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@Charlie-XIAO
Charlie-XIAO committed Jun 7, 2023
1 parent 59ddbc6 commit 2cb449b
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Showing 4 changed files with 110 additions and 90 deletions.
21 changes: 11 additions & 10 deletions pandas/core/generic.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -11144,7 +11144,7 @@ def pct_change(
self,
periods: int = 1,
fill_method: FillnaOptions | None | lib.NoDefault = lib.no_default,
limit: int | None | lib.NoDefault = lib.no_default,
limit: int | None = None,
freq=None,
**kwargs,
) -> Self:
Expand Down Expand Up @@ -11275,20 +11275,21 @@ def pct_change(
GOOG 0.179241 0.094112 NaN
APPL -0.252395 -0.011860 NaN
"""
if fill_method is not lib.no_default or limit is not lib.no_default:
# GH#53491
# GH#53491: deprecate default fill_method="pad"
# TODO: In 3.x, change default fill_method=None, then also in 3.x
# deprecate the fill_method and limit keywords, and finally remove
# them in 4.x
if fill_method is lib.no_default:
warnings.warn(
"The 'fill_method' and 'limit' keywords in "
f"{type(self).__name__}.pct_change are deprecated and will be "
"removed in a future version. Call fillna directly before "
"calling pct_change instead.",
f"The default fill_method='pad' in {type(self).__name__}.pct_change "
"is deprecated and will be changed to None in a future version of "
"pandas. Pass fill_method='pad' to retain current behavior or "
"fill_method=None to adopt the future default and silence this "
"warning.",
FutureWarning,
stacklevel=find_stack_level(),
)
if fill_method is lib.no_default:
fill_method = "pad"
if limit is lib.no_default:
limit = None

axis = self._get_axis_number(kwargs.pop("axis", "index"))
if fill_method is None:
Expand Down
21 changes: 11 additions & 10 deletions pandas/core/groupby/groupby.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -3946,7 +3946,7 @@ def pct_change(
self,
periods: int = 1,
fill_method: FillnaOptions | lib.NoDefault = lib.no_default,
limit: int | None | lib.NoDefault = lib.no_default,
limit: int | None = None,
freq=None,
axis: Axis | lib.NoDefault = lib.no_default,
):
Expand All @@ -3958,20 +3958,21 @@ def pct_change(
Series or DataFrame
Percentage changes within each group.
"""
if fill_method is not lib.no_default or limit is not lib.no_default:
# GH#53491
# GH#53491: deprecate default fill_method="ffill"
# TODO: In 3.x, change default fill_method=None, then also in 3.x
# deprecate the fill_method and limit keywords, and finally remove
# them in 4.x
if fill_method is lib.no_default:
warnings.warn(
"The 'fill_method' and 'limit' keywords in "
f"{type(self).__name__}.pct_change are deprecated and will be "
"removed in a future version. Call fillna directly before "
"calling pct_change instead.",
f"The default fill_method='ffill' in {type(self).__name__}.pct_change "
"is deprecated and will be changed to None in a future version of "
"pandas. Pass fill_method='ffill' to retain current behavior or "
"fill_method=None to adopt the future default and silence this "
"warning.",
FutureWarning,
stacklevel=find_stack_level(),
)
if fill_method is lib.no_default:
fill_method = "ffill"
if limit is lib.no_default:
limit = None

if axis is not lib.no_default:
axis = self.obj._get_axis_number(axis)
Expand Down
78 changes: 23 additions & 55 deletions pandas/tests/frame/methods/test_pct_change.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@

class TestDataFramePctChange:
@pytest.mark.parametrize(
"periods, fill_method, limit, exp",
"periods,fill_method,limit,exp",
[
(1, "ffill", None, [np.nan, np.nan, np.nan, 1, 1, 1.5, 0, 0]),
(1, "ffill", 1, [np.nan, np.nan, np.nan, 1, 1, 1.5, 0, np.nan]),
Expand All @@ -28,12 +28,7 @@ def test_pct_change_with_nas(
vals = [np.nan, np.nan, 1, 2, 4, 10, np.nan, np.nan]
obj = frame_or_series(vals)

msg = (
"The 'fill_method' and 'limit' keywords in "
f"{type(obj).__name__}.pct_change are deprecated"
)
with tm.assert_produces_warning(FutureWarning, match=msg):
res = obj.pct_change(periods=periods, fill_method=fill_method, limit=limit)
res = obj.pct_change(periods=periods, fill_method=fill_method, limit=limit)
tm.assert_equal(res, frame_or_series(exp))

def test_pct_change_numeric(self):
Expand All @@ -45,49 +40,41 @@ def test_pct_change_numeric(self):
pnl.iat[1, 1] = np.nan
pnl.iat[2, 3] = 60

msg = (
"The 'fill_method' and 'limit' keywords in "
"DataFrame.pct_change are deprecated"
)

for axis in range(2):
expected = pnl.ffill(axis=axis) / pnl.ffill(axis=axis).shift(axis=axis) - 1

with tm.assert_produces_warning(FutureWarning, match=msg):
result = pnl.pct_change(axis=axis, fill_method="pad")
result = pnl.pct_change(axis=axis, fill_method="pad")
tm.assert_frame_equal(result, expected)

def test_pct_change(self, datetime_frame):
msg = (
"The 'fill_method' and 'limit' keywords in "
"DataFrame.pct_change are deprecated"
)
msg = "The default fill_method='pad' in DataFrame.pct_change is deprecated"

with tm.assert_produces_warning(FutureWarning, match=msg):
rs = datetime_frame.pct_change(fill_method=None)
rs = datetime_frame.pct_change(fill_method=None)
tm.assert_frame_equal(rs, datetime_frame / datetime_frame.shift(1) - 1)

rs = datetime_frame.pct_change(2)
with tm.assert_produces_warning(FutureWarning, match=msg):
rs = datetime_frame.pct_change(2)
filled = datetime_frame.fillna(method="pad")
tm.assert_frame_equal(rs, filled / filled.shift(2) - 1)

with tm.assert_produces_warning(FutureWarning, match=msg):
rs = datetime_frame.pct_change(fill_method="bfill", limit=1)
rs = datetime_frame.pct_change(fill_method="bfill", limit=1)
filled = datetime_frame.fillna(method="bfill", limit=1)
tm.assert_frame_equal(rs, filled / filled.shift(1) - 1)

rs = datetime_frame.pct_change(freq="5D")
with tm.assert_produces_warning(FutureWarning, match=msg):
rs = datetime_frame.pct_change(freq="5D")
filled = datetime_frame.fillna(method="pad")
tm.assert_frame_equal(
rs, (filled / filled.shift(freq="5D") - 1).reindex_like(filled)
)

def test_pct_change_shift_over_nas(self):
s = Series([1.0, 1.5, np.nan, 2.5, 3.0])

df = DataFrame({"a": s, "b": s})

chg = df.pct_change()
msg = "The default fill_method='pad' in DataFrame.pct_change is deprecated"
with tm.assert_produces_warning(FutureWarning, match=msg):
chg = df.pct_change()

expected = Series([np.nan, 0.5, 0.0, 2.5 / 1.5 - 1, 0.2])
edf = DataFrame({"a": expected, "b": expected})
tm.assert_frame_equal(chg, edf)
Expand All @@ -106,31 +93,18 @@ def test_pct_change_shift_over_nas(self):
def test_pct_change_periods_freq(
self, datetime_frame, freq, periods, fill_method, limit
):
msg = (
"The 'fill_method' and 'limit' keywords in "
"DataFrame.pct_change are deprecated"
)

# GH#7292
with tm.assert_produces_warning(FutureWarning, match=msg):
rs_freq = datetime_frame.pct_change(
freq=freq, fill_method=fill_method, limit=limit
)
with tm.assert_produces_warning(FutureWarning, match=msg):
rs_periods = datetime_frame.pct_change(
periods, fill_method=fill_method, limit=limit
)
rs_freq = datetime_frame.pct_change(
freq=freq, fill_method=fill_method, limit=limit
)
rs_periods = datetime_frame.pct_change(
periods, fill_method=fill_method, limit=limit
)
tm.assert_frame_equal(rs_freq, rs_periods)

empty_ts = DataFrame(index=datetime_frame.index, columns=datetime_frame.columns)
with tm.assert_produces_warning(FutureWarning, match=msg):
rs_freq = empty_ts.pct_change(
freq=freq, fill_method=fill_method, limit=limit
)
with tm.assert_produces_warning(FutureWarning, match=msg):
rs_periods = empty_ts.pct_change(
periods, fill_method=fill_method, limit=limit
)
rs_freq = empty_ts.pct_change(freq=freq, fill_method=fill_method, limit=limit)
rs_periods = empty_ts.pct_change(periods, fill_method=fill_method, limit=limit)
tm.assert_frame_equal(rs_freq, rs_periods)


Expand All @@ -140,13 +114,7 @@ def test_pct_change_with_duplicated_indices(fill_method):
data = DataFrame(
{0: [np.nan, 1, 2, 3, 9, 18], 1: [0, 1, np.nan, 3, 9, 18]}, index=["a", "b"] * 3
)

msg = (
"The 'fill_method' and 'limit' keywords in "
"DataFrame.pct_change are deprecated"
)
with tm.assert_produces_warning(FutureWarning, match=msg):
result = data.pct_change(fill_method=fill_method)
result = data.pct_change(fill_method=fill_method)

if fill_method is None:
second_column = [np.nan, np.inf, np.nan, np.nan, 2.0, 1.0]
Expand Down
80 changes: 65 additions & 15 deletions pandas/tests/groupby/transform/test_transform.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -169,8 +169,18 @@ def test_transform_axis_1(request, transformation_func):
msg = "DataFrame.groupby with axis=1 is deprecated"
with tm.assert_produces_warning(FutureWarning, match=msg):
gb = df.groupby([0, 0, 1], axis=1)
result = gb.transform(transformation_func, *args)
expected = df.T.groupby([0, 0, 1]).transform(transformation_func, *args).T

pct_change_msg = (
"The default fill_method='ffill' in DataFrameGroupBy.pct_change is deprecated"
)
if transformation_func == "pct_change":
with tm.assert_produces_warning(FutureWarning, match=pct_change_msg):
result = gb.transform("pct_change", *args)
with tm.assert_produces_warning(FutureWarning, match=pct_change_msg):
expected = df.T.groupby([0, 0, 1]).transform("pct_change", *args).T
else:
result = gb.transform(transformation_func, *args)
expected = df.T.groupby([0, 0, 1]).transform(transformation_func, *args).T

if transformation_func in ["diff", "shift"]:
# Result contains nans, so transpose coerces to float
Expand Down Expand Up @@ -404,11 +414,25 @@ def mock_op(x):
test_op = lambda x: x.transform(transformation_func)
mock_op = lambda x: getattr(x, transformation_func)()

result = test_op(df.groupby("A"))
msg = "The default fill_method='pad' in DataFrame.pct_change is deprecated"
groupby_msg = (
"The default fill_method='ffill' in DataFrameGroupBy.pct_change is deprecated"
)

if transformation_func == "pct_change":
with tm.assert_produces_warning(FutureWarning, match=groupby_msg):
result = test_op(df.groupby("A"))
else:
result = test_op(df.groupby("A"))

# pass the group in same order as iterating `for ... in df.groupby(...)`
# but reorder to match df's index since this is a transform
groups = [df[["B"]].iloc[4:6], df[["B"]].iloc[6:], df[["B"]].iloc[:4]]
expected = concat([mock_op(g) for g in groups]).sort_index()
if transformation_func == "pct_change":
with tm.assert_produces_warning(FutureWarning, match=msg):
expected = concat([mock_op(g) for g in groups]).sort_index()
else:
expected = concat([mock_op(g) for g in groups]).sort_index()
# sort_index does not preserve the freq
expected = expected.set_axis(df.index)

Expand Down Expand Up @@ -969,14 +993,9 @@ def test_pct_change(frame_or_series, freq, periods, fill_method, limit):
else:
expected = expected.to_frame("vals")

msg = (
"The 'fill_method' and 'limit' keywords in "
f"{type(gb).__name__}.pct_change are deprecated"
result = gb.pct_change(
periods=periods, fill_method=fill_method, limit=limit, freq=freq
)
with tm.assert_produces_warning(FutureWarning, match=msg):
result = gb.pct_change(
periods=periods, fill_method=fill_method, limit=limit, freq=freq
)
tm.assert_equal(result, expected)


Expand Down Expand Up @@ -1394,13 +1413,21 @@ def test_null_group_str_transformer(request, dropna, transformation_func):
args = get_groupby_method_args(transformation_func, df)
gb = df.groupby("A", dropna=dropna)

msg = "The default fill_method='pad' in DataFrame.pct_change is deprecated"
groupby_msg = (
"The default fill_method='ffill' in DataFrameGroupBy.pct_change is deprecated"
)

buffer = []
for k, (idx, group) in enumerate(gb):
if transformation_func == "cumcount":
# DataFrame has no cumcount method
res = DataFrame({"B": range(len(group))}, index=group.index)
elif transformation_func == "ngroup":
res = DataFrame(len(group) * [k], index=group.index, columns=["B"])
elif transformation_func == "pct_change":
with tm.assert_produces_warning(FutureWarning, match=msg):
res = getattr(group[["B"]], "pct_change")(*args)
else:
res = getattr(group[["B"]], transformation_func)(*args)
buffer.append(res)
Expand All @@ -1413,7 +1440,11 @@ def test_null_group_str_transformer(request, dropna, transformation_func):
# ngroup/cumcount always returns a Series as it counts the groups, not values
expected = expected["B"].rename(None)

result = gb.transform(transformation_func, *args)
if transformation_func == "pct_change":
with tm.assert_produces_warning(FutureWarning, match=groupby_msg):
result = gb.transform("pct_change", *args)
else:
result = gb.transform(transformation_func, *args)

tm.assert_equal(result, expected)

Expand Down Expand Up @@ -1465,13 +1496,21 @@ def test_null_group_str_transformer_series(dropna, transformation_func):
args = get_groupby_method_args(transformation_func, ser)
gb = ser.groupby([1, 1, np.nan], dropna=dropna)

msg = "The default fill_method='pad' in Series.pct_change is deprecated"
groupby_msg = (
"The default fill_method='ffill' in SeriesGroupBy.pct_change is deprecated"
)

buffer = []
for k, (idx, group) in enumerate(gb):
if transformation_func == "cumcount":
# Series has no cumcount method
res = Series(range(len(group)), index=group.index)
elif transformation_func == "ngroup":
res = Series(k, index=group.index)
elif transformation_func == "pct_change":
with tm.assert_produces_warning(FutureWarning, match=msg):
res = getattr(group, "pct_change")(*args)
else:
res = getattr(group, transformation_func)(*args)
buffer.append(res)
Expand All @@ -1480,7 +1519,10 @@ def test_null_group_str_transformer_series(dropna, transformation_func):
buffer.append(Series([np.nan], index=[3], dtype=dtype))
expected = concat(buffer)

with tm.assert_produces_warning(None):
if transformation_func == "pct_change":
with tm.assert_produces_warning(FutureWarning, match=groupby_msg):
result = gb.transform("pct_change", *args)
else:
result = gb.transform(transformation_func, *args)

tm.assert_equal(result, expected)
Expand Down Expand Up @@ -1523,6 +1565,14 @@ def test_as_index_no_change(keys, df, groupby_func):
args = get_groupby_method_args(groupby_func, df)
gb_as_index_true = df.groupby(keys, as_index=True)
gb_as_index_false = df.groupby(keys, as_index=False)
result = gb_as_index_true.transform(groupby_func, *args)
expected = gb_as_index_false.transform(groupby_func, *args)

msg = "The default fill_method='ffill' in DataFrameGroupBy.pct_change is deprecated"
if groupby_func == "pct_change":
with tm.assert_produces_warning(FutureWarning, match=msg):
result = gb_as_index_true.transform("pct_change", *args)
with tm.assert_produces_warning(FutureWarning, match=msg):
expected = gb_as_index_false.transform("pct_change", *args)
else:
result = gb_as_index_true.transform(groupby_func, *args)
expected = gb_as_index_false.transform(groupby_func, *args)
tm.assert_equal(result, expected)

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