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https://api.github.com/repos/pandas-dev/pandas/issues/5201 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5201/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5201/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5201/events | https://github.com/pandas-dev/pandas/pull/5201 | 20,918,689 | MDExOlB1bGxSZXF1ZXN0OTA1MDIzNQ== | 5,201 | BUG/ENH: Index constructor with dtype now delegates | {
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slightly too, which is a nice side bonus. Will even better after Index
refactor.
Fixes #5196.
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https://api.github.com/repos/pandas-dev/pandas/issues/5202 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5202/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5202/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5202/events | https://github.com/pandas-dev/pandas/issues/5202 | 20,918,891 | MDU6SXNzdWUyMDkxODg5MQ== | 5,202 | ENH: Period ops NaT & timedelta ops | {
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... | 4 | 2013-10-12T23:09:40Z | 2018-10-25T03:25:41Z | 2018-10-25T03:25:41Z | CONTRIBUTOR | null | see related https://github.com/pydata/pandas/issues/5200, #4551, #4056
seem that a direct subtraction of PeriodIndexes would accomplish this,
but don't seem to support those types of ops...
This is currently an intersection (with a '-'), but want to do a timedelta like op
```
In [40]: pd.PeriodIndex(start='20130101'... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5203 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5203/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5203/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5203/events | https://github.com/pandas-dev/pandas/issues/5203 | 20,919,296 | MDU6SXNzdWUyMDkxOTI5Ng== | 5,203 | BUG: period on weekends rolling to odd business days | {
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looks like a bug (though it might just be ambiguous/undefined behavior).
```
In [11]: pd.Period('2013-10-4', freq='B')
Out[11]: Period('2013-10-04', 'B')
In [12]: pd.Period('2013-10-5', freq='B')
Out[12]: Period('2013-10-07', 'B')
In [13]: pd.Pe... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5204 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5204/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5204/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5204/events | https://github.com/pandas-dev/pandas/pull/5204 | 20,923,392 | MDExOlB1bGxSZXF1ZXN0OTA1MjE5NA== | 5,204 | improved daytimes conversion performance in period.c | {
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"followers_url": "https://api.github.com/users/wesm... | 1 | 2013-10-13T08:14:17Z | 2014-01-12T07:38:07Z | 2013-10-13T23:31:31Z | CONTRIBUTOR | null | Especially when using repeated conversion with period_asfreq_arr of tslib the code introduced with #3060 was about two to three times slower than before.
This PR improves the performance issues by moving global calculations out of the loop.
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- change methods which directly pass metadata to use **finalize**
These provide a simple mechanism for meta data propagation, which
can be overriden in subclasses if desired. Currently these only do non-ambiguous
propagation.
makes #60, #2485 easier
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This does not work as we are using a rhs of a series which is not broadcast
to the assignment
```
df.loc[df['A'],['A','B']] = df['C']
```
This works, but a tad cumbersome
``... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5207 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5207/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5207/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5207/events | https://github.com/pandas-dev/pandas/pull/5207 | 20,930,632 | MDExOlB1bGxSZXF1ZXN0OTA1NDk0MQ== | 5,207 | DOC: Note -> Notes (numpydoc docstring section) | {
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So I searched for all occurences and adjusted them.
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https://api.github.com/repos/pandas-dev/pandas/issues/5208 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5208/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5208/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5208/events | https://github.com/pandas-dev/pandas/pull/5208 | 20,931,216 | MDExOlB1bGxSZXF1ZXN0OTA1NTIwOQ== | 5,208 | DOC: make api docs reflect api usage (#4539) | {
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This removes all use of `.. currentmodule:: pandas.some.submodule` (in favor of `.. currentmodule:: pandas`) in api.rst. Rationale is that docs should reflect the user api usage.
Only exception are `pandas.io.sql.read_frame/write_frame` and `pandas.io.stata.StataReader` methods, because they are not ava... | {
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cases). Fixes #4794.
Changed an assert_almost_equal to assert_series_equal to better reflect
actual return value.
Also makes set_levels, set_labels and set_names match behavior of rename to _not_ return self if inplace.
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https://api.github.com/repos/pandas-dev/pandas/issues/5210 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5210/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5210/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5210/events | https://github.com/pandas-dev/pandas/pull/5210 | 20,935,047 | MDExOlB1bGxSZXF1ZXN0OTA1Njc0NA== | 5,210 | BUG: Bug in loc setting with multiple indexers and a rhs of a Series that needs broadcasting (GH5206) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5211 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5211/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5211/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5211/events | https://github.com/pandas-dev/pandas/pull/5211 | 20,935,078 | MDExOlB1bGxSZXF1ZXN0OTA1Njc1Mw== | 5,211 | ENH: Add usecols option to python parser. | {
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This ticket felt a little bit like whack-a-mole.
The key is that names can have two meanings: if it matches length of usecols then it is the name to apply to the (numeric) usecols. If it matches the length of the original columns, it is the set of column names and string values in usecols refer to it.
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https://api.github.com/repos/pandas-dev/pandas/issues/5212 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5212/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5212/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5212/events | https://github.com/pandas-dev/pandas/issues/5212 | 20,937,086 | MDU6SXNzdWUyMDkzNzA4Ng== | 5,212 | Validate that MultiIndex labels are Int64 type when not called internally. | {
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... | 2 | 2013-10-14T01:44:30Z | 2021-04-11T03:43:45Z | 2021-04-11T03:43:44Z | CONTRIBUTOR | null | Right now you could create MI with weird types and it doesn't error out. More difficult to do effectively when MI is an ndarray subclass (because there are so many different ways to instantiate a MultiIndex). Will fix in Index refactor (just want to remember to do so).
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https://api.github.com/repos/pandas-dev/pandas/issues/5213 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5213/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5213/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5213/events | https://github.com/pandas-dev/pandas/issues/5213 | 20,937,158 | MDU6SXNzdWUyMDkzNzE1OA== | 5,213 | MultiIndex needs to validate that levels and labels are compatible. | {
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```
n [1]: import pandas as pd
In [2]: mi = pd.MultiIndex(labels = [[1.25, 0.25, 3.1], [3.2, 1.2, 4.1]], levels=[['a'], ['a', 'b', 'c']])
In [3]: mi
Out[3]:
MultiIndex(levels=[[u'a'], [u'a', u'b', u'c']],
labels=[[1, 0, 3], [3, 1, 4]])
In [4]: mi.values
----------------------------------------------... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5214 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5214/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5214/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5214/events | https://github.com/pandas-dev/pandas/pull/5214 | 20,937,719 | MDExOlB1bGxSZXF1ZXN0OTA1NzkwNQ== | 5,214 | BUG/CLN: MI now checks level & label compatibility | {
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it ought not to be.
Fixes #5213.
Clearly this adds a (likely small) perf hit - but should only occur
from external MI calls that specifically call the constructor with
levels and labels (for ex... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5215 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5215/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5215/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5215/events | https://github.com/pandas-dev/pandas/pull/5215 | 20,939,083 | MDExOlB1bGxSZXF1ZXN0OTA1ODU2Nw== | 5,215 | BUG/CLN: Clear _tuples on setting MI levels/labels | {
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that it would return wrong values. (and this was ocurring in v0.12 and
earlier too).
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``` python
import numpy as np
import pandas as pd
print('pandas : %s' % pd.__version__)
print('numpy : %s' % np.__version__)
a = np.random.rand(10, 3)
df = pd.DataFrame(a, columns=['x', 'y', 'z'])
tuples = [(i,... | {
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When adding `Timestamp` in api.rst to document this class and its methods (as eg done in this commit https://github.com/jorisvandenbossche/pandas/commit/3a8a41dda11d47d337e3f916567e8af2772598c2), you get warnings when building the docs like for example:
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WARNING: error while f... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5219 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5219/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5219/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5219/events | https://github.com/pandas-dev/pandas/pull/5219 | 20,976,948 | MDExOlB1bGxSZXF1ZXN0OTA3ODU4NA== | 5,219 | TST/PERF: Re-write assert_almost_equal() in cython #4398 | {
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"followers_url": "https://api.github.com/users/wesm... | 24 | 2013-10-14T19:34:42Z | 2014-06-19T14:48:35Z | 2013-10-21T21:35:44Z | CONTRIBUTOR | null | closes #4398
Add a testing.pyx cython file, and port assert_almost_equal() from
python to cython. This also fixes a few minor bugs that were in the
python version of assert_almost_equal() and adds more test cases to
test_tests.py
On my machine this brings a modest gain to the suite of "not slow" tests
(160s -> 140s)... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5220 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5220/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5220/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5220/events | https://github.com/pandas-dev/pandas/pull/5220 | 20,977,662 | MDExOlB1bGxSZXF1ZXN0OTA3ODk5NA== | 5,220 | fix business day calculation | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2013-10-14T19:48:51Z | 2014-06-22T14:38:02Z | 2013-10-15T13:28:59Z | CONTRIBUTOR | null | This will fix the so far broken calculation of business day periods and the corresponding tests reported
closes #5203.
The expected behaviour found in the present tests is that the date is always rolling forward to the next business day:
```
Friday: Period('2012-3-09', freq='B') => '2012-03-09'
Saturday: Period('2... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5221 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5221/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5221/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5221/events | https://github.com/pandas-dev/pandas/issues/5221 | 20,977,929 | MDU6SXNzdWUyMDk3NzkyOQ== | 5,221 | DOC: use Sphinx extension directly from numpy/ipython instead of maintaining our own version | {
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"labels_url": "htt... | 20 | 2013-10-14T19:53:53Z | 2014-02-24T12:56:13Z | 2014-02-24T12:56:13Z | MEMBER | null | Summary: proposal to not maintain our own version of Sphinx extension in pandas repo but instead use the extensions directly from the project it maintains.
The pandas docs are using some Sphinx extensions that are not included in Sphinx itself: `numpydoc` and ipythons `ipython_directive` and `ipython_console_highlight... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5222 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5222/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5222/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5222/events | https://github.com/pandas-dev/pandas/pull/5222 | 20,978,600 | MDExOlB1bGxSZXF1ZXN0OTA3OTUwMg== | 5,222 | BUG: Groupby filter maintains ordering, closes #4621 | {
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Includes tests for SeriesGroupBy and DataFrameGroupBy, using indexes that are sequentially increasing, sequentially decreasing, and shuffled. Also, this PR removes all ad hoc sorting involved in the original filter tests -- now no longer needed. Much better!
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https://api.github.com/repos/pandas-dev/pandas/issues/5223 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5223/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5223/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5223/events | https://github.com/pandas-dev/pandas/issues/5223 | 20,979,100 | MDU6SXNzdWUyMDk3OTEwMA== | 5,223 | Slicing using .loc fails when either boundary falls outside the index | {
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```
>>> s = pd.Series(np.arange(10))
>>> s.loc[:15]
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-37-e6f70b3a4e46> in <module>()
-... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5224 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5224/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5224/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5224/events | https://github.com/pandas-dev/pandas/pull/5224 | 20,982,597 | MDExOlB1bGxSZXF1ZXN0OTA4MTg1NA== | 5,224 | Redefine match | {
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How does this look? If the docstring and the tests reflect our consensus, I'll take a stab at the docs. This is the gist of it:
Default behavior is unchanged, but issues a warning.
```
In [1]: Series(['aa', 'bb']).str.match('(a)(a)')
pandas/core/strings.py:333: UserWarning: This usage of match will be r... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5225 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5225/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5225/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5225/events | https://github.com/pandas-dev/pandas/issues/5225 | 20,983,448 | MDU6SXNzdWUyMDk4MzQ0OA== | 5,225 | BUG: MI needs to invalidate all of its cached properties when levels or labels are set. | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2013-10-14T21:39:58Z | 2013-10-16T22:32:15Z | 2013-10-16T22:32:15Z | CONTRIBUTOR | null | Whack-a-mole! @jreback is there some kind of standardized method for resetting the `_cache` attribute? I was thinking we could add a `_reset_cache` method to `PandasObject` that resets the attribute (so we only have to change it in one or two places).
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https://api.github.com/repos/pandas-dev/pandas/issues/5226 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5226/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5226/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5226/events | https://github.com/pandas-dev/pandas/issues/5226 | 20,992,677 | MDU6SXNzdWUyMDk5MjY3Nw== | 5,226 | New appending behavior doesn't work on an empty DataFrame | {
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"followers_url": "https://api.github.com/users/wesm... | 1 | 2013-10-15T01:54:31Z | 2013-10-23T14:51:25Z | 2013-10-15T13:11:40Z | CONTRIBUTOR | null | Consider this working example from the docs:
```
In [9]: df1 = DataFrame(np.arange(6).reshape(3,2),
...: columns=['A','B'])
In [10]: df1.loc[3] = [6, 7]
In [11]: df1
Out[11]:
A B
0 0 1
1 2 3
2 4 5
3 6 7
```
And now watch what happens when the DataFrame is empty:
```
In [12]: df2 = D... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5228 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5228/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5228/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5228/events | https://github.com/pandas-dev/pandas/issues/5228 | 20,995,480 | MDU6SXNzdWUyMDk5NTQ4MA== | 5,228 | ERROR: Failure: ImportError (No module named pandas) | {
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```
cannot import name hashtable
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "pandas/__init__.py", line 9, in <module>
from . import hashtable, tslib, lib
ImportError: cannot import name hashtable
nosetests --exe -w /tmp... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5229 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5229/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5229/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5229/events | https://github.com/pandas-dev/pandas/issues/5229 | 21,003,354 | MDU6SXNzdWUyMTAwMzM1NA== | 5,229 | Yahoo finance data fails on market cap | {
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"followers_url": "https://api.github.com/users/jre... | 4 | 2013-10-15T08:43:21Z | 2014-11-07T11:48:09Z | 2014-11-07T11:48:09Z | CONTRIBUTOR | null | Market cap returns a "B" etc. that needs to be parsed before the result is coerced into a DataFrame.
https://groups.google.com/forum/#!topic/pydata/KOdYtiw7cE8
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https://api.github.com/repos/pandas-dev/pandas/issues/5230 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5230/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5230/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5230/events | https://github.com/pandas-dev/pandas/issues/5230 | 21,028,844 | MDU6SXNzdWUyMTAyODg0NA== | 5,230 | Series.diff incorrect values with uint64 | {
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"color": "009... | closed | false | null | [] | null | 3 | 2013-10-15T16:45:01Z | 2013-10-15T19:03:37Z | 2013-10-15T16:58:51Z | NONE | null | Series.diff appears to get things off with unsigned ints
``` python
s=pd.Series([1, 2, 3, 4, 5, 6], dtype='uint')
print s
print s.shift(-1)
print s.diff(-1) # this result is wrong, some conversion issues
print s.map(int)
print s.map(int).diff(-1) # this result is right
0 1
1 2
2 3
3 4
4 5
5 6
dt... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5231 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5231/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5231/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5231/events | https://github.com/pandas-dev/pandas/pull/5231 | 21,030,591 | MDExOlB1bGxSZXF1ZXN0OTEwODI2MQ== | 5,231 | EHN/FIX: Add na_last parameter to DataFrame.sort. Fixes GH3917 | {
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This is an attempt to fix the Nested Sort with NaN bug (https://github.com/pydata/pandas/issues/3917).
I've added tests to `test_frame.py` and `test_hashtable.py` to demonstrate the problem.
`hashtable.Factorizer.factorize` has been modified to map `nan` to `na_sentinel`. Before it was mapping `nan` to... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5232 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5232/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5232/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5232/events | https://github.com/pandas-dev/pandas/issues/5232 | 21,030,673 | MDU6SXNzdWUyMTAzMDY3Mw== | 5,232 | read_csv dtype argument not working when there is a footer | {
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... | 12 | 2013-10-15T17:16:46Z | 2016-08-02T09:56:06Z | 2016-08-02T09:56:06Z | NONE | null | xref #7141
## Datafile test.csv
col1|col2
a|438087272980
b|399432587827
c|592706116147
d|1584843561523
footer 1
## Command
print pd.read_csv('test.csv', sep='|', skipfooter=1, dtype={'col2':'object'}).dtypes
## Output
col1 object
col2 int64
dtype: object
## Expected Output
col1 object
col2 object
dtype... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5233 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5233/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5233/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5233/events | https://github.com/pandas-dev/pandas/issues/5233 | 21,039,658 | MDU6SXNzdWUyMTAzOTY1OA== | 5,233 | BUG: OLS.predict() fails when given a Series | {
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"followers_url": "https://api.github.com/users/wesm... | 1 | 2013-10-15T19:44:55Z | 2013-10-17T13:07:34Z | 2013-10-17T13:07:34Z | CONTRIBUTOR | null | OLS.predict() makes a call to dropna() with an argument when Series has no such argument. I believe the fix here is to just move the DataFrame creation above the "if fill_value" clause.
```
orig_x = x
if fill_value is None and fill_method is None:
x = x.dropna(how='any')
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https://api.github.com/repos/pandas-dev/pandas/issues/5234 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5234/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5234/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5234/events | https://github.com/pandas-dev/pandas/pull/5234 | 21,041,342 | MDExOlB1bGxSZXF1ZXN0OTExNDQ3Mw== | 5,234 | FIX: OLS.predict() - cast input to DataFrame from Series before performing operations | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5235 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5235/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5235/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5235/events | https://github.com/pandas-dev/pandas/issues/5235 | 21,048,558 | MDU6SXNzdWUyMTA0ODU1OA== | 5,235 | Issue with Excel writers when column names are duplicated | {
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"followers_url": "https://api.github.com/users/wesm... | 7 | 2013-10-15T22:19:45Z | 2013-11-04T01:38:29Z | 2013-10-16T18:50:39Z | CONTRIBUTOR | null | There appears to be an issue with Excel writers when DataFrame column names are duplicated. This issue that was initially reported on [StackOverflow](http://stackoverflow.com/questions/19363779/problems-writing-to-file-in-pandas).
For example consider the following program:
``` python
import pandas as pd
from pandas... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5236 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5236/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5236/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5236/events | https://github.com/pandas-dev/pandas/issues/5236 | 21,049,195 | MDU6SXNzdWUyMTA0OTE5NQ== | 5,236 | Add cache resetting method to PandasObject | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5238 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5238/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5238/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5238/events | https://github.com/pandas-dev/pandas/pull/5238 | 21,054,652 | MDExOlB1bGxSZXF1ZXN0OTEyMjM5OA== | 5,238 | CLN: Add _reset_cache method to PandasObject | {
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friends. I think there are other objects that use `cache_readonly` that
might want to reset too.
I also moved the local dir methods off of StringMixin to PandasObject
(where they ought to have been).
Fixes #5236 and fixes #5225.
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https://api.github.com/repos/pandas-dev/pandas/issues/5239 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5239/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5239/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5239/events | https://github.com/pandas-dev/pandas/issues/5239 | 21,056,790 | MDU6SXNzdWUyMTA1Njc5MA== | 5,239 | na_filter=False ignored when index_col set | {
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"default": false,
"description": "np.nan, pd.NaT, pd.NA, d... | closed | false | null | [] | {
"closed_at": "2017-12-13T13:05:41Z",
"closed_issues": 160,
"created_at": "2017-10-02T10:21:48Z",
"creator": {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2013-10-16T02:24:42Z | 2017-11-06T20:33:44Z | 2017-11-06T20:33:44Z | CONTRIBUTOR | null | Given the following CSV file:
```
u1,u2,u3,d1,d2,d3,d4
Good Things,C,,1,1,1,1
Good Things,R,,1,1,1,1
Bad Things,C,,1,1,1,1
Bad Things,T,,1,1,1,1
Okay Things,N,B,1,1,1,1
Okay Things,N,D,1,1,1,1
Okay Things,B,,1,1,1,1
Okay Things,D,,1,1,1,1
```
First I parse with `na_filter=True`:
```
In [13]: pd.read_csv("/home/alex/... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5240 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5240/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5240/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5240/events | https://github.com/pandas-dev/pandas/pull/5240 | 21,057,243 | MDExOlB1bGxSZXF1ZXN0OTEyMzcyNg== | 5,240 | CLN/ENH: Make names getattr'able in core/ops +PEP8. | {
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NDFrame (previously you had things like `or_ [|]`. better to just have them
all be named exactly what they are s.t. subclasses can do
`getattr(super(self, MyClass), name)(*args, **kwargs)`.
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https://api.github.com/repos/pandas-dev/pandas/issues/5241 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5241/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5241/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5241/events | https://github.com/pandas-dev/pandas/pull/5241 | 21,063,526 | MDExOlB1bGxSZXF1ZXN0OTEyNjg5Nw== | 5,241 | DOC: fix building of gbq docs | {
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And in the same time I corrected some minor numpydoc docstring things.
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https://api.github.com/repos/pandas-dev/pandas/issues/5242 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5242/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5242/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5242/events | https://github.com/pandas-dev/pandas/pull/5242 | 21,075,665 | MDExOlB1bGxSZXF1ZXN0OTEzMzQzNg== | 5,242 | Fixed assertion error message | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5243 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5243/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5243/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5243/events | https://github.com/pandas-dev/pandas/pull/5243 | 21,099,782 | MDExOlB1bGxSZXF1ZXN0OTE0NzA4MQ== | 5,243 | API: add excel kw to to_clipboard to preserve compat behavior (related GH5070) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5244 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5244/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5244/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5244/events | https://github.com/pandas-dev/pandas/pull/5244 | 21,112,490 | MDExOlB1bGxSZXF1ZXN0OTE1Mzk5Mg== | 5,244 | API/CLN: consolidate truncate into NDFrame (panel had a separate method) | {
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(related #5242)
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https://api.github.com/repos/pandas-dev/pandas/issues/5245 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5245/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5245/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5245/events | https://github.com/pandas-dev/pandas/pull/5245 | 21,116,498 | MDExOlB1bGxSZXF1ZXN0OTE1NjIxMQ== | 5,245 | Make doc compiling under windows workable | {
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and encoded umlauts in code (see links in
https://github.com/pydata/pandas/issues/5142).
The workaround is to replace the offending text with one which does not fail
(but which makes the example a bit pointless), build the docs and restore the
old tex... | {
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``` python
df = pd.DataFrame(zip(range(10), range(10)))
df._data = 5
df + 2 # Maximum recursion depth error.
```
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https://api.github.com/repos/pandas-dev/pandas/issues/5248 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5248/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5248/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5248/events | https://github.com/pandas-dev/pandas/issues/5248 | 21,142,694 | MDU6SXNzdWUyMTE0MjY5NA== | 5,248 | Series.drop regression and unexpected behaviour | {
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```
>>> s = pandas.Series([1,1,2],index=["one","one","two"])
>>> s.drop(["one"])
two 2
dtype: int64
```
but a singleton silently fails:
```
>>> s.drop("one")
one 1
one 1
two 2
dtype: int64
```
except when index is unique:
```
>>> s = pandas.Series([1,2],index=["one","two"])
>... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5250 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5250/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5250/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5250/events | https://github.com/pandas-dev/pandas/issues/5250 | 21,148,574 | MDU6SXNzdWUyMTE0ODU3NA== | 5,250 | ENH: Unify API for drop and dropna for NDFrame | {
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"followers_url": "https://api.github.com/users/wesm... | 3 | 2013-10-17T12:12:08Z | 2013-10-17T13:07:34Z | 2013-10-17T13:07:34Z | CONTRIBUTOR | null | This can at least be done for Series and DataFrame (for dropna, thresh and how would just have no effect and axis must always be 0). Need to see whether it's possible for Panel.
cf the recent issue with OLS.predict and issues with how. #5233
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closes #5234
closes #5250
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@jmcnamara if you have any tips they'd certainly be appreciated - I may only do it for Xlsxw... | {
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"followers_url": "https://api.github.com/users/wesm... | 4 | 2013-10-17T22:17:00Z | 2013-10-21T18:00:29Z | 2013-10-21T18:00:29Z | CONTRIBUTOR | null | This is a placeholder for a commit I'm working on to resolve a recently introduced API bug with `pandas.io.gbq`. Basically, the module fails to handle result pagination properly, so result sets are limied to 10k rows. When #4140 was pulled, we were told by Google that this would be a backend fix that would not require ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5256 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5256/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5256/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5256/events | https://github.com/pandas-dev/pandas/issues/5256 | 21,191,260 | MDU6SXNzdWUyMTE5MTI2MA== | 5,256 | use of iloc with heterogeneous DataFrame coerces dtype? | {
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The `iloc` method seems to coerce dtype of values in some cases. For example:
```
x5 = pd.DataFrame(index=['A','B','C'],columns=['foo','bar','baz'])
x5.foo = np.int16([-1,-2,-3])
x5.bar = np.uint16([1,2,3])
x5.baz = np.uint32([100000,200000,300000])
pr... | {
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Rows:
```
In [5]: pd.DataFrame({"A":[1,2],"B":[20,40]}).loc[[1]]
Out[5]:
A B
1 2 40
In [6]: pd.DataFrame({"A":[1,2],"B":[20,40]}).loc[[False, True]]
Out[6]:
A B
1 2 40
```
and these work for columns:
```
In [7]: pd.DataFrame({"A":[1,2],"B":[20,40]})[["B"]]
Out[7]:
B
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https://api.github.com/repos/pandas-dev/pandas/issues/5259 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5259/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5259/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5259/events | https://github.com/pandas-dev/pandas/issues/5259 | 21,207,823 | MDU6SXNzdWUyMTIwNzgyMw== | 5,259 | DOC: docs on website not building | {
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I don't exactly know how it is arranged, but are they supposed to build daily?
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https://api.github.com/repos/pandas-dev/pandas/issues/5260 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5260/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5260/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5260/events | https://github.com/pandas-dev/pandas/issues/5260 | 21,235,033 | MDU6SXNzdWUyMTIzNTAzMw== | 5,260 | DataFrame.groupby() causes loss of precision on large integer values | {
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``` python
In [298]: g
Out[298]:
ts level
33 1382016600011617669 32
34 1382016600011625872 32
44 1382016600013590377 43
45 1382016600013598606 43
```
Running groupby() causes my 'ts' value to change and causes some loss of preci... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5261 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5261/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5261/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5261/events | https://github.com/pandas-dev/pandas/issues/5261 | 21,252,795 | MDU6SXNzdWUyMTI1Mjc5NQ== | 5,261 | Support for numpy strings | {
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"f... | 10 | 2013-10-19T00:25:06Z | 2020-08-06T18:01:55Z | 2020-08-06T18:01:54Z | CONTRIBUTOR | null | This is more of a question than an issue:
why does Pandas use object type rather than the native fixed length numpy strings?
For example:
```
In [24]: np.array(["foo", "baz"])
Out[24]:
array(['foo', 'baz'],
dtype='|S3')
```
but:
```
In [29]: pd.DataFrame({"a":np.array(["foo", "baz"])}).dtypes
Out[29]:
a ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5262 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5262/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5262/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5262/events | https://github.com/pandas-dev/pandas/pull/5262 | 21,253,862 | MDExOlB1bGxSZXF1ZXN0OTIyODIyNA== | 5,262 | BUG: Pagination in pandas.io.gbq | {
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"followers_url": "https://api.github.com/users/wesm... | 12 | 2013-10-19T01:16:07Z | 2014-07-16T08:35:55Z | 2013-10-21T18:00:12Z | CONTRIBUTOR | null | In light of some last minute API changes in Google BigQuery, I have updated our code to function properly. In particular, this fixes a known bug that limited result sets to 10,000. Hopefully we'll have an entirely new version soon that will make better use of Google's reference code and thus be more future proof. Note ... | {
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... | 4 | 2013-10-19T09:42:14Z | 2017-07-09T02:32:37Z | 2017-07-09T02:32:37Z | NONE | null | related #4264
The normal matplotlib boxplot command in Python returns a dictionary with keys for the boxes, median, whiskers, fliers, and caps. This makes styling really easy. Pandas.groupby boxplots, however, return an AxesSubplot object. This makes styling the plots more difficult.
I posted this question recently o... | {
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_Update from @hayd I think these should reference `_selected_obj` rather than `obj`._
Looking through some others, looks these also ignore the selection
- [x] count #6570
- [x] corr #6570
- [x] cummax #6570
- [x] cummin #6570
- [x] cumsum #6570
- [x] cumprod #6570
- [x] describe #6570
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https://api.github.com/repos/pandas-dev/pandas/issues/5267 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5267/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5267/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5267/events | https://github.com/pandas-dev/pandas/issues/5267 | 21,266,946 | MDU6SXNzdWUyMTI2Njk0Ng== | 5,267 | BUG: groupby get_group should be more datelike friendly | {
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"labels_url": "htt... | 0 | 2013-10-19T18:51:04Z | 2014-04-21T12:22:23Z | 2014-04-11T22:33:18Z | CONTRIBUTOR | null | http://stackoverflow.com/questions/19458361/python-pandas-groupby-date-and-accessing-each-group-by-timestamp
```
In [2]: df= pd.DataFrame({'DATE' : ['10-Oct-2013', '10-Oct-2013', '10-Oct-2013', '11-Oct-2013', '11-Oct-2013', '11-Oct-2013'],'VAL' : [1,2,3,4,5,6]})
In [3]: df['DATE'] = pd.to_datetime(df['DATE'])
In [4]... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5268 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5268/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5268/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5268/events | https://github.com/pandas-dev/pandas/pull/5268 | 21,268,107 | MDExOlB1bGxSZXF1ZXN0OTIzMzg0Ng== | 5,268 | BUG: Fixed issue #5156: segfault on read_csv | {
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Our c parser was not checking array bounds.
Example:
```
In [1]: from StringIO import StringIO; import pandas as pd
In [2]: data = """\
1,2,3
4,,6
7,8,9
10,11,12\n"""
In [3]: df = pd.read_csv(StringIO(data), header=0, names=['a', 'b', 'c', 'd'], engin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5269 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5269/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5269/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5269/events | https://github.com/pandas-dev/pandas/issues/5269 | 21,268,966 | MDU6SXNzdWUyMTI2ODk2Ng== | 5,269 | Fix unhelpful "length mismatch" error message on set_axis | {
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```
>>> df = DataFrame({0:[1,2,3], 1:[1,2,3]})
>>> df.columns = df.columns = ['a', 'b', 'c']
Exception: Length mismatch (3 vs 2)
```
When the lists were bigger, I had... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5270 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5270/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5270/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5270/events | https://github.com/pandas-dev/pandas/pull/5270 | 21,269,022 | MDExOlB1bGxSZXF1ZXN0OTIzNDI2Nw== | 5,270 | CLN: Fix unhelpful "length mismatch" error message on set_axis | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5271 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5271/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5271/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5271/events | https://github.com/pandas-dev/pandas/pull/5271 | 21,270,476 | MDExOlB1bGxSZXF1ZXN0OTIzNDg5MA== | 5,271 | Added handling for v3 advanced segment ids which aren't just ints as of July 15th | {
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"followers_url": "https://api.github.com/users/wesm... | 21 | 2013-10-19T23:02:49Z | 2014-06-14T07:09:34Z | 2013-10-22T04:06:16Z | CONTRIBUTOR | null | The old int based advanced segment ids are deprecated. The new segment ids are alphanumeric. I know from experimentation that their form includes alphanumeric and alphanumeric+hyphen. Updated code for both
cases. Reference: https://developers.google.com/analytics/devguides/reporting/core/v3/changelog
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https://api.github.com/repos/pandas-dev/pandas/issues/5272 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5272/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5272/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5272/events | https://github.com/pandas-dev/pandas/issues/5272 | 21,270,829 | MDU6SXNzdWUyMTI3MDgyOQ== | 5,272 | BUG: Selecting a column from a data frame sometimes returns a series and sometimes returns a data frame | {
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In [3]: pandas.version.version
Out[3]: '0.12.0'
## Code to reproduce:
``` python
import collections
import pandas as pd
import numpy as np
cols = map(str, np.unique(np.random.randint(0, 1000000, 200)))
index = map(str, np.unique(np.random.randint(0, 1000000, 5000)))
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"labels_url": "htt... | 4 | 2013-10-20T00:54:23Z | 2014-04-09T12:27:47Z | 2014-04-09T12:27:47Z | CONTRIBUTOR | null | How do I change the names of the various levels on a MultiIndex? How do I do so NOT in place (i.e returning a new Dataframe)?
For example I have:
```
d1 d2 d3 d4
u1 u2 u3
Good Things C 1 1 1 1
R 1 1 1 1
Bad Things C 1 1 1 ... | {
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```
l1 1 2
l2 1 13 99 89
0 1 2 2 1
```
and for each value of l1, I want to find the corresponding max value amongst the l2 values under that l1 value. Is there an easy way to do this using groupby?
so in the above example it would be 1->2 and 2->99
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"followers_url": "https://api.github.com/users/jorisva... | 5 | 2013-10-20T03:50:55Z | 2021-03-21T15:51:01Z | 2021-03-21T15:50:10Z | CONTRIBUTOR | null | Is there a reset_index equivalent for the column headings? In other words, if the column names are an MultiIndex, how would I drop one of the levels?
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https://api.github.com/repos/pandas-dev/pandas/issues/5276 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5276/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5276/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5276/events | https://github.com/pandas-dev/pandas/pull/5276 | 21,274,142 | MDExOlB1bGxSZXF1ZXN0OTIzNjM4Mw== | 5,276 | CLN: Remove unused ValuesProperty class. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5277 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5277/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5277/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5277/events | https://github.com/pandas-dev/pandas/pull/5277 | 21,279,434 | MDExOlB1bGxSZXF1ZXN0OTIzODAzMw== | 5,277 | DOC: changed the term "Vern" to "Version" to be clearer | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5278 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5278/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5278/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5278/events | https://github.com/pandas-dev/pandas/issues/5278 | 21,282,028 | MDU6SXNzdWUyMTI4MjAyOA== | 5,278 | drop_level does not show up as arg for DataFrame.xs on api page | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5279 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5279/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5279/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5279/events | https://github.com/pandas-dev/pandas/issues/5279 | 21,282,215 | MDU6SXNzdWUyMTI4MjIxNQ== | 5,279 | New in version 0.13 for "Setting index metadata" | {
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I believe that many of those methods were recently added.
For example on v12:
```
AttributeError: 'MultiIndex' object has no attribute 'set_names'
```
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https://api.github.com/repos/pandas-dev/pandas/issues/5280 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5280/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5280/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5280/events | https://github.com/pandas-dev/pandas/issues/5280 | 21,282,460 | MDU6SXNzdWUyMTI4MjQ2MA== | 5,280 | DOC: MultiIndex Indexing Using Slices | {
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"labels_url": "htt... | 10 | 2013-10-20T16:09:30Z | 2014-03-30T14:46:04Z | 2014-03-30T14:46:04Z | CONTRIBUTOR | null | I have the following `DataFrame`:
```
t1 t2
b1 b1
i1 1 1
```
which I can index like this:
```
In [139]: df["t1"]
Out[139]:
b1
i1 1
In [140]: df["t1","b1"]
Out[140]:
i1 1
Name: (t1, b1), dtype: int64
In [141]: df["t1"]["b1"]
Out[141]:
i1 1
Name: b1, dtype: int64
```
I would expect this... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5281 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5281/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5281/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5281/events | https://github.com/pandas-dev/pandas/pull/5281 | 21,282,623 | MDExOlB1bGxSZXF1ZXN0OTIzOTI2OA== | 5,281 | DOC: Added versionadded for "Setting index metadata" | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5282 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5282/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5282/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5282/events | https://github.com/pandas-dev/pandas/pull/5282 | 21,283,294 | MDExOlB1bGxSZXF1ZXN0OTIzOTUxNw== | 5,282 | DOC: add some missing entries to api docs | {
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is similar to `np.array_equal` except that it handles object arrays and
treats NaNs in corresponding locations as equal.
closes https://github.com/pydata/pandas/issues/5183
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"closed_at": "2020-01-30T12:18:05Z",
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http://stackoverflow.com/questions/19484344/how-do-i-use-a-specific-columns-value-in-a-pandas-dataframe-where-clause/19494873#19494873
http://stackoverflow.com/questions/19507088/filtering-a-pandas-dataframe-without-removing-rows/19516869#19516869
http://stackoverflow.com/q/21627926/190597
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http://pandas.pydata.org/pandas-docs/dev/generated/pandas.DataFrame.sort.html
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```
csv_str = """u1,u2,u3,d1,d2,d3,d4
Good Things,C,,1,1,1,1
Good Things,R,,1,1,1,1
Bad Things,C,,1,1,1,1
Bad Things,T,,1,1,1,1
Okay Things,N,B,1,1,1,1
Okay Things,N,D,1,1,1,1
Okay Things,B,,1,1,1,1
Okay Things,D,,1,1,1,1"""
d_nan = pd.read_csv(StringIO.StringIO(csv_str), na_filter=False,index_col... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5287 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5287/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5287/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5287/events | https://github.com/pandas-dev/pandas/pull/5287 | 21,290,775 | MDExOlB1bGxSZXF1ZXN0OTI0MjYyMg== | 5,287 | DOC: expand JSON docs | {
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Expanded JSON docs to add more detail about the different orient options and the use of the numpy param when decoding.
Feedback welcome.
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"followers_url": "https://api.github.com/users/jr... | 5 | 2013-10-21T04:09:17Z | 2014-02-19T17:41:28Z | 2014-02-19T17:41:28Z | CONTRIBUTOR | null | AssertionError bubbling up to the user - ruroh:
``` python
from io import StringIO
data = StringIO(u"""
121301234
121300123
121300012
""")
pd.read_fwf(data, colspecs=[4, 5])
```
Ends up with an AssertionError:
```
/opt/anaconda/envs/np17py27-1.5/lib/python2.7/site-packages/pandas/io/parsers.pyc in __init__(self, f, ... | {
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``` python
df = pd.DataFrame(zip(range(10), range(10)), columns=['apple', 'b'])
df.groupby([[]])
# Long traceback yields: AssertionError: Grouper and axis must be same leng... | {
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... | {
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... | 12 | 2013-10-21T20:28:00Z | 2017-11-06T17:42:08Z | 2017-11-06T17:42:08Z | NONE | null | I have encountered an issue with the csv parser, pandas.io.parser.read_csv. I get segmentation fault or UnicodeDecodeError when reading a csv-file in chunks and it seems like that the problem depends on the size of the chunks.
Consider the following code:
``` python
import codecs
import csv
import pandas as pd
def c... | {
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Wound up working on this in preparation for the DST change next week. Here's a first pass at a solution and a test.
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closes #4444
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https://api.github.com/repos/pandas-dev/pandas/issues/5296 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5296/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5296/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5296/events | https://github.com/pandas-dev/pandas/pull/5296 | 21,382,325 | MDExOlB1bGxSZXF1ZXN0OTI5MjkyNg== | 5,296 | DOC: Remove iloc example. | {
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"gi... | [] | closed | false | null | [] | null | 0 | 2013-10-22T13:40:07Z | 2014-06-27T12:40:04Z | 2013-10-22T13:53:21Z | CONTRIBUTOR | null | Forgot to remove the `isin(iloc=True)` example from indexing.rst.
https://github.com/pydata/pandas/pull/5199#issuecomment-26786681
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https://api.github.com/repos/pandas-dev/pandas/issues/5297 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5297/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5297/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5297/events | https://github.com/pandas-dev/pandas/issues/5297 | 21,415,971 | MDU6SXNzdWUyMTQxNTk3MQ== | 5,297 | io.html.read_html from UTF-8 file-like object (OS X) | {
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For faster testing, I read *.html files from disk instead of URL with `io.html.read_html()`. Now these files are utf-8 encoded and I can read them directly with
```
open('some.html', encoding='UTF-8').read()
```
However, using `read_html()` with the file name as string gives T... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5298 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5298/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5298/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5298/events | https://github.com/pandas-dev/pandas/pull/5298 | 21,425,132 | MDExOlB1bGxSZXF1ZXN0OTMxMzg1OQ== | 5,298 | BUG: parser can handle a common_format multi-column index (no row index cols), (GH4702) | {
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Will handle the format generated by `to_csv` (which has a an 'extra' line for the index names)
and the more 'common' format
```
In [4]: data = """,a,a,a,b,c,c
...: ,q,r,s,t,u,v
...: one,1,2,3,4,5,6
...: two,7,8,9,10,11,12"""
In [6]: read_csv(StringIO(data),header... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5299 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5299/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5299/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5299/events | https://github.com/pandas-dev/pandas/issues/5299 | 21,447,128 | MDU6SXNzdWUyMTQ0NzEyOA== | 5,299 | doc: DataFrame.apply can return several columns | {
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"followers_url": "https://api.github.com/users/j... | 6 | 2013-10-23T11:15:46Z | 2018-03-05T14:38:48Z | 2018-03-05T14:38:41Z | NONE | null | Might be worth mentioning in the docs that if "func" returns a Series, the result is a DataFrame.
It took me a while to figure this out (tried with tuples and a dict).
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https://api.github.com/repos/pandas-dev/pandas/issues/5300 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5300/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5300/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5300/events | https://github.com/pandas-dev/pandas/issues/5300 | 21,452,380 | MDU6SXNzdWUyMTQ1MjM4MA== | 5,300 | More tolerant dataframe drop method for multiple columns deletion | {
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"id": 2822098,
"name": "Indexing",
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"color": "AD... | closed | false | null | [] | {
"closed_at": "2015-05-11T15:46:03Z",
"closed_issues": 237,
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"followers_url": "https://api.github.com/users/jr... | 5 | 2013-10-23T13:09:37Z | 2015-04-08T14:35:57Z | 2015-04-08T14:35:57Z | NONE | null | Current dataframe.drop will raise error for below code for 'non_exist_in_df_col' :
```
df = df.drop(['col_1', 'col_2', 'non_exist_in_df_col'], axis=1)
```
But below is better for it can accept it.
```
def drop_cols(df, del_cols):
for col in (set(del_cols) & set(df.columns)):
df = df.drop([col], axis=1... | {
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