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DEPR: deprecate Series/DataFrame.compound #26405

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May 16, 2019
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DEPR: deprecate Series/DataFrame.compound #26405

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9a3ac10
DEPR: deprecate Series/DataFrame.compound
jorisvandenbossche May 15, 2019
19a32dd
add whatsnew
jorisvandenbossche May 16, 2019
4d40284
Merge remote-tracking branch 'upstream/master' into depr-compound
jorisvandenbossche May 16, 2019
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2 changes: 2 additions & 0 deletions doc/source/whatsnew/v0.25.0.rst
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Expand Up @@ -257,6 +257,8 @@ Deprecations

- Deprecated the ``units=M`` (months) and ``units=Y`` (year) parameters for ``units`` of :func:`pandas.to_timedelta`, :func:`pandas.Timedelta` and :func:`pandas.TimedeltaIndex` (:issue:`16344`)
- The functions :func:`pandas.to_datetime` and :func:`pandas.to_timedelta` have deprecated the ``box`` keyword. Instead, use :meth:`to_numpy` or :meth:`Timestamp.to_datetime64` or :meth:`Timedelta.to_timedelta64`. (:issue:`24416`)
- The :meth:`DataFrame.compound` and :meth:`Series.compound` methods are deprecated and will be removed in a future version.


.. _whatsnew_0250.prior_deprecations:

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7 changes: 5 additions & 2 deletions pandas/core/generic.py
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Expand Up @@ -10177,11 +10177,14 @@ def mad(self, axis=None, skipna=None, level=None):
nanops.nanstd)

@Substitution(desc="Return the compound percentage of the values for "
"the requested axis.", name1=name, name2=name2,
axis_descr=axis_descr,
"the requested axis.\n\n.. deprecated:: 0.25.0",
name1=name, name2=name2, axis_descr=axis_descr,
min_count='', see_also='', examples='')
@Appender(_num_doc)
def compound(self, axis=None, skipna=None, level=None):
msg = ("The 'compound' method is deprecated and will be"
"removed in a future version.")
warnings.warn(msg, FutureWarning, stacklevel=2)
if skipna is None:
skipna = True
return (1 + self).prod(axis=axis, skipna=skipna, level=level) - 1
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9 changes: 9 additions & 0 deletions pandas/tests/series/test_analytics.py
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Expand Up @@ -1145,6 +1145,15 @@ def test_validate_stat_keepdims(self):
with pytest.raises(ValueError, match=msg):
np.sum(s, keepdims=True)

def test_compound_deprecated(self):
s = Series([.1, .2, .3, .4])
with tm.assert_produces_warning(FutureWarning):
s.compound()

df = pd.DataFrame({'s': s})
with tm.assert_produces_warning(FutureWarning):
df.compound()


main_dtypes = [
'datetime',
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