011-01-01 to 2011-01-03\nFreq: D"
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exp5 = (
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"DatetimeIndex: 3 entries, 2011-01-01 09:00:00+09:00 "
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"to 2011-01-01 11:00:00+09:00\n"
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"Freq: h"
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)
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exp6 = """DatetimeIndex: 3 entries, 2011-01-01 09:00:00-05:00 to NaT"""
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for idx, expected in zip(
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[idx1, idx2, idx3, idx4, idx5, idx6], [exp1, exp2, exp3, exp4, exp5, exp6]
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):
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result = idx._summary()
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assert result == expected
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@pytest.mark.parametrize("tz", [None, pytz.utc, dateutil.tz.tzutc()])
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@pytest.mark.parametrize("freq", ["B", "C"])
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def test_dti_business_repr_etc_smoke(self, tz, freq):
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# only really care that it works
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dti = pd.bdate_range(
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datetime(2009, 1, 1), datetime(2010, 1, 1), tz=tz, freq=freq
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)
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repr(dti)
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dti._summary()
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dti[2:2]._summary()
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class TestFormat:
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def test_format(self):
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# GH#35439
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idx = pd.date_range("20130101", periods=5)
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expected = [f"{x:%Y-%m-%d}" for x in idx]
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msg = r"DatetimeIndex\.format is deprecated"
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with tm.assert_produces_warning(FutureWarning, match=msg):
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assert idx.format() == expected
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def test_format_with_name_time_info(self):
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# bug I fixed 12/20/2011
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dates = pd.date_range("2011-01-01 04:00:00", periods=10, name="something")
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msg = "DatetimeIndex.format is deprecated"
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with tm.assert_produces_warning(FutureWarning, match=msg):
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formatted = dates.format(name=True)
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assert formatted[0] == "something"
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def test_format_datetime_with_time(self):
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dti = DatetimeIndex([datetime(2012, 2, 7), datetime(2012, 2, 7, 23)])
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msg = "DatetimeIndex.format is deprecated"
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with tm.assert_produces_warning(FutureWarning, match=msg):
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result = dti.format()
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expected = ["2012-02-07 00:00:00", "2012-02-07 23:00:00"]
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assert len(result) == 2
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assert result == expected
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def test_format_datetime(self):
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msg = "DatetimeIndex.format is deprecated"
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with tm.assert_produces_warning(FutureWarning, match=msg):
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formatted = pd.to_datetime([datetime(2003, 1, 1, 12), NaT]).format()
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assert formatted[0] == "2003-01-01 12:00:00"
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assert formatted[1] == "NaT"
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def test_format_date(self):
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msg = "DatetimeIndex.format is deprecated"
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with tm.assert_produces_warning(FutureWarning, match=msg):
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formatted = pd.to_datetime([datetime(2003, 1, 1), NaT]).format()
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assert formatted[0] == "2003-01-01"
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assert formatted[1] == "NaT"
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def test_format_date_tz(self):
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dti = pd.to_datetime([datetime(2013, 1, 1)], utc=True)
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msg = "DatetimeIndex.format is deprecated"
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with tm.assert_produces_warning(FutureWarning, match=msg):
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formatted = dti.format()
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assert formatted[0] == "2013-01-01 00:00:00+00:00"
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dti = pd.to_datetime([datetime(2013, 1, 1), NaT], utc=True)
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with tm.assert_produces_warning(FutureWarning, match=msg):
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formatted = dti.format()
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assert formatted[0] == "2013-01-01 00:00:00+00:00"
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def test_format_date_explicit_date_format(self):
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dti = pd.to_datetime([datetime(2003, 2, 1), NaT])
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msg = "DatetimeIndex.format is deprecated"
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with tm.assert_produces_warning(FutureWarning, match=msg):
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formatted = dti.format(date_format="%m-%d-%Y", na_rep="UT")
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assert formatted[0] == "02-01-2003"
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assert formatted[1] == "UT"
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