peacock-data-public-datasets-idc-cronscript
/
venv
/lib
/python3.10
/site-packages
/pandas
/tests
/series
/test_cumulative.py
""" | |
Tests for Series cumulative operations. | |
See also | |
-------- | |
tests.frame.test_cumulative | |
""" | |
import numpy as np | |
import pytest | |
import pandas as pd | |
import pandas._testing as tm | |
methods = { | |
"cumsum": np.cumsum, | |
"cumprod": np.cumprod, | |
"cummin": np.minimum.accumulate, | |
"cummax": np.maximum.accumulate, | |
} | |
class TestSeriesCumulativeOps: | |
def test_datetime_series(self, datetime_series, func): | |
tm.assert_numpy_array_equal( | |
func(datetime_series).values, | |
func(np.array(datetime_series)), | |
check_dtype=True, | |
) | |
# with missing values | |
ts = datetime_series.copy() | |
ts[::2] = np.nan | |
result = func(ts)[1::2] | |
expected = func(np.array(ts.dropna())) | |
tm.assert_numpy_array_equal(result.values, expected, check_dtype=False) | |
def test_cummin_cummax(self, datetime_series, method): | |
ufunc = methods[method] | |
result = getattr(datetime_series, method)().values | |
expected = ufunc(np.array(datetime_series)) | |
tm.assert_numpy_array_equal(result, expected) | |
ts = datetime_series.copy() | |
ts[::2] = np.nan | |
result = getattr(ts, method)()[1::2] | |
expected = ufunc(ts.dropna()) | |
result.index = result.index._with_freq(None) | |
tm.assert_series_equal(result, expected) | |
def test_cummin_cummax_datetimelike(self, ts, method, skipna, exp_tdi): | |
# with ts==pd.Timedelta(0), we are testing td64; with naive Timestamp | |
# we are testing datetime64[ns]; with Timestamp[US/Pacific] | |
# we are testing dt64tz | |
tdi = pd.to_timedelta(["NaT", "2 days", "NaT", "1 days", "NaT", "3 days"]) | |
ser = pd.Series(tdi + ts) | |
exp_tdi = pd.to_timedelta(exp_tdi) | |
expected = pd.Series(exp_tdi + ts) | |
result = getattr(ser, method)(skipna=skipna) | |
tm.assert_series_equal(expected, result) | |
def test_cummin_cummax_period(self, func, exp): | |
# GH#28385 | |
ser = pd.Series( | |
[pd.Period("2012-1-1", freq="D"), pd.NaT, pd.Period("2012-1-2", freq="D")] | |
) | |
result = getattr(ser, func)(skipna=False) | |
expected = pd.Series([pd.Period("2012-1-1", freq="D"), pd.NaT, pd.NaT]) | |
tm.assert_series_equal(result, expected) | |
result = getattr(ser, func)(skipna=True) | |
expected = pd.Series([pd.Period("2012-1-1", freq="D"), pd.NaT, exp]) | |
tm.assert_series_equal(result, expected) | |
def test_cummethods_bool(self, arg, func, method): | |
# GH#6270 | |
# checking Series method vs the ufunc applied to the values | |
ser = func(pd.Series(arg)) | |
ufunc = methods[method] | |
exp_vals = ufunc(ser.values) | |
expected = pd.Series(exp_vals) | |
result = getattr(ser, method)() | |
tm.assert_series_equal(result, expected) | |
def test_cummethods_bool_in_object_dtype(self, method, expected): | |
ser = pd.Series([False, True, np.nan, False]) | |
result = getattr(ser, method)() | |
tm.assert_series_equal(result, expected) | |
def test_cumprod_timedelta(self): | |
# GH#48111 | |
ser = pd.Series([pd.Timedelta(days=1), pd.Timedelta(days=3)]) | |
with pytest.raises(TypeError, match="cumprod not supported for Timedelta"): | |
ser.cumprod() | |