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DOC: update the pandas.DataFrame.clip_lower docstring #20289

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Jul 8, 2018
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DOC: update the pandas.DataFrame.clip_lower docstring #20289

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DOC: update the pandas.DataFrame.clip_lower docstring
adatasetaday Mar 11, 2018
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DOC: update the pandas.DataFrame.clip_lower docstring
adatasetaday Mar 12, 2018
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DOC: update the pandas.DataFrame.clip_lower docstring
adatasetaday Mar 12, 2018
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DOC: update the pandas.DataFrame.clip_lower docstring
adatasetaday Mar 13, 2018
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DOC: update the pandas.DataFrame.clip_lower docstring
adatasetaday Mar 13, 2018
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Merge remote-tracking branch 'upstream/master' into adatasetaday-docs…
jorisvandenbossche Jul 8, 2018
e48d49b
fixup
jorisvandenbossche Jul 8, 2018
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69 changes: 60 additions & 9 deletions pandas/core/generic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5716,24 +5716,75 @@ def clip_upper(self, threshold, axis=None, inplace=False):

def clip_lower(self, threshold, axis=None, inplace=False):
"""
Return copy of the input with values below given value(s) truncated.
Trim the caller's values below a given `threshold`.

Elements below the `threshold` will be changed to match the
`threshold` value(s).

Parameters
----------
threshold : float or array_like
axis : int or string axis name, optional
threshold : float or array-like
Lower value(s) to which the input value(s) will be trimmed.
axis : {0 or 'index', 1 or 'columns', None}, default None
Align object with threshold along the given axis.
inplace : boolean, default False
Whether to perform the operation in place on the data
.. versionadded:: 0.21.0
Whether to perform the operation in place on the data.

See Also
--------
clip
.. versionadded:: 0.21.0

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Sorry if I forgot some discussion about it, but don't we want a See Also section? I think clip and clip_upper should be listed.

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Yes good spot we definitely still want this - @adatasetaday can you add back in?

I know we had some back and forth about Series.clip_lower being self-referential with the shared doc system. If you find that confusing just remove that one entry, but all the rest should remain

Returns
-------
clipped : same type as input
Series or DataFrame
Same type as caller.
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For this method may be it's a bit obvious, but for consistency I'd say in the description what this method returns (e.g. Original data with values trimmed). The note about the time is all right (not sure if other methods have it as part of the type or the description).

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Would any of these work?

Series or DataFrame (same type as caller)
Original data with values trimmed.

Series or DataFrame
Original data (in same type as caller) with values trimmed .

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They look great. If you want to take a look at the latest merged pull requests, I think this happens in few, and may be there is a way more standard than another. If you don't find any, from my side you can choose whatever you want.

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Based on what I see in the code, this seems to be the most common format

type of caller
Original data with values trimmed.

I was thinking that there would be some value in creating PRs for standarizing these kind of things. For example, do one that fixes the axis parameters in ALL methods to match the format agreed in the discussions in this sprint. Another one could be done to make sure there is no period after the versionadded (which a lot of them have it, probably due to the validating script complaining if it was not there). Would this be a good idea? Who should I contact if I want to take care of some of these?

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Feel free to do it. I'd probably wait until most of the PRs from the sprint are closed, to avoid conflicts. And more than contacting someone, you can create an issue (or one per change) with what you're planning to do, you can get some discussion and feedback before doing all the work.


Examples
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Nice job here - I think the examples are very clear

--------
>>> df = pd.DataFrame({'a': [0.740518, 0.450228, 0.710404, -0.771225],
... 'b': [0.040507, -0.45121, 0.760925, 0.010624]})
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Personally I find the data used in #20212 easier to understand. It requires a decent amount of concentration to see what the examples are doing with so many decimal numbers.


>>> df
a b
0 0.740518 0.040507
1 0.450228 -0.451210
2 0.710404 0.760925
3 -0.771225 0.010624

Clip to a scalar value

>>> df.clip_lower(0.2)
a b
0 0.740518 0.200000
1 0.450228 0.200000
2 0.710404 0.760925
3 0.200000 0.200000

Clip to an array along the index axis

>>> df.clip_lower([0.2, 0.4, 0.6, 0.8], axis=0)
a b
0 0.740518 0.200000
1 0.450228 0.400000
2 0.710404 0.760925
3 0.800000 0.800000

Clip to an array along the column axis

>>> df.clip_lower([0.5, 0.0], axis=1)
a b
0 0.740518 0.040507
1 0.500000 0.000000
2 0.710404 0.760925
3 0.500000 0.010624

Clip in place

>>> df.clip_lower(0.2, inplace=True)
>>> df
a b
0 0.740518 0.200000
1 0.450228 0.200000
2 0.710404 0.760925
3 0.200000 0.200000
"""
return self._clip_with_one_bound(threshold, method=self.ge,
axis=axis, inplace=inplace)
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