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Support axis=None in all reductions #21597

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TomAugspurger opened this issue Jun 22, 2018 · 17 comments · Fixed by #52042
Closed

Support axis=None in all reductions #21597

TomAugspurger opened this issue Jun 22, 2018 · 17 comments · Fixed by #52042
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Enhancement Reduction Operations sum, mean, min, max, etc.
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@TomAugspurger
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#21486 is implementing support for axis=None for compatibility with NumPy 1.15's all / any.

The basic idea is to have df.op(axis=None) be the same as np.op(df, axis=None) for reductions like sum, mean, etc.

Getting there poses a backwards-compatibility challenge. Currently for some reduction functions like np.sum we interpret axis=None as

In [11]: df = pd.DataFrame({"A": [1, 2]})

In [12]: np.sum(df)
Out[12]:
A    3
dtype: int64

The best I option I see is to just warn that the behavior will change in the future, without providing a way to achieve the behavior today. Then users can update things like np.sum(df) to np.sum(df, axis=0). In a later version we'll make the actual change to interpret axis=None like NumPy.

@TomAugspurger TomAugspurger added API Design Numeric Operations Arithmetic, Comparison, and Logical operations Deprecate Functionality to remove in pandas labels Jun 22, 2018
@TomAugspurger TomAugspurger added this to the 0.24.0 milestone Jun 22, 2018
@uds5501
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uds5501 commented Jun 23, 2018

@TomAugspurger @gfyoung , I am interested in this issue and would like to help. But could you guys guide me on how to display these deprecate messages?

@gfyoung
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gfyoung commented Jun 23, 2018

@uds5501 : Perhaps this will help?

import pandas.util.testing as tm
import warnings

def f():
   warnings.warn("This is a deprecation warning", DeprecationWarning)

def test_f():
   # Might need to also pass in `check_stacklevel=False`.
   with tm.assert_produces_warning(DeprecationWarning):
      f()

@uds5501
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uds5501 commented Jun 23, 2018

@gfyoung Thanks for the help!
Now regarding this issue, will the warning in the functions like df.sum and df.mean etc : "The behavior 'df.op(axis = None)` is going to change in the future versions " suffice for this issue?

@gfyoung
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gfyoung commented Jun 23, 2018

@uds5501 : Describe (briefly) how the behavior would change in the message.

@uds5501
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uds5501 commented Jun 23, 2018

@gfyoung Alright sure, would submit a PR soon 😄

@uds5501
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uds5501 commented Jun 23, 2018

@gfyoung I had one more query regarding this. If I am not wrong, we call Dataframe.sum from generic.py at core . So, am I supposed to place this error message in the function given below

pandas/pandas/core/generic.py

Lines 9551 to 9571 in 1a23779

def _make_min_count_stat_function(cls, name, name1, name2, axis_descr, desc,
f, examples):
@Substitution(outname=name, desc=desc, name1=name1, name2=name2,
axis_descr=axis_descr, min_count=_min_count_stub,
examples=examples)
@Appender(_num_doc)
def stat_func(self, axis=None, skipna=None, level=None, numeric_only=None,
min_count=0,
**kwargs):
nv.validate_stat_func(tuple(), kwargs, fname=name)
if skipna is None:
skipna = True
if axis is None:
axis = self._stat_axis_number
if level is not None:
return self._agg_by_level(name, axis=axis, level=level,
skipna=skipna, min_count=min_count)
return self._reduce(f, name, axis=axis, skipna=skipna,
numeric_only=numeric_only, min_count=min_count)
return set_function_name(stat_func, name, cls)

or make separate files for the same like these?

import warnings
# TODO: Remove after 0.23.x
warnings.warn("'pandas.core' is private. Use 'pandas.Categorical'",
FutureWarning, stacklevel=2)
from pandas.core.arrays import Categorical # noqa
from pandas.core.dtypes.dtypes import CategoricalDtype # noqa

A little guidance would be appreciated!

@gfyoung
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gfyoung commented Jun 24, 2018

IINM, you should add it to generic.py.

cc @jreback

@TomAugspurger
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FYI @uds5501, this is a rather large change that needs discussion first. If you're interested in working on it, then by all means, but you might want to wait for feedback from other maintainers before diving into it.

@uds5501
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uds5501 commented Jun 25, 2018

@TomAugspurger Sure sir! I have not yet begun either and conclusive discussions from maintainers who have better context regarding this are always welcome!

@jreback jreback modified the milestones: 0.24.0, 0.25.0 Oct 23, 2018
@jreback jreback modified the milestones: 0.25.0, 1.0 Apr 20, 2019
@TomAugspurger TomAugspurger modified the milestones: 1.0, Contributions Welcome Dec 30, 2019
@jbrockmendel jbrockmendel added the Reduction Operations sum, mean, min, max, etc. label Sep 23, 2020
@mroeschke mroeschke added Enhancement and removed API Design Numeric Operations Arithmetic, Comparison, and Logical operations labels Jun 20, 2021
@jreback
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jreback commented Dec 28, 2021

deprecation PR is #45072

@jreback
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jreback commented Dec 28, 2021

@jbrockmendel if you can add this to the do-it-in-2.0 list

@rhshadrach
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Since the deprecation portion of this issue has been handled, I'm removing the deprecate label as it is now just an enhancement. I believe the enhancement portion still needs to be implemented.

@rhshadrach rhshadrach removed the Deprecate Functionality to remove in pandas label Apr 16, 2022
@mroeschke mroeschke removed this from the Contributions Welcome milestone Oct 13, 2022
@mroeschke
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After #50593, axis=None support is still needed for sum, prod, var, std, sem

@jbrockmendel jbrockmendel added this to the 2.0 milestone Jan 23, 2023
@mroeschke mroeschke modified the milestones: 2.0, 3.0 Feb 8, 2023
@arv-77
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arv-77 commented Mar 5, 2023

Hi @mroeschke , I would love to contribute to this issue. Can I work on implementing the remaining ops?

@jbrockmendel
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We suggest contributors start with an issue with the "good first issue" tag

@arv-77
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arv-77 commented Mar 6, 2023

Ok, I'll start with some good first issue then. Thanks!

@jbrockmendel
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It looks like the remaining reductions didn't have the axis=None behavior deprecated, so we'll need to do a deprecation cycle and do the change in 3.0

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