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Merged
merged 4 commits into from
Jul 9, 2021
Merged

CLN: Group tests for apply/agg/transform with a string argument #42264

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721db7d
CLN: Group tests for apply/agg/transform with a string argument
rhshadrach Jun 26, 2021
30f8e50
Merge branch 'master' of https://github.com/pandas-dev/pandas into ap…
rhshadrach Jul 2, 2021
58d50d8
Move test changes from master into test_str
rhshadrach Jul 2, 2021
43b4608
Merge branch 'master' of https://github.com/pandas-dev/pandas into ap…
rhshadrach Jul 8, 2021
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122 changes: 0 additions & 122 deletions pandas/tests/apply/test_frame_apply.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,4 @@
from datetime import datetime
from itertools import chain
import warnings

import numpy as np
Expand Down Expand Up @@ -148,32 +147,6 @@ def test_apply_standard_nonunique():
tm.assert_series_equal(result, expected)


@pytest.mark.parametrize("func", ["sum", "mean", "min", "max", "std"])
@pytest.mark.parametrize(
"args,kwds",
[
pytest.param([], {}, id="no_args_or_kwds"),
pytest.param([1], {}, id="axis_from_args"),
pytest.param([], {"axis": 1}, id="axis_from_kwds"),
pytest.param([], {"numeric_only": True}, id="optional_kwds"),
pytest.param([1, None], {"numeric_only": True}, id="args_and_kwds"),
],
)
@pytest.mark.parametrize("how", ["agg", "apply"])
def test_apply_with_string_funcs(request, float_frame, func, args, kwds, how):
if len(args) > 1 and how == "agg":
request.node.add_marker(
pytest.mark.xfail(
raises=TypeError,
reason="agg/apply signature mismatch - agg passes 2nd "
"argument to func",
)
)
result = getattr(float_frame, how)(func, *args, **kwds)
expected = getattr(float_frame, func)(*args, **kwds)
tm.assert_series_equal(result, expected)


def test_apply_broadcast(float_frame, int_frame_const_col):

# scalars
Expand Down Expand Up @@ -1301,76 +1274,6 @@ def func(group_col):
tm.assert_frame_equal(result, expected)


@pytest.mark.parametrize(
"df, func, expected",
chain(
tm.get_cython_table_params(
DataFrame(),
[
("sum", Series(dtype="float64")),
("max", Series(dtype="float64")),
("min", Series(dtype="float64")),
("all", Series(dtype=bool)),
("any", Series(dtype=bool)),
("mean", Series(dtype="float64")),
("prod", Series(dtype="float64")),
("std", Series(dtype="float64")),
("var", Series(dtype="float64")),
("median", Series(dtype="float64")),
],
),
tm.get_cython_table_params(
DataFrame([[np.nan, 1], [1, 2]]),
[
("sum", Series([1.0, 3])),
("max", Series([1.0, 2])),
("min", Series([1.0, 1])),
("all", Series([True, True])),
("any", Series([True, True])),
("mean", Series([1, 1.5])),
("prod", Series([1.0, 2])),
("std", Series([np.nan, 0.707107])),
("var", Series([np.nan, 0.5])),
("median", Series([1, 1.5])),
],
),
),
)
def test_agg_cython_table(df, func, expected, axis):
# GH 21224
# test reducing functions in
# pandas.core.base.SelectionMixin._cython_table
result = df.agg(func, axis=axis)
tm.assert_series_equal(result, expected)


@pytest.mark.parametrize(
"df, func, expected",
chain(
tm.get_cython_table_params(
DataFrame(), [("cumprod", DataFrame()), ("cumsum", DataFrame())]
),
tm.get_cython_table_params(
DataFrame([[np.nan, 1], [1, 2]]),
[
("cumprod", DataFrame([[np.nan, 1], [1, 2]])),
("cumsum", DataFrame([[np.nan, 1], [1, 3]])),
],
),
),
)
def test_agg_cython_table_transform(df, func, expected, axis):
# GH 21224
# test transforming functions in
# pandas.core.base.SelectionMixin._cython_table (cumprod, cumsum)
if axis == "columns" or axis == 1:
# operating blockwise doesn't let us preserve dtypes
expected = expected.astype("float64")

result = df.agg(func, axis=axis)
tm.assert_frame_equal(result, expected)


@pytest.mark.parametrize("axis", [0, 1])
@pytest.mark.parametrize(
"args, kwargs",
Expand Down Expand Up @@ -1499,31 +1402,6 @@ def test_apply_raw_returns_string():
tm.assert_series_equal(result, expected)


@pytest.mark.parametrize(
"op", ["abs", "ceil", "cos", "cumsum", "exp", "log", "sqrt", "square"]
)
@pytest.mark.parametrize("how", ["transform", "apply"])
def test_apply_np_transformer(float_frame, op, how):
# GH 39116
result = getattr(float_frame, how)(op)
expected = getattr(np, op)(float_frame)
tm.assert_frame_equal(result, expected)


@pytest.mark.parametrize("op", ["mean", "median", "std", "var"])
@pytest.mark.parametrize("how", ["agg", "apply"])
def test_apply_np_reducer(float_frame, op, how):
# GH 39116
float_frame = DataFrame({"a": [1, 2], "b": [3, 4]})
result = getattr(float_frame, how)(op)
# pandas ddof defaults to 1, numpy to 0
kwargs = {"ddof": 1} if op in ("std", "var") else {}
expected = Series(
getattr(np, op)(float_frame, axis=0, **kwargs), index=float_frame.columns
)
tm.assert_series_equal(result, expected)


def test_aggregation_func_column_order():
# GH40420: the result of .agg should have an index that is sorted
# according to the arguments provided to agg.
Expand Down
45 changes: 0 additions & 45 deletions pandas/tests/apply/test_frame_transform.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,3 @@
import operator

import numpy as np
import pytest

Expand Down Expand Up @@ -38,40 +36,6 @@ def test_transform_ufunc(axis, float_frame, frame_or_series):
tm.assert_equal(result, expected)


@pytest.mark.parametrize("op", frame_transform_kernels)
def test_transform_groupby_kernel(axis, float_frame, op, using_array_manager, request):
# GH 35964
if using_array_manager and op == "pct_change" and axis in (1, "columns"):
# TODO(ArrayManager) shift with axis=1
request.node.add_marker(
pytest.mark.xfail(
reason="shift axis=1 not yet implemented for ArrayManager"
)
)

args = [0.0] if op == "fillna" else []
if axis == 0 or axis == "index":
ones = np.ones(float_frame.shape[0])
else:
ones = np.ones(float_frame.shape[1])
expected = float_frame.groupby(ones, axis=axis).transform(op, *args)
result = float_frame.transform(op, axis, *args)
tm.assert_frame_equal(result, expected)

# same thing, but ensuring we have multiple blocks
assert "E" not in float_frame.columns
float_frame["E"] = float_frame["A"].copy()
assert len(float_frame._mgr.arrays) > 1

if axis == 0 or axis == "index":
ones = np.ones(float_frame.shape[0])
else:
ones = np.ones(float_frame.shape[1])
expected2 = float_frame.groupby(ones, axis=axis).transform(op, *args)
result2 = float_frame.transform(op, axis, *args)
tm.assert_frame_equal(result2, expected2)


@pytest.mark.parametrize(
"ops, names",
[
Expand Down Expand Up @@ -162,15 +126,6 @@ def func(x):
tm.assert_equal(result, expected)


@pytest.mark.parametrize("method", ["abs", "shift", "pct_change", "cumsum", "rank"])
def test_transform_method_name(method):
# GH 19760
df = DataFrame({"A": [-1, 2]})
result = df.transform(method)
expected = operator.methodcaller(method)(df)
tm.assert_frame_equal(result, expected)


wont_fail = ["ffill", "bfill", "fillna", "pad", "backfill", "shift"]
frame_kernels_raise = [x for x in frame_transform_kernels if x not in wont_fail]

Expand Down
97 changes: 0 additions & 97 deletions pandas/tests/apply/test_series_apply.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,13 +2,10 @@
Counter,
defaultdict,
)
from itertools import chain

import numpy as np
import pytest

from pandas.core.dtypes.common import is_number

import pandas as pd
from pandas import (
DataFrame,
Expand Down Expand Up @@ -87,14 +84,6 @@ def f(x):
assert result.dtype == object


def test_with_string_args(datetime_series):

for arg in ["sum", "mean", "min", "max", "std"]:
result = datetime_series.apply(arg)
expected = getattr(datetime_series, arg)()
assert result == expected


def test_apply_args():
s = Series(["foo,bar"])

Expand Down Expand Up @@ -418,92 +407,6 @@ def test_non_callable_aggregates(how):
tm.assert_series_equal(result, expected)


@pytest.mark.parametrize(
"series, func, expected",
chain(
tm.get_cython_table_params(
Series(dtype=np.float64),
[
("sum", 0),
("max", np.nan),
("min", np.nan),
("all", True),
("any", False),
("mean", np.nan),
("prod", 1),
("std", np.nan),
("var", np.nan),
("median", np.nan),
],
),
tm.get_cython_table_params(
Series([np.nan, 1, 2, 3]),
[
("sum", 6),
("max", 3),
("min", 1),
("all", True),
("any", True),
("mean", 2),
("prod", 6),
("std", 1),
("var", 1),
("median", 2),
],
),
tm.get_cython_table_params(
Series("a b c".split()),
[
("sum", "abc"),
("max", "c"),
("min", "a"),
("all", True),
("any", True),
],
),
),
)
def test_agg_cython_table(series, func, expected):
# GH21224
# test reducing functions in
# pandas.core.base.SelectionMixin._cython_table
result = series.agg(func)
if is_number(expected):
assert np.isclose(result, expected, equal_nan=True)
else:
assert result == expected


@pytest.mark.parametrize(
"series, func, expected",
chain(
tm.get_cython_table_params(
Series(dtype=np.float64),
[
("cumprod", Series([], Index([]), dtype=np.float64)),
("cumsum", Series([], Index([]), dtype=np.float64)),
],
),
tm.get_cython_table_params(
Series([np.nan, 1, 2, 3]),
[
("cumprod", Series([np.nan, 1, 2, 6])),
("cumsum", Series([np.nan, 1, 3, 6])),
],
),
tm.get_cython_table_params(
Series("a b c".split()), [("cumsum", Series(["a", "ab", "abc"]))]
),
),
)
def test_agg_cython_table_transform(series, func, expected):
# GH21224
# test transforming functions in
# pandas.core.base.SelectionMixin._cython_table (cumprod, cumsum)
result = series.agg(func)
tm.assert_series_equal(result, expected)


def test_series_apply_no_suffix_index():
# GH36189
s = Series([4] * 3)
Expand Down
18 changes: 0 additions & 18 deletions pandas/tests/apply/test_series_transform.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,24 +8,6 @@
concat,
)
import pandas._testing as tm
from pandas.core.groupby.base import transformation_kernels

# tshift only works on time index and is deprecated
# There is no Series.cumcount
series_kernels = [
x for x in sorted(transformation_kernels) if x not in ["tshift", "cumcount"]
]


@pytest.mark.parametrize("op", series_kernels)
def test_transform_groupby_kernel(string_series, op):
# GH 35964

args = [0.0] if op == "fillna" else []
ones = np.ones(string_series.shape[0])
expected = string_series.groupby(ones).transform(op, *args)
result = string_series.transform(op, 0, *args)
tm.assert_series_equal(result, expected)


@pytest.mark.parametrize(
Expand Down
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