mirror of
https://github.com/PiBrewing/craftbeerpi4.git
synced 2024-12-26 07:24:56 +01:00
231 lines
7 KiB
Python
231 lines
7 KiB
Python
import numpy as np
|
|
import pytest
|
|
|
|
from pandas.errors import UnsupportedFunctionCall
|
|
|
|
import pandas as pd
|
|
from pandas import DataFrame, Series
|
|
import pandas._testing as tm
|
|
from pandas.core.window import Expanding
|
|
|
|
|
|
def test_doc_string():
|
|
|
|
df = DataFrame({"B": [0, 1, 2, np.nan, 4]})
|
|
df
|
|
df.expanding(2).sum()
|
|
|
|
|
|
@pytest.mark.filterwarnings(
|
|
"ignore:The `center` argument on `expanding` will be removed in the future"
|
|
)
|
|
def test_constructor(which):
|
|
# GH 12669
|
|
|
|
c = which.expanding
|
|
|
|
# valid
|
|
c(min_periods=1)
|
|
c(min_periods=1, center=True)
|
|
c(min_periods=1, center=False)
|
|
|
|
# not valid
|
|
for w in [2.0, "foo", np.array([2])]:
|
|
msg = "min_periods must be an integer"
|
|
with pytest.raises(ValueError, match=msg):
|
|
c(min_periods=w)
|
|
|
|
msg = "center must be a boolean"
|
|
with pytest.raises(ValueError, match=msg):
|
|
c(min_periods=1, center=w)
|
|
|
|
|
|
@pytest.mark.parametrize("method", ["std", "mean", "sum", "max", "min", "var"])
|
|
def test_numpy_compat(method):
|
|
# see gh-12811
|
|
e = Expanding(Series([2, 4, 6]), window=2)
|
|
|
|
msg = "numpy operations are not valid with window objects"
|
|
|
|
with pytest.raises(UnsupportedFunctionCall, match=msg):
|
|
getattr(e, method)(1, 2, 3)
|
|
with pytest.raises(UnsupportedFunctionCall, match=msg):
|
|
getattr(e, method)(dtype=np.float64)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"expander",
|
|
[
|
|
1,
|
|
pytest.param(
|
|
"ls",
|
|
marks=pytest.mark.xfail(
|
|
reason="GH#16425 expanding with offset not supported"
|
|
),
|
|
),
|
|
],
|
|
)
|
|
def test_empty_df_expanding(expander):
|
|
# GH 15819 Verifies that datetime and integer expanding windows can be
|
|
# applied to empty DataFrames
|
|
|
|
expected = DataFrame()
|
|
result = DataFrame().expanding(expander).sum()
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
# Verifies that datetime and integer expanding windows can be applied
|
|
# to empty DataFrames with datetime index
|
|
expected = DataFrame(index=pd.DatetimeIndex([]))
|
|
result = DataFrame(index=pd.DatetimeIndex([])).expanding(expander).sum()
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
|
|
def test_missing_minp_zero():
|
|
# https://github.com/pandas-dev/pandas/pull/18921
|
|
# minp=0
|
|
x = pd.Series([np.nan])
|
|
result = x.expanding(min_periods=0).sum()
|
|
expected = pd.Series([0.0])
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
# minp=1
|
|
result = x.expanding(min_periods=1).sum()
|
|
expected = pd.Series([np.nan])
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
|
|
def test_expanding_axis(axis_frame):
|
|
# see gh-23372.
|
|
df = DataFrame(np.ones((10, 20)))
|
|
axis = df._get_axis_number(axis_frame)
|
|
|
|
if axis == 0:
|
|
expected = DataFrame(
|
|
{i: [np.nan] * 2 + [float(j) for j in range(3, 11)] for i in range(20)}
|
|
)
|
|
else:
|
|
# axis == 1
|
|
expected = DataFrame([[np.nan] * 2 + [float(i) for i in range(3, 21)]] * 10)
|
|
|
|
result = df.expanding(3, axis=axis_frame).sum()
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
|
|
@pytest.mark.parametrize("constructor", [Series, DataFrame])
|
|
def test_expanding_count_with_min_periods(constructor):
|
|
# GH 26996
|
|
result = constructor(range(5)).expanding(min_periods=3).count()
|
|
expected = constructor([np.nan, np.nan, 3.0, 4.0, 5.0])
|
|
tm.assert_equal(result, expected)
|
|
|
|
|
|
@pytest.mark.parametrize("constructor", [Series, DataFrame])
|
|
def test_expanding_count_default_min_periods_with_null_values(constructor):
|
|
# GH 26996
|
|
values = [1, 2, 3, np.nan, 4, 5, 6]
|
|
expected_counts = [1.0, 2.0, 3.0, 3.0, 4.0, 5.0, 6.0]
|
|
|
|
result = constructor(values).expanding().count()
|
|
expected = constructor(expected_counts)
|
|
tm.assert_equal(result, expected)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"df,expected,min_periods",
|
|
[
|
|
(
|
|
DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}),
|
|
[
|
|
({"A": [1], "B": [4]}, [0]),
|
|
({"A": [1, 2], "B": [4, 5]}, [0, 1]),
|
|
({"A": [1, 2, 3], "B": [4, 5, 6]}, [0, 1, 2]),
|
|
],
|
|
3,
|
|
),
|
|
(
|
|
DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}),
|
|
[
|
|
({"A": [1], "B": [4]}, [0]),
|
|
({"A": [1, 2], "B": [4, 5]}, [0, 1]),
|
|
({"A": [1, 2, 3], "B": [4, 5, 6]}, [0, 1, 2]),
|
|
],
|
|
2,
|
|
),
|
|
(
|
|
DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}),
|
|
[
|
|
({"A": [1], "B": [4]}, [0]),
|
|
({"A": [1, 2], "B": [4, 5]}, [0, 1]),
|
|
({"A": [1, 2, 3], "B": [4, 5, 6]}, [0, 1, 2]),
|
|
],
|
|
1,
|
|
),
|
|
(DataFrame({"A": [1], "B": [4]}), [], 2),
|
|
(DataFrame(), [({}, [])], 1),
|
|
(
|
|
DataFrame({"A": [1, np.nan, 3], "B": [np.nan, 5, 6]}),
|
|
[
|
|
({"A": [1.0], "B": [np.nan]}, [0]),
|
|
({"A": [1, np.nan], "B": [np.nan, 5]}, [0, 1]),
|
|
({"A": [1, np.nan, 3], "B": [np.nan, 5, 6]}, [0, 1, 2]),
|
|
],
|
|
3,
|
|
),
|
|
(
|
|
DataFrame({"A": [1, np.nan, 3], "B": [np.nan, 5, 6]}),
|
|
[
|
|
({"A": [1.0], "B": [np.nan]}, [0]),
|
|
({"A": [1, np.nan], "B": [np.nan, 5]}, [0, 1]),
|
|
({"A": [1, np.nan, 3], "B": [np.nan, 5, 6]}, [0, 1, 2]),
|
|
],
|
|
2,
|
|
),
|
|
(
|
|
DataFrame({"A": [1, np.nan, 3], "B": [np.nan, 5, 6]}),
|
|
[
|
|
({"A": [1.0], "B": [np.nan]}, [0]),
|
|
({"A": [1, np.nan], "B": [np.nan, 5]}, [0, 1]),
|
|
({"A": [1, np.nan, 3], "B": [np.nan, 5, 6]}, [0, 1, 2]),
|
|
],
|
|
1,
|
|
),
|
|
],
|
|
)
|
|
def test_iter_expanding_dataframe(df, expected, min_periods):
|
|
# GH 11704
|
|
expected = [DataFrame(values, index=index) for (values, index) in expected]
|
|
|
|
for (expected, actual) in zip(expected, df.expanding(min_periods)):
|
|
tm.assert_frame_equal(actual, expected)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"ser,expected,min_periods",
|
|
[
|
|
(Series([1, 2, 3]), [([1], [0]), ([1, 2], [0, 1]), ([1, 2, 3], [0, 1, 2])], 3),
|
|
(Series([1, 2, 3]), [([1], [0]), ([1, 2], [0, 1]), ([1, 2, 3], [0, 1, 2])], 2),
|
|
(Series([1, 2, 3]), [([1], [0]), ([1, 2], [0, 1]), ([1, 2, 3], [0, 1, 2])], 1),
|
|
(Series([1, 2]), [([1], [0]), ([1, 2], [0, 1])], 2),
|
|
(Series([np.nan, 2]), [([np.nan], [0]), ([np.nan, 2], [0, 1])], 2),
|
|
(Series([], dtype="int64"), [], 2),
|
|
],
|
|
)
|
|
def test_iter_expanding_series(ser, expected, min_periods):
|
|
# GH 11704
|
|
expected = [Series(values, index=index) for (values, index) in expected]
|
|
|
|
for (expected, actual) in zip(expected, ser.expanding(min_periods)):
|
|
tm.assert_series_equal(actual, expected)
|
|
|
|
|
|
def test_center_deprecate_warning():
|
|
# GH 20647
|
|
df = pd.DataFrame()
|
|
with tm.assert_produces_warning(FutureWarning):
|
|
df.expanding(center=True)
|
|
|
|
with tm.assert_produces_warning(FutureWarning):
|
|
df.expanding(center=False)
|
|
|
|
with tm.assert_produces_warning(None):
|
|
df.expanding()
|