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