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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 = Series(
np.arange(10, dtype=np.float64),
index=date_range("2020-01-01", periods=10),
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)