import numpy as np
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import pytest
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from pandas import (
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Series,
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TimedeltaIndex,
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date_range,
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)
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import pandas._testing as tm
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class TestSeriesDiff:
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def test_diff_np(self):
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# TODO(__array_function__): could make np.diff return a Series
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# matching ser.diff()
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ser = Series(np.arange(5))
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res = np.diff(ser)
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expected = np.array([1, 1, 1, 1])
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tm.assert_numpy_array_equal(res, expected)
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def test_diff_int(self):
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# int dtype
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a = 10000000000000000
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b = a + 1
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ser = Series([a, b])
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result = ser.diff()
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assert result[1] == 1
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def test_diff_tz(self):
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# Combined datetime diff, normal diff and boolean diff test
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ts = tm.makeTimeSeries(name="ts")
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ts.diff()
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# neg n
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result = ts.diff(-1)
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expected = ts - ts.shift(-1)
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tm.assert_series_equal(result, expected)
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# 0
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result = ts.diff(0)
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expected = ts - ts
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tm.assert_series_equal(result, expected)
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def test_diff_dt64(self):
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# datetime diff (GH#3100)
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ser = Series(date_range("20130102", periods=5))
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result = ser.diff()
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expected = ser - ser.shift(1)
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tm.assert_series_equal(result, expected)
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# timedelta diff
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result = result - result.shift(1) # previous result
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expected = expected.diff() # previously expected
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tm.assert_series_equal(result, expected)
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def test_diff_dt64tz(self):
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# with tz
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ser = Series(
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date_range("2000-01-01 09:00:00", periods=5, tz="US/Eastern"), name="foo"
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)
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result = ser.diff()
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expected = Series(TimedeltaIndex(["NaT"] + ["1 days"] * 4), name="foo")
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tm.assert_series_equal(result, expected)
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@pytest.mark.parametrize(
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"input,output,diff",
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[([False, True, True, False, False], [np.nan, True, False, True, False], 1)],
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)
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def test_diff_bool(self, input, output, diff):
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# boolean series (test for fixing #17294)
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ser = Series(input)
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result = ser.diff()
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expected = Series(output)
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tm.assert_series_equal(result, expected)
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def test_diff_object_dtype(self):
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# object series
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ser = Series([False, True, 5.0, np.nan, True, False])
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result = ser.diff()
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expected = ser - ser.shift(1)
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tm.assert_series_equal(result, expected)
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