DOC: correct docstring examples (#3439) by ProsperousHeart · Pull Request #16432 · pandas-dev/pandas (original) (raw)
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| 0 0.548814 0.544883 0.437587 0.383442 |
|---|
| 1 0.715189 0.423655 0.891773 0.791725 |
| 2 0.602763 0.645894 0.963663 0.528895 |
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I think you have to remove this line (even though it seems like it should be there, based on the output).
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aw man ... WTF?^^ lol
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Thanks for working on this!
| @@ -1129,8 +1134,7 @@ def get_dummies(data, prefix=None, prefix_sep='_', dummy_na=False, |
|---|
| 1 0 1 0 |
| 2 0 0 1 |
| >>> df = pd.DataFrame({'A': ['a', 'b', 'a'], 'B': ['b', 'a', 'c'], |
| 'C': [1, 2, 3]}) |
| >>> df = pd.DataFrame({'A': ['a', 'b', 'a'], 'B': ['b', 'a', 'c'], 'C': [1, 2, 3]}) |
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This will give a linting error (we check for PEP8)
The way you can solve this is by adding ... (then it should pass the doctests):
>>> df = pd.DataFrame({'A': ['a', 'b', 'a'], 'B': ['b', 'a', 'c'],
... 'C': [1, 2, 3]})
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Specifically, the lines should be less than 80 characters wide.
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aw man .... I did that to several ...any suggested way to fix it?
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like in mass? lol
| @@ -940,6 +941,7 @@ def wide_to_long(df, stubnames, i, j, sep="", suffix='\d+'): |
|---|
| 8 3 3 2.1 2.9 |
| >>> l = pd.wide_to_long(df, stubnames='ht', i=['famid', 'birth'], j='age') |
| >>> l |
| ... # doctest: +NORMALIZE_WHITESPACE |
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can you give some explanation why this is needed in this case ?
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@jorisvandenbossche I think the issue was when there's a df.index.name the output has whitespace for the rest of that line (which we don't want to include in the source)
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Aha, ...
Is that actually something we might want to solve in pandas, in the repr? (it's not a bug, but I also don't think it is a feature someone relies upon? So could change that (if it is easy) to not have to do this here) But that is certainly for another PR
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Or we could set this flag globally if this occurs a lot? (if that is possible)
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That's what @TomAugspurger was thinking, but I don't think he knows either?
| @@ -689,7 +689,7 @@ def _convert_level_number(level_num, columns): |
|---|
| new_labels = [np.arange(N).repeat(levsize)] |
| new_names = [this.index.name] # something better? |
| new_levels.append(level_vals) |
| new_levels.append(frame.columns.levels[level_num]) |
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This is an actual change in the code. Is this to fix a bug? If so, could you do this as a separate PR (and add a test for it)?
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I didn't make that change so I don't know what that is
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Since it is in your commit, you somehow made that change :-)
But if it was not the intent, you can just revert it (change it back to how it was based on the diff you see here)
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I didn't - I swear I didn't. I don't even know what that means. I'll change it back, but I promise it wasn't me.
| >>> s.unstack(level=0) |
| one two |
| a 1 2 |
| b 3 4 |
| a 1.0 3.0 |
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Ah, this was actually an error in the example!
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Oh no! So ...... how do I fix it? Cause when I try to change it, I get an error
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No, no, now it is correct! So your change is perfect. I just noticed that by running the doctests, we actually corrected some errors in the docs, which is its purpose, so that is good :-)
| two a 3 |
|---|
| b 4 |
| one a 1.0 |
| b 2.0 |
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another option would be to change the series construction, use np.arange(1, 5) instead of np.arange(1.0, 5.0).
I think using integers makes the example slightly simpler
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Agreed - working on this now.
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done - will be committing soon
1st update for issue 3439 DOC: correct docstring examples (#3439)
| X id |
|---|
| 0 0 0 |
| 1 1 1 |
| 2 2 2 |
| 2 1 2 |
| >>> pd.wide_to_long(df, ['A(quarterly)', 'B(quarterly)'], |
| i='id', j='year', sep='-') |
| X A(quarterly) B(quarterly) |
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Is it possible that the X column below is not correct? (it has no 1's)
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X is random ... which didn't make sense to me.
>>> df = pd.DataFrame({'A(quarterly)-2010': np.random.rand(3),
... 'A(quarterly)-2011': np.random.rand(3),
... 'B(quarterly)-2010': np.random.rand(3),
... 'B(quarterly)-2011': np.random.rand(3),
... 'X' : np.random.randint(3, size=3)})
>>> df['id'] = df.index
>>> df
... # doctest: +NORMALIZE_WHITESPACE
A(quarterly)-2010 A(quarterly)-2011 B(quarterly)-2010 B(quarterly)-2011 \
0 0.548814 0.544883 0.437587 0.383442
1 0.715189 0.423655 0.891773 0.791725
2 0.602763 0.645894 0.963663 0.528895
X id
0 0 0
1 1 1
2 1 2```
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You can either change X to something not random, or leave it as is(with the random seed, it is also consistent), but the output below should just match the input (which is now not the case I think)
| 1 0.634401 0.611024 0.361789 0.630976 |
|---|
| 2 0.849432 0.722443 0.228263 0.092105 |
| \ |
| ... # doctest: +NORMALIZE_WHITESPACE |
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I think it was too long then :)
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I meant
>>> df # doctest: +NORMALIZE_WHITESPACE
which would not be too long in this case
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ok - I'll add in next commit
| b 2 |
|---|
| two a 3 |
| b 4 |
| dtype: int32 |
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this one will depend on the platform you are using, so to be more robust, we should probably best add the dtype to np.arange. I would use 'int64', as this is the default in pandas (in numpy the default is platform dependent).
Or as an alternative use range(1, 5), then pandas Series will always convert this to int64
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As per our discussion, left at int32 - np.arrange and range() did not seem to make a difference so I kept it at np.arrange
What does it mean when the continuous-integration/travis-ci/py failed?
In this case it is due to some linting errors (some style issues, based on PEP8 and flake are checked in the third build on travis, which is the one that is failing. If you go to travis and click on the failing build, and scroll down, you can see why).
The output from travis:
$ ci/lint.sh
inside ci/lint.sh
Linting *.py
pandas/core/reshape/reshape.py:992:80: E501 line too long (84 > 79 characters)
pandas/core/reshape/reshape.py:993:80: E501 line too long (81 > 79 characters)
pandas/core/reshape/reshape.py:994:80: E501 line too long (81 > 79 characters)
pandas/core/reshape/reshape.py:995:80: E501 line too long (81 > 79 characters)
pandas/core/reshape/reshape.py:1000:1: W293 blank line contains whitespace
pandas/core/reshape/reshape.py:1001:80: E501 line too long (88 > 79 characters)
pandas/core/reshape/reshape.py:1015:80: E501 line too long (117 > 79 characters)
pandas/core/reshape/reshape.py:1133:71: W291 trailing whitespace
Linting *.py DONE
I don't see any way (may not have search correct) for Notepad++ and PEP8
| ... "one", "two", "two", "two", "one"], dtype=object) |
|---|
| >>> c = np.array(["dull", "dull", "shiny", "dull", "dull", "shiny", |
| ... "shiny", "dull", "shiny", "shiny", "shiny"], |
| ... dtype=object) |
| >>> crosstab(a, [b, c], rownames=['a'], colnames=['b', 'c']) |
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Can you make this pd.crosstab instead of crosstab ?
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done - will be in next commit
| >>> pd.cut(np.array([.2, 1.4, 2.5, 6.2, 9.7, 2.1]), 3, |
|---|
| labels=["good","medium","bad"]) |
| >>> result, bins = pd.cut(np.array([.2, 1.4, 2.5, 6.2, 9.7, 2.1]), |
| ... 3, labels=["good","medium","bad"]) |
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Here, you still would need
>>> result
... [output]
>>> bins
... [output]
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I'm not sure what that would look like :(
Once confirmed, pivot completed.
@ProsperousHeart Thanks a lot for working on this!
Merging this now (follow-up PRs to do further improvements are always welcome!)
The appveyor failure is the matplotlib one, so ignoring that one.
There is one failing doctest, but that seems a python version issue (get different results when testing that locally as well on different python version). Will do another PR to check if changing doc build to py 3.6 solves things.
Kiv pushed a commit to Kiv/pandas that referenced this pull request
stangirala pushed a commit to stangirala/pandas that referenced this pull request
