Add example usage to DataFrame.filter by cswarth · Pull Request #12399 · pandas-dev/pandas (original) (raw)
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Updates doc comments for DataFrame.filter and adds usage examples.
Fixed errors identified by flake8 and correctly rebase my branch before issuing PR.
DataFrame. filter(items=None, like=None, regex=None, axis=None)¶
Subset rows or columns of dataframe according to labels in the index.
Note that this routine does not filter a dataframe on its contents. The filter is applied to the labels of the index. This method is a thin veneer on top of DateFrame Select
| Parameters: | items : list-like List of info axis to restrict to (must not all be present) like : string Keep info axis where “arg in col == True” regex : string (regular expression) Keep info axis with re.search(regex, col) == True axis : int or None The axis to filter on. |
|---|---|
| Returns: | same type as input object with filtered info axis |
Notes
The items, like, and regex parameters should be mutually exclusive, but this is not checked.
axis defaults to the info axis that is used when indexing with [].
Examples
df one two three mouse 1 2 3 rabbit 4 5 6
select columns by name
df.filter(items=['one', 'three'])
one three mouse 1 3 rabbit 4 6
select columns by regular expression
df.filter(regex='e$', axis=1) one three mouse 1 3 rabbit 4 6
select rows containing 'bbi'
df.filter(like='bbi', axis=0) one two three rabbit 4 5 6
| Note that this routine does not filter a dataframe on its |
|---|
| contents. The filter is applied to the labels of the index. |
| This method is a thin veneer on top of :ref:`DateFrame Select |
| <DataFrame.select>` |
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this last sentence is not necessary.
Removed the "thin veneer" comment and added a See Also referring to pandas.DataFrame.select.
The point is to demonstrate that this routine does not filter on the contents of the dataframe, but on the index. Hopefully this will help those coming from R who might be expecting DataFrame.filter to act like dplyr::filter
Sorry for being a newbie, but update in what way? Do you want me to rebase my doc/df_filter development branch to upstream/master and push that to github? It looks like that will be push 201 commits so I want to make sure that is the right thing to do.
you need to rebase on master first
I updated my branch, but 24hrs later the CI builds are still not complete. Is that unusual or expected?
Also the CI build for python 3.5 failed but I don't see how it has anything to do with changes I created.
https://travis-ci.org/pydata/pandas/jobs/124031500
Travis was having some issues ok now
ithe 3.5 build on. numpy master is currently failing but that is ok
can you rebase / update according to comments
Current coverage is 83.76%
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As requested, added test for mutually exclusive arguments in DataFrame.filter and added unit tests for same.
| """ |
|---|
| import re |
| args = locals().copy() |
| nkw = sum(map(lambda x: operator.getitem(args,x)!=None, ['items', 'like', 'regex'])) |
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This seems a bit complicated for what we want to achieve (the locals is certainly not needed I think).
Using a similar construct: sum(map(lambda x: x is not None, [item, like, regex])) (but using a list comprehension is maybe easier to read: sum([x is not None for x in [item, like, regex]]))
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thanks, changing to,
nkw = sum([operator.getitem(args,x) is not None for x in ['items', 'like', 'regex']])
if nkw > 1:
raise TypeError("filter(): keyword arguments are mutually exclusive")
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opps, I didn't understand...now using,
nkw = sum([x is not None for x in [items, like, regex]])
Enforcing mutually exclusive arguments in frame.filter() is an incompatible change that is going to break some code, somewhere. Should this be called out in the release notes?
I would like to make a case that this API should be deprecated at this time. It adds little value over reindex and select at the expense of an API that is different than just about anything else.
| if nkw > 1: |
|---|
| raise TypeError('Keyword arguments `items`, `like`, or `regex` ' |
| 'are mutually exclusive') |
| if axis is None: |
| axis = self._info_axis_name |
| axis_name = self._get_axis_name(axis) |
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e.g. checked here
@cswarth yes pls add a whatsnew note about the mutually exclusive args.
already slated to deprecate in 0.19.0: #12401
- add sample usage
- enforce mutual exlusion of keyword arguments
- add note to what's new doc calling out API change
Labels
Related to indexing on series/frames, not to indexes themselves