118 lines
4.4 KiB
Python
118 lines
4.4 KiB
Python
import numpy as np
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import pytest
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from pandas import DataFrame, Series
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import pandas._testing as tm
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class TestDataFramePctChange:
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@pytest.mark.parametrize(
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"periods,fill_method,limit,exp",
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[
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(1, "ffill", None, [np.nan, np.nan, np.nan, 1, 1, 1.5, 0, 0]),
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(1, "ffill", 1, [np.nan, np.nan, np.nan, 1, 1, 1.5, 0, np.nan]),
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(1, "bfill", None, [np.nan, 0, 0, 1, 1, 1.5, np.nan, np.nan]),
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(1, "bfill", 1, [np.nan, np.nan, 0, 1, 1, 1.5, np.nan, np.nan]),
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(-1, "ffill", None, [np.nan, np.nan, -0.5, -0.5, -0.6, 0, 0, np.nan]),
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(-1, "ffill", 1, [np.nan, np.nan, -0.5, -0.5, -0.6, 0, np.nan, np.nan]),
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(-1, "bfill", None, [0, 0, -0.5, -0.5, -0.6, np.nan, np.nan, np.nan]),
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(-1, "bfill", 1, [np.nan, 0, -0.5, -0.5, -0.6, np.nan, np.nan, np.nan]),
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],
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)
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@pytest.mark.parametrize("klass", [DataFrame, Series])
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def test_pct_change_with_nas(self, periods, fill_method, limit, exp, klass):
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vals = [np.nan, np.nan, 1, 2, 4, 10, np.nan, np.nan]
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obj = klass(vals)
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res = obj.pct_change(periods=periods, fill_method=fill_method, limit=limit)
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tm.assert_equal(res, klass(exp))
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def test_pct_change_numeric(self):
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# GH#11150
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pnl = DataFrame(
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[np.arange(0, 40, 10), np.arange(0, 40, 10), np.arange(0, 40, 10)]
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).astype(np.float64)
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pnl.iat[1, 0] = np.nan
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pnl.iat[1, 1] = np.nan
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pnl.iat[2, 3] = 60
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for axis in range(2):
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expected = pnl.ffill(axis=axis) / pnl.ffill(axis=axis).shift(axis=axis) - 1
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result = pnl.pct_change(axis=axis, fill_method="pad")
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tm.assert_frame_equal(result, expected)
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def test_pct_change(self, datetime_frame):
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rs = datetime_frame.pct_change(fill_method=None)
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tm.assert_frame_equal(rs, datetime_frame / datetime_frame.shift(1) - 1)
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rs = datetime_frame.pct_change(2)
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filled = datetime_frame.fillna(method="pad")
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tm.assert_frame_equal(rs, filled / filled.shift(2) - 1)
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rs = datetime_frame.pct_change(fill_method="bfill", limit=1)
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filled = datetime_frame.fillna(method="bfill", limit=1)
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tm.assert_frame_equal(rs, filled / filled.shift(1) - 1)
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rs = datetime_frame.pct_change(freq="5D")
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filled = datetime_frame.fillna(method="pad")
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tm.assert_frame_equal(
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rs, (filled / filled.shift(freq="5D") - 1).reindex_like(filled)
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)
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def test_pct_change_shift_over_nas(self):
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s = Series([1.0, 1.5, np.nan, 2.5, 3.0])
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df = DataFrame({"a": s, "b": s})
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chg = df.pct_change()
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expected = Series([np.nan, 0.5, 0.0, 2.5 / 1.5 - 1, 0.2])
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edf = DataFrame({"a": expected, "b": expected})
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tm.assert_frame_equal(chg, edf)
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@pytest.mark.parametrize(
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"freq, periods, fill_method, limit",
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[
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("5B", 5, None, None),
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("3B", 3, None, None),
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("3B", 3, "bfill", None),
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("7B", 7, "pad", 1),
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("7B", 7, "bfill", 3),
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("14B", 14, None, None),
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],
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)
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def test_pct_change_periods_freq(
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self, datetime_frame, freq, periods, fill_method, limit
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):
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# GH#7292
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rs_freq = datetime_frame.pct_change(
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freq=freq, fill_method=fill_method, limit=limit
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)
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rs_periods = datetime_frame.pct_change(
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periods, fill_method=fill_method, limit=limit
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)
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tm.assert_frame_equal(rs_freq, rs_periods)
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empty_ts = DataFrame(index=datetime_frame.index, columns=datetime_frame.columns)
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rs_freq = empty_ts.pct_change(freq=freq, fill_method=fill_method, limit=limit)
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rs_periods = empty_ts.pct_change(periods, fill_method=fill_method, limit=limit)
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tm.assert_frame_equal(rs_freq, rs_periods)
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@pytest.mark.parametrize("fill_method", ["pad", "ffill", None])
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def test_pct_change_with_duplicated_indices(fill_method):
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# GH30463
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data = DataFrame(
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{0: [np.nan, 1, 2, 3, 9, 18], 1: [0, 1, np.nan, 3, 9, 18]}, index=["a", "b"] * 3
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)
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result = data.pct_change(fill_method=fill_method)
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if fill_method is None:
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second_column = [np.nan, np.inf, np.nan, np.nan, 2.0, 1.0]
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else:
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second_column = [np.nan, np.inf, 0.0, 2.0, 2.0, 1.0]
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expected = DataFrame(
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{0: [np.nan, np.nan, 1.0, 0.5, 2.0, 1.0], 1: second_column},
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index=["a", "b"] * 3,
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)
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tm.assert_frame_equal(result, expected)
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