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https://api.github.com/repos/pandas-dev/pandas/issues/11203 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11203/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11203/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11203/events | https://github.com/pandas-dev/pandas/pull/11203 | 108,946,012 | MDExOlB1bGxSZXF1ZXN0NDYzMjMzOTY= | 11,203 | Fixed pandas.DataFrame().join() function. | {
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] | closed | false | null | [] | null | 6 | 2015-09-29T19:51:34Z | 2015-10-05T11:05:55Z | 2015-10-05T11:05:55Z | CONTRIBUTOR | null | Added on_right and on_left keywords.
Now a right.join(left,on=key) works as expected.
Old behavior is archived by right.join(left,left_on=key)
Tested multi-index funtionallity.
```
import pandas as pd
from copy import copy
print pd.__file__
left = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3','A4'],
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https://api.github.com/repos/pandas-dev/pandas/issues/11204 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11204/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11204/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11204/events | https://github.com/pandas-dev/pandas/issues/11204 | 108,956,980 | MDU6SXNzdWUxMDg5NTY5ODA= | 11,204 | pandas.DataFrame.div "MemoryError" | {
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] | closed | false | null | [] | null | 5 | 2015-09-29T20:49:38Z | 2015-09-29T21:57:30Z | 2015-09-29T21:57:30Z | NONE | null | Using Pandas 0.16.2, NumPy 1.9.2.
This pairwise operation is completed without errors.
``` python
df0=pd.DataFrame(np.random.normal(size=(10000,100)))
df1=df0.div(df0.sum(axis=1))
```
This one involves 10 times more rows. Memory never exceeds 50%, and yet a MemoryError comes up.
``` python
df0=pd.DataFrame(np.rando... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11205 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11205/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11205/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11205/events | https://github.com/pandas-dev/pandas/pull/11205 | 108,984,073 | MDExOlB1bGxSZXF1ZXN0NDYzNDc3NjI= | 11,205 | PERF: vectorized DateOffset with months | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-09-30T00:03:30Z | 2015-10-04T17:01:51Z | 2015-10-02T02:15:07Z | CONTRIBUTOR | null | This is a follow-up to https://github.com/pydata/pandas/pull/10744. In that, vectorized versions of some offsets were implemented, mostly by changing to periods and back.
The case of shifting by years/months (which is actually most useful to me) required some extra hoops and had poorer performance - this PR impleme... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11206 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11206/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11206/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11206/events | https://github.com/pandas-dev/pandas/issues/11206 | 109,066,095 | MDU6SXNzdWUxMDkwNjYwOTU= | 11,206 | BUG: accept np.datetime64('NaT') in an object dtyped as a null | {
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this should work
```
Out[3]: array([11, 22, 33, nan, numpy.datetime64('NaT')], dtype=object)
In [4]: pd.isnull(ser)
Out[4]:
0 False
1 False
2 False
3 True
4 False
Name: my_series, dtype: ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11207 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11207/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11207/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11207/events | https://github.com/pandas-dev/pandas/pull/11207 | 109,138,129 | MDExOlB1bGxSZXF1ZXN0NDY0Mjk2MjM= | 11,207 | Copy on Write via weakrefs | {
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In the interest of advancing the discussion on this, here's a skeleton of a different copy on write implementation.
**Currently**
When setting on a view, converts to copy.
```
df = pd.DataFrame({'col1':[1,2], 'col2':[3,4]})
intermediate = df.loc[1:1,]
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https://api.github.com/repos/pandas-dev/pandas/issues/11208 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11208/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11208/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11208/events | https://github.com/pandas-dev/pandas/issues/11208 | 109,163,914 | MDU6SXNzdWUxMDkxNjM5MTQ= | 11,208 | DataFrame.apply() silently converting columns to non-categorical type | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-09-30T19:40:45Z | 2015-09-30T19:56:15Z | 2015-09-30T19:56:03Z | CONTRIBUTOR | null | Per [this SO question](http://stackoverflow.com/q/32873402/467366), using `apply()` to convert multiple `DataFrame` columns to categorical does not work unless _all_ columns are categorical.
An MWE demonstrating the issue can be found at [this gist](https://gist.github.com/pganssle/4d0b4c326f0f8e80ba50) for easy copy-... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11209 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11209/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11209/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11209/events | https://github.com/pandas-dev/pandas/pull/11209 | 109,184,335 | MDExOlB1bGxSZXF1ZXN0NDY0NTk4OTk= | 11,209 | Add ability to set the allowLargeResults option in BigQuery #10474 | {
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] | closed | false | null | [] | null | 8 | 2015-09-30T21:35:26Z | 2015-10-02T15:25:42Z | 2015-10-02T15:25:42Z | CONTRIBUTOR | null | - Modify `read_gbq()` to allow users to redirect the query results to a destination table via the `destination_table` parameter
- Modify `read_gbq()` to allow users to allow users to set the `'allowLargeResults'` option in the BigQuery job configuration via the `allow_large_results` parameter
cc @aaront
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https://api.github.com/repos/pandas-dev/pandas/issues/11210 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11210/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11210/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11210/events | https://github.com/pandas-dev/pandas/issues/11210 | 109,189,057 | MDU6SXNzdWUxMDkxODkwNTc= | 11,210 | TST: fix some unreliable html_truncate tests | {
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don't fail for me locally, so not sure what's up.
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closes #8038
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https://api.github.com/repos/pandas-dev/pandas/issues/11212 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11212/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11212/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11212/events | https://github.com/pandas-dev/pandas/pull/11212 | 109,200,196 | MDExOlB1bGxSZXF1ZXN0NDY0Njk2MzA= | 11,212 | BUG: GH11206 where pd.isnull did not consider numpy NaT null | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11213 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11213/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11213/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11213/events | https://github.com/pandas-dev/pandas/issues/11213 | 109,206,862 | MDU6SXNzdWUxMDkyMDY4NjI= | 11,213 | Dataframe.from_dict inconsistent behavior | {
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this works:
```
monthly = {'datetime_col_to_use':['START DATE'],
'colnames': ["TYPE", "START DATE", "END DATE", "USAGE", "UNITS", "COST", "NOTES"],
'header_size':4,
'concat_datetime_cols': False}
monthly_df = pd.DataFrame.from_dict(monthly, orient='index')
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https://api.github.com/repos/pandas-dev/pandas/issues/11214 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11214/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11214/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11214/events | https://github.com/pandas-dev/pandas/issues/11214 | 109,277,851 | MDU6SXNzdWUxMDkyNzc4NTE= | 11,214 | PERF/CLN: see what we can use from offsets.pyx | {
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"followers_url": "https://api.github.com/users/jorisva... | 7 | 2015-10-01T11:02:20Z | 2017-11-10T16:12:40Z | 2017-11-10T09:00:41Z | CONTRIBUTOR | null | xref #11205
https://github.com/pydata/pandas/blob/master/pandas/src/offsets.pyx
is in the repo but is not included in the build, nor updated in 2+ years.
Looks like their might be some cython code to speed up `DateOffset` apply in the non-vectorized cases.
Further might look to move _some_ routines from `tslib.pyx`... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11215 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11215/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11215/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11215/events | https://github.com/pandas-dev/pandas/pull/11215 | 109,299,052 | MDExOlB1bGxSZXF1ZXN0NDY1MjMwNTM= | 11,215 | Use set literal syntax for set prettyprinting | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11216 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11216/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11216/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11216/events | https://github.com/pandas-dev/pandas/pull/11216 | 109,417,385 | MDExOlB1bGxSZXF1ZXN0NDY1OTY4NDY= | 11,216 | BUG: edge case when reading from postgresl with read_sql_query and datetime with tz and chunksize | {
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- We create a propery datetime64[ns, tz] type, but its a pytz.FixedOffset(....)
which ATM is not really a useful/palatable type and is mostly confusing for now.
In the future could attempt to coerce this to a nice tz, e.g. US/Eastern, ,not sure... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11217 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11217/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11217/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11217/events | https://github.com/pandas-dev/pandas/issues/11217 | 109,448,287 | MDU6SXNzdWUxMDk0NDgyODc= | 11,217 | resample() should allow a "null" fill_method | {
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... | 25 | 2015-10-02T08:12:50Z | 2020-03-31T05:14:54Z | 2020-03-31T05:14:53Z | CONTRIBUTOR | null | I'm using `resample()` to aggregate data in a timeframe.
``` python
>>> s = pandas.Series((3, 4), (pandas.Timestamp("2014-1-1"), pandas.Timestamp("2015-1-1")))
>>> x = s.resample("1s")
>>> len(x)
31536001
```
When doing such a call, `resample` fills with NaN all the (31536001 - 2) inexistent values, which ends up cre... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11218 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11218/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11218/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11218/events | https://github.com/pandas-dev/pandas/issues/11218 | 109,475,689 | MDU6SXNzdWUxMDk0NzU2ODk= | 11,218 | requirements_dev.txt missing | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11219 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11219/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11219/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11219/events | https://github.com/pandas-dev/pandas/pull/11219 | 109,482,277 | MDExOlB1bGxSZXF1ZXN0NDY2MzA0NjU= | 11,219 | ENH: added compression kw to to_csv GH7615 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11220 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11220/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11220/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11220/events | https://github.com/pandas-dev/pandas/issues/11220 | 109,493,387 | MDU6SXNzdWUxMDk0OTMzODc= | 11,220 | BUG: numpy.datetime('NaT') printing inconsistency | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11221 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11221/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11221/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11221/events | https://github.com/pandas-dev/pandas/issues/11221 | 109,498,865 | MDU6SXNzdWUxMDk0OTg4NjU= | 11,221 | API: .convert_objects is deprecated, do we want a .convert to replace? | {
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or IMHO simply replace by use of `pd.to_datetime,pd.to_timedelta,pd.to_numeric`.
Having an auto-guesser is ok, but when you try to forcefully coerce things can easily go awry.
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https://api.github.com/repos/pandas-dev/pandas/issues/11222 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11222/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11222/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11222/events | https://github.com/pandas-dev/pandas/issues/11222 | 109,514,067 | MDU6SXNzdWUxMDk1MTQwNjc= | 11,222 | AttributeError: 'DataFrame' object has no attribute 'bits' | {
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"descript... | closed | false | null | [] | null | 5 | 2015-10-02T15:26:03Z | 2015-10-02T16:24:21Z | 2015-10-02T15:28:40Z | NONE | null | Hi, I am new here just started some tutorials learning python, can you plz help me
'vw_bits_amazon.csv'
```
bits loss
25 0.151731
24 0.151809
23 0.151951
22 0.151809
```
```
import pandas as pd
from matplotlib import pyplot as plt
input_file = 'vw_bits_amazon.csv'
d = pd.read_csv(input_file)
plt.plot(d.bits... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11223 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11223/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11223/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11223/events | https://github.com/pandas-dev/pandas/issues/11223 | 109,540,052 | MDU6SXNzdWUxMDk1NDAwNTI= | 11,223 | object used in example but not created there | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-10-02T17:56:33Z | 2015-11-15T18:41:29Z | 2015-11-15T18:41:29Z | CONTRIBUTOR | null | In [here](http://pandas-docs.github.io/pandas-docs-travis/groupby.html#groupby-with-multiindex) object `s` is used in the example but not created on this page (at least in this form).
Above it is created as series
``` python
In [8]: s = pd.Series([1, 2, 3, 10, 20, 30], lst)
```
once under [here](http://pandas-docs... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11224 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11224/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11224/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11224/events | https://github.com/pandas-dev/pandas/issues/11224 | 109,540,759 | MDU6SXNzdWUxMDk1NDA3NTk= | 11,224 | DataFrame.loc[] returns inconsistent types depending on row count | {
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"color": "00... | closed | false | null | [] | null | 9 | 2015-10-02T18:00:01Z | 2015-10-02T20:00:01Z | 2015-10-02T18:53:10Z | NONE | null | If a dataframe has a single row for a given index entry, it returns a Series. If it
has two rows for that index, it returns a DataFrame. I believe that it should return a
DataFrame in either case for consistency.
Image attached, small dataframe and notebook exhibiting the problem attached. OK, so
I can't attach either... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11225 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11225/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11225/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11225/events | https://github.com/pandas-dev/pandas/pull/11225 | 109,559,514 | MDExOlB1bGxSZXF1ZXN0NDY2NzQxNzU= | 11,225 | defer or remove loading of openhub in docs | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-10-02T19:43:34Z | 2015-10-02T21:26:59Z | 2015-10-02T21:26:58Z | CONTRIBUTOR | null | Their service was slowing down the loading of our docs. I've added a defer tag so that our docs load first.
Or we can delete that entirely, anyone know why it's in there to begin with?
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https://api.github.com/repos/pandas-dev/pandas/issues/11226 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11226/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11226/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11226/events | https://github.com/pandas-dev/pandas/issues/11226 | 109,568,951 | MDU6SXNzdWUxMDk1Njg5NTE= | 11,226 | BUG: multilevel indexing with new values | {
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... | 1 | 2015-10-02T20:44:21Z | 2016-02-13T13:48:30Z | 2016-02-13T13:48:30Z | CONTRIBUTOR | null | ```
In [2]: df = pd.DataFrame(data=[[0, 2, 1], [np.nan, 5, 4]], index=pd.date_range('2014-01-01', '2014-01-2', name='timestamp'), columns=pd.MultiIndex.from_product([['value'], [24, 3766, 5061]], names=[None, 'sid']))
In [3]: df
Out[3]:
value
sid 24 3766 5061
timestamp
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https://api.github.com/repos/pandas-dev/pandas/issues/11227 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11227/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11227/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11227/events | https://github.com/pandas-dev/pandas/issues/11227 | 109,629,267 | MDU6SXNzdWUxMDk2MjkyNjc= | 11,227 | COMPAT: different orderings in value_counts on 32-bit platforms | {
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see test skipping here: https://github.com/pydata/pandas/co... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11228 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11228/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11228/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11228/events | https://github.com/pandas-dev/pandas/issues/11228 | 109,633,211 | MDU6SXNzdWUxMDk2MzMyMTE= | 11,228 | Inconsistent color arguments | {
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... | open | false | null | [] | null | 8 | 2015-10-03T17:04:06Z | 2021-04-20T05:26:33Z | null | NONE | null | In pandas 0.17.0.rc1 there is an inconsistency in the color arguments: once it is "color", other times it is "colors":
df.plot(kind='bar', color= ....)
df.plot(kind='pie', colors= ...)
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https://api.github.com/repos/pandas-dev/pandas/issues/11229 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11229/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11229/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11229/events | https://github.com/pandas-dev/pandas/issues/11229 | 109,636,324 | MDU6SXNzdWUxMDk2MzYzMjQ= | 11,229 | Squeeze fails on zero length arrays | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-10-03T18:04:36Z | 2015-10-09T13:15:20Z | 2015-10-09T13:15:20Z | CONTRIBUTOR | null | ``` python
In [77]: empty=pd.DataFrame(pd.np.empty(shape=(0,1)))
In [78]: empty
Out[78]:
Empty DataFrame
Columns: [0]
Index: []
In [79]: empty.squeeze()
Out[79]:
Empty DataFrame
Columns: [0]
Index: []
```
...but should return a `Series`
PR coming now
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https://api.github.com/repos/pandas-dev/pandas/issues/11230 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11230/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11230/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11230/events | https://github.com/pandas-dev/pandas/pull/11230 | 109,636,435 | MDExOlB1bGxSZXF1ZXN0NDY3MTAwNzc= | 11,230 | squeeze works on 0 length arrays | {
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"followers_url": "https://api.github.com/users/jr... | 9 | 2015-10-03T18:05:48Z | 2015-12-08T03:52:34Z | 2015-10-09T13:15:07Z | CONTRIBUTOR | null | fixes: https://github.com/pydata/pandas/issues/11229.
fixes: https://github.com/pydata/pandas/issues/8999.
Also a better implementation that avoids `ix`
Should I add to What's new for 0.17? Or is that closed now?
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https://api.github.com/repos/pandas-dev/pandas/issues/11231 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11231/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11231/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11231/events | https://github.com/pandas-dev/pandas/pull/11231 | 109,651,376 | MDExOlB1bGxSZXF1ZXN0NDY3MTU1NDk= | 11,231 | DOC: Add note about unicode layout | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11232 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11232/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11232/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11232/events | https://github.com/pandas-dev/pandas/issues/11232 | 109,664,187 | MDU6SXNzdWUxMDk2NjQxODc= | 11,232 | tseries and TestSeries test errors on Python 3.3 and OSX | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-10-04T05:34:59Z | 2015-10-06T18:04:08Z | 2015-10-06T18:04:08Z | CONTRIBUTOR | null | Building and testing OSX wheels for 0.17.0, I am getting these errors on Python 3.3 (not 2.7 or 3.4 or 3.5):
```
======================================================================
FAIL: test_isin (pandas.tseries.tests.test_timedeltas.TestTimedeltaIndex)
-------------------------------------------------------------... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11233 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11233/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11233/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11233/events | https://github.com/pandas-dev/pandas/pull/11233 | 109,667,079 | MDExOlB1bGxSZXF1ZXN0NDY3MjA1Mjc= | 11,233 | BUG: to_latex() output broken when the index has a name (GH10660) | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-10-04T06:55:29Z | 2015-10-09T13:04:03Z | 2015-10-09T13:03:57Z | CONTRIBUTOR | null | closes #10660
first try at contributing to pandas. feedbacks will be greatly appreciated.
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https://api.github.com/repos/pandas-dev/pandas/issues/11234 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11234/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11234/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11234/events | https://github.com/pandas-dev/pandas/issues/11234 | 109,686,223 | MDU6SXNzdWUxMDk2ODYyMjM= | 11,234 | HDFStore fails to read non-ascii characters | {
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``` python
import pandas as pd
df = pd.DataFrame(columns=["... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11235 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11235/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11235/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11235/events | https://github.com/pandas-dev/pandas/issues/11235 | 109,686,658 | MDU6SXNzdWUxMDk2ODY2NTg= | 11,235 | Dataframe.eval(): Negative number in list passed to 'in'-expression causes crash on python 3.4.0 | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2015-10-04T15:30:08Z | 2017-05-15T22:59:47Z | 2015-10-23T20:41:12Z | CONTRIBUTOR | null | The following crashes on python 3.4.0. It works fine on Python 2.7.5.
```
>>> import pandas
>>> from io import StringIO
>>> data = "foo,bar\n11,12"
>>> df = pandas.read_csv(StringIO(data))
>>> df.eval('foo in [11, 32]')
0 True
dtype: bool
>>> df.eval('foo in [11, -32]')
Traceback (most recent call last):
File "<s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11236 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11236/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11236/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11236/events | https://github.com/pandas-dev/pandas/issues/11236 | 109,692,589 | MDU6SXNzdWUxMDk2OTI1ODk= | 11,236 | add a graph data structure using the data frame | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11237 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11237/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11237/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11237/events | https://github.com/pandas-dev/pandas/pull/11237 | 109,694,935 | MDExOlB1bGxSZXF1ZXN0NDY3Mjk5MDk= | 11,237 | BUG: to_excel duplicate columns | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2015-10-04T18:21:15Z | 2015-10-11T23:36:11Z | 2015-10-10T00:23:39Z | CONTRIBUTOR | null | closes #11007
closes #10970 (data in wrong order)
closes #10982 (columns lost).
Using the approach suggested [here](https://github.com/pydata/pandas/issues/11007#issuecomment-141019207)
All three occurred when using `to_excel` with duplicate columns in the `DataFrame`
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https://api.github.com/repos/pandas-dev/pandas/issues/11238 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11238/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11238/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11238/events | https://github.com/pandas-dev/pandas/issues/11238 | 109,705,560 | MDU6SXNzdWUxMDk3MDU1NjA= | 11,238 | column-specific min_itemsize doesn't work with append_to_multiple | {
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Simple example:
```
>>> store.append_to_multiple... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11239 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11239/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11239/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11239/events | https://github.com/pandas-dev/pandas/issues/11239 | 109,707,319 | MDU6SXNzdWUxMDk3MDczMTk= | 11,239 | Specifying data_columns for non-selector tables with `append_to_multiple` | {
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... | 0 | 2015-10-04T21:53:18Z | 2021-04-20T05:26:50Z | null | NONE | null | `HDFStore.append_to_multiple` only lets your specify `data_columns` for the "selector" table; all other tables you make with it have no data columns. Is there a reason it needs to be that way?
I think the `append_to_multiple`/`select_as_multiple` workflow would be somewhat more flexible if we didn't view the set of t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11240 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11240/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11240/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11240/events | https://github.com/pandas-dev/pandas/pull/11240 | 109,714,512 | MDExOlB1bGxSZXF1ZXN0NDY3MzY5MDI= | 11,240 | BUG: HDFStore.append with encoded string itemsize | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-10-05T00:15:36Z | 2015-10-09T13:33:02Z | 2015-10-09T13:33:02Z | CONTRIBUTOR | null | Closes https://github.com/pydata/pandas/issues/11234
Failure came when the maximum length of the unencoded string
was smaller than the maximum encoded length.
Need to run a perf check still. We end up having to call `_convert_string_array` twice, once before we know the min_itemsize, and a second time just before app... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11241 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11241/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11241/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11241/events | https://github.com/pandas-dev/pandas/pull/11241 | 109,783,607 | MDExOlB1bGxSZXF1ZXN0NDY3NzMyMzI= | 11,241 | test regarding fix about non propagating along axis on pct_change | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11243 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11243/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11243/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11243/events | https://github.com/pandas-dev/pandas/pull/11243 | 109,824,578 | MDExOlB1bGxSZXF1ZXN0NDY3OTY0MTg= | 11,243 | DOC: clarify requirements for read_stata's args | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11244 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11244/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11244/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11244/events | https://github.com/pandas-dev/pandas/issues/11244 | 109,845,663 | MDU6SXNzdWUxMDk4NDU2NjM= | 11,244 | BUG: index sorting with strings & timestamps | {
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``` python
test = pd.DataFrame({
pd.Timestamp('2012-01-01 00:00:00'): ['a', 'b'],
pd.Timestamp('2012-01-02 00:00:00'): ['c', 'd'],
'name': ['e', 'e'],
'aaaa': ['f', 'g']
})
print(test)
print(test.groupby('name').first())
```
Fails with:
```
File "/usr/lib64/python3.4/... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11245 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11245/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11245/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11245/events | https://github.com/pandas-dev/pandas/pull/11245 | 109,859,561 | MDExOlB1bGxSZXF1ZXN0NDY4MTcxNDM= | 11,245 | BUG: datetime64 series reduces to nan when empty instead of nat | {
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"followers_url": "https://api.github.com/users/jr... | 16 | 2015-10-05T18:41:09Z | 2015-10-11T15:17:56Z | 2015-10-11T15:17:51Z | CONTRIBUTOR | null | I ran into some strange behavior with a series of dtype datetime64[ns] where I called max and got back a `nan`. I think the correct behavior here is to return `nat`. I looked through test_nanops but I am not sure where the correct place to put the test for this is.
The new behavior is:
``` python
In [1]: pd.Series(dt... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11246 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11246/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11246/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11246/events | https://github.com/pandas-dev/pandas/issues/11246 | 109,880,068 | MDU6SXNzdWUxMDk4ODAwNjg= | 11,246 | DOC: typo in convert_objects | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2015-10-05T20:33:35Z | 2015-10-06T07:55:46Z | 2015-10-06T07:55:46Z | CONTRIBUTOR | null | In the new warning. `to_timestamp` should be `to_timedelta`
```
df.convert_objects()
...
FutureWarning: convert_objects is deprecated.
Use the data-type specific converters pd.to_datetime, pd.to_timestamp and pd.to_numeric.
```
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```
data = df.to_dict(orient='records')
```
but I had to replace with a different to_dict conversion because to_dict(orient='records') doesn't properly convert numpy.datetime64 to Timestamps but rather returns numpy.datetime64 values which are hard to work with downstream. If you include any o... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11249 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11249/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11249/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11249/events | https://github.com/pandas-dev/pandas/pull/11249 | 109,910,349 | MDExOlB1bGxSZXF1ZXN0NDY4NDk2NDc= | 11,249 | DOC: Fix typo in Grouper private method documentation. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11250 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11250/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11250/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11250/events | https://github.com/pandas-dev/pandas/issues/11250 | 109,928,545 | MDU6SXNzdWUxMDk5Mjg1NDU= | 11,250 | Drop duplicate columns from DataFrame based on column values | {
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... | 14 | 2015-10-06T03:21:46Z | 2021-04-20T05:27:53Z | null | NONE | null | Here is sample code that finds duplicate columns in a DataFrame based on their values (useful for cleaning data):
``` python
def duplicate_columns(frame):
groups = frame.columns.to_series().groupby(frame.dtypes).groups
dups = []
for t, v in groups.items():
dcols = frame[v].to_dict(orient="list")
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https://api.github.com/repos/pandas-dev/pandas/issues/11251 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11251/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11251/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11251/events | https://github.com/pandas-dev/pandas/issues/11251 | 109,948,402 | MDU6SXNzdWUxMDk5NDg0MDI= | 11,251 | importing pandas will cause a file called "parser.py" in the CWD to be imported | {
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pandas should not be importing random files wh... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11252 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11252/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11252/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11252/events | https://github.com/pandas-dev/pandas/pull/11252 | 109,985,450 | MDExOlB1bGxSZXF1ZXN0NDY4ODkwNjA= | 11,252 | COMPAT/PERF: lib.ismember_int64 on older numpies/cython not comparing correctly #11232 | {
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PERF: use np.in1d on larger isin sizes
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https://api.github.com/repos/pandas-dev/pandas/issues/11253 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11253/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11253/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11253/events | https://github.com/pandas-dev/pandas/pull/11253 | 110,041,856 | MDExOlB1bGxSZXF1ZXN0NDY5MjIxMjc= | 11,253 | added random_split in generic.py, for DataFrames etc. | {
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Basic use: for train/test or train/validation/test splitting of a dataframe.
Note: I'm not sure this feature fits well in NDFrame. If you think this feature can be added, I'll add more tests and docs.
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https://api.github.com/repos/pandas-dev/pandas/issues/11254 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11254/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11254/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11254/events | https://github.com/pandas-dev/pandas/issues/11254 | 110,102,340 | MDU6SXNzdWUxMTAxMDIzNDA= | 11,254 | Testing RC versions of pandas in conda | {
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> I'm pleased to announce the availability of the second release candidate of Pandas 0.17.0.
> ...
> Best way to get this is to install via conda from our development channel. Builds for osx-64,linux-64,win-64 for Python 2.7, Python 3.4, and Python 3.5 (... | {
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ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
The only thing different abou... | {
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So, if the file contains text before the data, column detection fails. It could be solved by using only the actual data lines (and header) to infer column widths.
I worked around that is... | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-10-07T11:19:56Z | 2018-12-06T21:13:45Z | 2015-10-07T21:42:44Z | MEMBER | null | This PR includes some hacks to numpydoc to get rid of a bunch of warnings (split of from https://github.com/pydata/pandas/pull/11069 as I want these merged for 0.17.0). There is some more explanation in the commit messages.
Closes #6100
The disadvantage of this is that this causes a deviation from numpydoc upstream, ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11258 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11258/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11258/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11258/events | https://github.com/pandas-dev/pandas/issues/11258 | 110,288,535 | MDU6SXNzdWUxMTAyODg1MzU= | 11,258 | .read_sql_query works but .read_sql_table fails | {
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"followers_url": "https://api.github.com/users/jorisva... | 10 | 2015-10-07T18:34:33Z | 2021-04-06T15:13:52Z | 2015-10-09T07:08:49Z | NONE | null | Pandas is very helpful and I have been using it heavily recently. However, I have run into an issue where this code works:
```
from sqlalchemy import *
import pandas as pd
orcl_connect_string = 'oracle+cx_oracle://system:oracle@192.168.56.101:1521/?service_name=orcl'
engine = create_engine(orcl_connect_string)
pd.read... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11259 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11259/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11259/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11259/events | https://github.com/pandas-dev/pandas/pull/11259 | 110,296,765 | MDExOlB1bGxSZXF1ZXN0NDcwNjkxOTg= | 11,259 | BUG/ERR: raise when trying to set a subset of values in a datetime64[ns, tz] columns with another tz | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11260 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11260/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11260/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11260/events | https://github.com/pandas-dev/pandas/issues/11260 | 110,308,919 | MDU6SXNzdWUxMTAzMDg5MTk= | 11,260 | CLN: Integrate .corrwith and .corr | {
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- `corr` on a `DataFrame` requires another `DataFrame`, and fails on a `Series`
- `corrwith` on a `DataFrame` takes a `Series`
Is there a good reason these are separate? Should `corr` do whatever `corrwith` does when passed a `Series`, and `corrwith` could be deprecated?
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https://api.github.com/repos/pandas-dev/pandas/issues/11261 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11261/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11261/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11261/events | https://github.com/pandas-dev/pandas/pull/11261 | 110,356,723 | MDExOlB1bGxSZXF1ZXN0NDcxMDM5NzQ= | 11,261 | DOC: Included halflife as one 3 optional params that must be specified | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11262 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11262/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11262/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11262/events | https://github.com/pandas-dev/pandas/pull/11262 | 110,361,593 | MDExOlB1bGxSZXF1ZXN0NDcxMDU5ODE= | 11,262 | CI: fix numpy to 1.9.3 in 2.7,3.5 builds for now, as packages for 1.1.0 not released ATM | {
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conda packages are not yet updated, so need to fix to 1.9.3 for now
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https://api.github.com/repos/pandas-dev/pandas/issues/11263 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11263/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11263/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11263/events | https://github.com/pandas-dev/pandas/pull/11263 | 110,365,967 | MDExOlB1bGxSZXF1ZXN0NDcxMDgxNTA= | 11,263 | PERF: Release GIL on some datetime ops | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2015-10-08T03:29:23Z | 2015-10-21T22:42:05Z | 2015-10-17T14:48:10Z | CONTRIBUTOR | null | This is a WIP, but far enough along I thought I'd share and see if the approach was reasonable.
This releases the GIL on most vectorized field accessors (e.g. `dt.year`) and conversion to and from `Period`. May be places it could be done - obviously would be nice for parsing, but I'm not sure that's possible.
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https://api.github.com/repos/pandas-dev/pandas/issues/11264 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11264/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11264/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11264/events | https://github.com/pandas-dev/pandas/issues/11264 | 110,399,531 | MDU6SXNzdWUxMTAzOTk1MzE= | 11,264 | add set_index_ncol(ncol) to set first n columns as indices | {
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df = pd.read_sql('select idx1,idx2,metric1 from table1 ', dbcon)
df.set_index(list(df.columns)[:ncol]).T.to_dict('list')
```
such operations are very frequent in product
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] | closed | false | null | [] | null | 7 | 2015-10-08T16:14:59Z | 2018-06-20T13:18:48Z | 2015-10-08T17:38:31Z | NONE | null | The output is so long but it seems that something goes wrong with the compiling, is there something wrong with the complier I use?
```
> pip install pandas
Collecting pandas
Using cached pandas-0.16.2.tar.gz
Requirement already satisfied (use --upgrade to upgrade): python-dateutil>=2 in c:\program files\python 3.5\l... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11266 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11266/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11266/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11266/events | https://github.com/pandas-dev/pandas/issues/11266 | 110,604,799 | MDU6SXNzdWUxMTA2MDQ3OTk= | 11,266 | Using blosc compression in pandas causes heap corruption in Windows | {
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```
INSTALLED VERSIONS
------------------
commit: None
python: 3.4.3.final.0
python-bits: 64
OS: Windows
OS-... | {
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... | 7 | 2015-10-09T08:02:26Z | 2020-10-17T01:51:36Z | 2020-10-17T01:51:36Z | NONE | null | `MultiIndex` cannot be subclassed because in several spots, including `__new__`, the output class is hardcoded as `MultiIndex` rather than `cls` or `self.__class__` or the like.
This code illustrates the problem:
``` python
$ python
Python 2.7.10 (default, Sep 13 2015, 20:30:50)
[GCC 5.2.1 20150911] on linux2
Type ... | {
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MultiIndex had several places where the output class was hard-coded to
MultiIndex rather than cls, self.**class**, or the like. These have
been replaced.
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``` python
def itertuples(self, index=True):
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https://api.github.com/repos/pandas-dev/pandas/issues/11270 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11270/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11270/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11270/events | https://github.com/pandas-dev/pandas/issues/11270 | 110,656,934 | MDU6SXNzdWUxMTA2NTY5MzQ= | 11,270 | ABCGeneric instance checking is broken | {
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... | 11 | 2015-10-09T13:13:37Z | 2018-10-29T10:51:32Z | 2018-10-29T10:51:32Z | NONE | null | So, my issue was that pandas was throwing an error (about not having implemented `_constructor`) when I tried to use a custom object as a label for a column in `DataFrame`, even though that object's class was not a part of the pandas hierarchy. After some digging I have realized that pandas thinks this object is an ins... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11271 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11271/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11271/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11271/events | https://github.com/pandas-dev/pandas/issues/11271 | 110,661,207 | MDU6SXNzdWUxMTA2NjEyMDc= | 11,271 | CLN: move _get_handle, UTF encoders from core.common to io.common | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11272 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11272/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11272/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11272/events | https://github.com/pandas-dev/pandas/pull/11272 | 110,689,229 | MDExOlB1bGxSZXF1ZXN0NDcyOTAyNTY= | 11,272 | PERF: Removed the GIL from parts of the TextReader class | {
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## Benchmark:
### Data Generation:
``` python
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randn(1000000,10))
df.to_csv('test.csv')
```
### Benchmark Code:
``` python
import pandas as pd
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https://api.github.com/repos/pandas-dev/pandas/issues/11273 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11273/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11273/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11273/events | https://github.com/pandas-dev/pandas/issues/11273 | 110,700,983 | MDU6SXNzdWUxMTA3MDA5ODM= | 11,273 | COMPAT: drop support for Python 3.3 | {
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let's deprecate in 0.17.1 and just remove in 0.18.0
This was never advertised / doc-ed so prob safe to remove
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I've uploaded quite a few 3.5 wheels to pypi in the last couple of weeks, e.g.:
https://pypi.python.org/pypi/scipy
https://pypi.python.org/pypi/matplotlib
https://pypi.python.org/pypi/Cython
Do you have any more information on that pr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11277 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11277/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11277/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11277/events | https://github.com/pandas-dev/pandas/pull/11277 | 110,736,983 | MDExOlB1bGxSZXF1ZXN0NDczMjA3Mjk= | 11,277 | Update sql.py | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-10-09T21:13:48Z | 2015-10-10T10:10:18Z | 2015-10-10T10:10:18Z | CONTRIBUTOR | null | Fix documentation for index_col parameter to read_sql, read_sql_table and read_sql_query to reflect that a list can be passed.
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https://api.github.com/repos/pandas-dev/pandas/issues/11278 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11278/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11278/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11278/events | https://github.com/pandas-dev/pandas/issues/11278 | 110,751,293 | MDU6SXNzdWUxMTA3NTEyOTM= | 11,278 | List indexer on PeriodIndex doesn't coerce strings | {
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"closed_at": "2020-07-28T18:13:47Z",
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"followers_url": "https://api.github.com/users/j... | 1 | 2015-10-09T23:25:59Z | 2020-05-03T16:09:14Z | 2020-05-03T16:09:14Z | CONTRIBUTOR | null | ``` python
In [2]: index = pd.period_range(start='2000', periods=20, freq='B')
In [5]: series = pd.Series(range(20), index=index)
In [6]: series
Out[6]:
2000-01-03 0
2000-01-04 1
2000-01-05 2
...
2000-01-26 17
2000-01-27 18
2000-01-28 19
Freq: B, dtype: int64
In [7]: series.loc['2000-01-14']
Out... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11279 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11279/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11279/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11279/events | https://github.com/pandas-dev/pandas/pull/11279 | 110,758,984 | MDExOlB1bGxSZXF1ZXN0NDczMzQwNDk= | 11,279 | PERF: use .values in index difference | {
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"color": "a1... | closed | false | null | [] | null | 14 | 2015-10-10T01:16:40Z | 2016-01-06T17:35:24Z | 2016-01-06T17:18:33Z | CONTRIBUTOR | null | The existing `.difference` method 'unboxed' all the objects, which has a severe performance impact on `PeriodIndex` in particular.
``` python
In [3]: long_index = pd.period_range(start='2000', freq='s', periods=1000)
In [4]: empty_index = pd.PeriodIndex([],freq='s')
In [24]: %timeit long_index.difference(empty_in... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11280 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11280/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11280/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11280/events | https://github.com/pandas-dev/pandas/pull/11280 | 110,785,508 | MDExOlB1bGxSZXF1ZXN0NDczNDI1ODE= | 11,280 | DOC: whatsnew fixes | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2015-10-10T10:12:33Z | 2015-10-10T10:12:54Z | 2015-10-10T10:12:54Z | MEMBER | null | Some fixes I applied to the v0.17.0 docs I uploaded (older whatsnew was failing due to changes in 0.17)
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https://api.github.com/repos/pandas-dev/pandas/issues/11281 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11281/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11281/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11281/events | https://github.com/pandas-dev/pandas/issues/11281 | 110,797,705 | MDU6SXNzdWUxMTA3OTc3MDU= | 11,281 | Saving datetime64 with timezone to HDF5 | {
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"descript... | closed | false | null | [] | null | 2 | 2015-10-10T14:30:23Z | 2015-11-17T10:18:46Z | 2015-10-10T14:47:39Z | NONE | null | An attempt to store a dataframe with datetime64+tz column (introduced in pandas 0.17) results in a TypeError exception
``` python
import pandas as pd
```
``` python
df = pd.DataFrame(pd.date_range('2015-01-01', '2015-01-02', freq='T'), columns=['time'])
df.time = df.time.dt.tz_localize('UTC')
df.dtypes
```
```
time ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11282 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11282/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11282/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11282/events | https://github.com/pandas-dev/pandas/issues/11282 | 110,807,301 | MDU6SXNzdWUxMTA4MDczMDE= | 11,282 | few fresh failed tests on big-endian platforms (0.17.0+git8-gcac4ad2) | {
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... | 15 | 2015-10-10T17:35:46Z | 2021-04-20T05:32:22Z | 2021-04-20T05:32:21Z | CONTRIBUTOR | null | for details see https://buildd.debian.org/status/fetch.php?pkg=pandas&arch=powerpc&ver=0.17.0%2Bgit8-gcac4ad2-1&stamp=1444485115 but here is the excerpt of few failed tests:
```
======================================================================
FAIL: pandas.io.tests.test_packers.TestMsgpack.test_msgpack('0.16.2',... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11283 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11283/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11283/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11283/events | https://github.com/pandas-dev/pandas/issues/11283 | 110,822,073 | MDU6SXNzdWUxMTA4MjIwNzM= | 11,283 | Mistake in BinOp.conform? | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-10-10T23:11:39Z | 2015-10-13T11:49:26Z | 2015-10-13T11:49:26Z | NONE | null | in BinOp.conform in pandas.computation,pytables there is this code:
```
def conform(self, rhs):
""" inplace conform rhs """
if not com.is_list_like(rhs):
rhs = [rhs]
if hasattr(self.rhs, 'ravel'):
rhs = rhs.ravel()
return rhs
```
I think this is wrong. The ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11284 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11284/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11284/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11284/events | https://github.com/pandas-dev/pandas/issues/11284 | 110,822,630 | MDU6SXNzdWUxMTA4MjI2MzA= | 11,284 | Pandas HDF query syntax is more restrictive than PyTables | {
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"description": "read_hdf... | open | false | null | [] | null | 5 | 2015-10-10T23:23:55Z | 2020-04-30T05:51:49Z | null | NONE | null | With PyTables, you can do queries like `someTable.where("X**2 + Y**2 < 1")` (as described [here](http://www.pytables.org/usersguide/condition_syntax.html)). It seems, though, that pandas imposes its own more restrictive query syntax which allows only a very limited set of query operations. This is confusing to users ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11285 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11285/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11285/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11285/events | https://github.com/pandas-dev/pandas/issues/11285 | 110,851,511 | MDU6SXNzdWUxMTA4NTE1MTE= | 11,285 | Improve the BigQuery streaming insert failure message | {
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"color": "0052... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2015-10-11T11:41:01Z | 2015-10-11T15:40:28Z | 2015-10-11T15:40:28Z | CONTRIBUTOR | null | The error message shown when a BigQuery streaming insert fails could be improved by adding the location field.
Code to reproduce:
```
from datetime import datetime
from pandas import DataFrame
from pandas.io import gbq
import pytz
test_timestamp = datetime.now(pytz.timezone('US/Arizona'))
bad_df = DataFrame({'bools... | {
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This is a minor change to include `'Location'` in the error message reported when a streaming insert fails using the `df.to_gbq()`
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```
test_invalid_index_types (pandas.tseries.tests.test_frequencies.TestFrequencyInference) ... ERROR
======================================================================
ERROR: test_invalid_index_types (pand... | {
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![eq1](https://cloud.githubusercontent.com/assets/2401026/10417648/45... | {
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] | closed | false | null | [] | null | 3 | 2015-10-11T16:38:59Z | 2015-10-13T11:56:45Z | 2015-10-12T15:59:52Z | NONE | null | Hi all,
I've enjoyed using pandas for a little while now. Thanks for developing such a useful and convenient tool!
A little nit has been nagging at me about pct_change function (and the .pct_change method of Series, DataFrame, etc.). If I run a sequence of numbers that increase by 100% (python 0.16.2):
``` python
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https://api.github.com/repos/pandas-dev/pandas/issues/11290 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11290/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11290/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11290/events | https://github.com/pandas-dev/pandas/issues/11290 | 110,894,327 | MDU6SXNzdWUxMTA4OTQzMjc= | 11,290 | Indexing a dataframe with a 2D boolean array? | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11291 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11291/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11291/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11291/events | https://github.com/pandas-dev/pandas/pull/11291 | 110,902,598 | MDExOlB1bGxSZXF1ZXN0NDczODMwNTg= | 11,291 | Fix mistake in Pytables querying with numpy scalar value. Fixes #11283 | {
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First PR to this project. The fix is minuscule, but let me know if I did anything awry.
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I'm just using 0.17 for testing exporting multiindex column dataframe. When i'm pivot table dataframe with X column as index (and without "columns" argument), **which will not create multiindex column**,
pivot table code (without columns argument):
```
df.pivot_table(index=["X"], columns=[], aggfunc={"Y": l... | {
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closes #10299
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Worked for this during PyCon JP 2015 pandas sprint /w @sinhrks
I found `test_frame.py:TestDataFrame.test_sort_index` cover this change.
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-10-12T11:30:23Z | 2015-10-13T12:25:28Z | 2015-10-13T12:25:28Z | NONE | null | Second tz_convert fails with AmbiguousTimeError ('UTC' in the example, but other timezones fail too).
EDIT: Actually it's not only second tz_convert that fails, it looks like most (if not all) of the .dt accessed properties are affected
``` python
t = pd.Series(pd.date_range('2015-01-01', '2016-01-01', freq='T'))
t =... | {
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I work on a dataframe with a multi index (Date, InputTime) and this dataframe may contain some NaN values in the columns (Value, Id). I want to fill forward value but by Date only and I don't find anyway to do this a in a very efficient way. I'm using Pandas 0.16.2 and numpy 1.9.2.
Here is the type of datafram... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11297 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11297/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11297/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11297/events | https://github.com/pandas-dev/pandas/issues/11297 | 110,977,221 | MDU6SXNzdWUxMTA5NzcyMjE= | 11,297 | test_expand_user failure in 0.17.0 | {
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"followers_url": "https://api.github.com/users/jorisva... | 7 | 2015-10-12T13:39:40Z | 2019-07-30T03:29:08Z | 2019-07-30T03:29:02Z | CONTRIBUTOR | null | ``` python
======================================================================
FAIL: test_expand_user (pandas.io.tests.test_common.TestCommonIOCapabilities)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.17.0/work... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11298 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11298/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11298/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11298/events | https://github.com/pandas-dev/pandas/issues/11298 | 110,977,361 | MDU6SXNzdWUxMTA5NzczNjE= | 11,298 | test_get_filepath_or_buffer_with_path fails in 0.17.0 | {
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] | closed | false | null | [] | null | 3 | 2015-10-12T13:40:38Z | 2015-11-26T14:05:41Z | 2015-11-26T14:05:41Z | CONTRIBUTOR | null | ``` python
======================================================================
FAIL: test_get_filepath_or_buffer_with_path (pandas.io.tests.test_common.TestCommonIOCapabilities)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/var/tmp/portage/dev-pyth... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11299 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11299/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11299/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11299/events | https://github.com/pandas-dev/pandas/issues/11299 | 110,982,319 | MDU6SXNzdWUxMTA5ODIzMTk= | 11,299 | pandas.io.tests.test_json.test_ujson.NumpyJSONTests testOdArray segfaults under python2.7/3.5 in 0.17.0 | {
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testOdArray (pandas.io.tests.test_json.test_ujson.NumpyJSONTests) ... Segmentation fault (core dumped)
```
``` python
In [2]: pd.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.10.final.0
python-bits: 64
OS: Linux
OS-release: 4.1.8-lh
machine: x86_64
processor: Intel(R) Core(TM) i7-... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11300 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11300/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11300/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11300/events | https://github.com/pandas-dev/pandas/pull/11300 | 110,987,537 | MDExOlB1bGxSZXF1ZXN0NDc0MjcxNzg= | 11,300 | BUG: GH10355 groupby std() no longer sqrts grouping cols | {
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... | closed | false | null | [] | null | 7 | 2015-10-12T14:40:57Z | 2019-02-14T05:23:36Z | 2015-11-05T12:57:18Z | NONE | null | closes #10355
Previously grouping columns were square rooted when as_index=False
New method closely follows the format of var() method.
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https://api.github.com/repos/pandas-dev/pandas/issues/11301 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11301/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11301/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11301/events | https://github.com/pandas-dev/pandas/pull/11301 | 111,002,906 | MDExOlB1bGxSZXF1ZXN0NDc0MzQ3MTQ= | 11,301 | BUG: Bug in tz-conversions with an ambiguous time and .dt accessors, #11295 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11302 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11302/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11302/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11302/events | https://github.com/pandas-dev/pandas/issues/11302 | 111,021,364 | MDU6SXNzdWUxMTEwMjEzNjQ= | 11,302 | Different precision calling .astype(str) on float numbers | {
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> > > import pandas as pd
> > > pd.DataFrame([1.12345678901234567890]).astype(str)
> > > 0
> > > 0 1.12345678901
With pandas 0.17:
> > > import pandas as pd
> > > pd.DataFrame([1.12345678901234567890]).astype(str)
> > > 0
> > > 0 1.1234567890123457
I read the... | {
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