Why Gemfury? Push, build, and install  RubyGems npm packages Python packages Maven artifacts PHP packages Go Modules Bower components Debian packages RPM packages NuGet packages

aaronreidsmith / pandas   python

Repository URL to install this package:

Version: 0.25.3 

/ tests / frame / test_asof.py

import numpy as np
import pytest

from pandas import DataFrame, Series, Timestamp, date_range, to_datetime
import pandas.util.testing as tm


@pytest.fixture
def date_range_frame():
    """
    Fixture for DataFrame of ints with date_range index

    Columns are ['A', 'B'].
    """
    N = 50
    rng = date_range("1/1/1990", periods=N, freq="53s")
    return DataFrame({"A": np.arange(N), "B": np.arange(N)}, index=rng)


class TestFrameAsof:
    def test_basic(self, date_range_frame):
        df = date_range_frame
        N = 50
        df.loc[15:30, "A"] = np.nan
        dates = date_range("1/1/1990", periods=N * 3, freq="25s")

        result = df.asof(dates)
        assert result.notna().all(1).all()
        lb = df.index[14]
        ub = df.index[30]

        dates = list(dates)
        result = df.asof(dates)
        assert result.notna().all(1).all()

        mask = (result.index >= lb) & (result.index < ub)
        rs = result[mask]
        assert (rs == 14).all(1).all()

    def test_subset(self, date_range_frame):
        N = 10
        df = date_range_frame.iloc[:N].copy()
        df.loc[4:8, "A"] = np.nan
        dates = date_range("1/1/1990", periods=N * 3, freq="25s")

        # with a subset of A should be the same
        result = df.asof(dates, subset="A")
        expected = df.asof(dates)
        tm.assert_frame_equal(result, expected)

        # same with A/B
        result = df.asof(dates, subset=["A", "B"])
        expected = df.asof(dates)
        tm.assert_frame_equal(result, expected)

        # B gives df.asof
        result = df.asof(dates, subset="B")
        expected = df.resample("25s", closed="right").ffill().reindex(dates)
        expected.iloc[20:] = 9

        tm.assert_frame_equal(result, expected)

    def test_missing(self, date_range_frame):
        # GH 15118
        # no match found - `where` value before earliest date in index
        N = 10
        df = date_range_frame.iloc[:N].copy()
        result = df.asof("1989-12-31")

        expected = Series(index=["A", "B"], name=Timestamp("1989-12-31"))
        tm.assert_series_equal(result, expected)

        result = df.asof(to_datetime(["1989-12-31"]))
        expected = DataFrame(
            index=to_datetime(["1989-12-31"]), columns=["A", "B"], dtype="float64"
        )
        tm.assert_frame_equal(result, expected)

    def test_all_nans(self, date_range_frame):
        # GH 15713
        # DataFrame is all nans
        result = DataFrame([np.nan]).asof([0])
        expected = DataFrame([np.nan])
        tm.assert_frame_equal(result, expected)

        # testing non-default indexes, multiple inputs
        N = 150
        rng = date_range_frame.index
        dates = date_range("1/1/1990", periods=N, freq="25s")
        result = DataFrame(np.nan, index=rng, columns=["A"]).asof(dates)
        expected = DataFrame(np.nan, index=dates, columns=["A"])
        tm.assert_frame_equal(result, expected)

        # testing multiple columns
        dates = date_range("1/1/1990", periods=N, freq="25s")
        result = DataFrame(np.nan, index=rng, columns=["A", "B", "C"]).asof(dates)
        expected = DataFrame(np.nan, index=dates, columns=["A", "B", "C"])
        tm.assert_frame_equal(result, expected)

        # testing scalar input
        result = DataFrame(np.nan, index=[1, 2], columns=["A", "B"]).asof([3])
        expected = DataFrame(np.nan, index=[3], columns=["A", "B"])
        tm.assert_frame_equal(result, expected)

        result = DataFrame(np.nan, index=[1, 2], columns=["A", "B"]).asof(3)
        expected = Series(np.nan, index=["A", "B"], name=3)
        tm.assert_series_equal(result, expected)

    @pytest.mark.parametrize(
        "stamp,expected",
        [
            (
                Timestamp("2018-01-01 23:22:43.325+00:00"),
                Series(2.0, name=Timestamp("2018-01-01 23:22:43.325+00:00")),
            ),
            (
                Timestamp("2018-01-01 22:33:20.682+01:00"),
                Series(1.0, name=Timestamp("2018-01-01 22:33:20.682+01:00")),
            ),
        ],
    )
    def test_time_zone_aware_index(self, stamp, expected):
        # GH21194
        # Testing awareness of DataFrame index considering different
        # UTC and timezone
        df = DataFrame(
            data=[1, 2],
            index=[
                Timestamp("2018-01-01 21:00:05.001+00:00"),
                Timestamp("2018-01-01 22:35:10.550+00:00"),
            ],
        )
        result = df.asof(stamp)
        tm.assert_series_equal(result, expected)