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https://api.github.com/repos/pandas-dev/pandas/issues/9102 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9102/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9102/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9102/events | https://github.com/pandas-dev/pandas/pull/9102 | 52,320,807 | MDExOlB1bGxSZXF1ZXN0MjYyNzQ5Mjc= | 9,102 | BUG in read_csv when using skiprows on a file with CR line endings #9079 | {
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Fix the read_csv bug introduced in 6bf83c5d when using skiprows on a file with CR line terminators
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https://api.github.com/repos/pandas-dev/pandas/issues/9103 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9103/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9103/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9103/events | https://github.com/pandas-dev/pandas/issues/9103 | 52,340,655 | MDU6SXNzdWU1MjM0MDY1NQ== | 9,103 | `to_msgpack` throws "PackValueError: recursion limit exceeded." for unsupported objects. | {
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... | 2 | 2014-12-18T09:17:04Z | 2019-12-11T13:31:14Z | 2019-12-11T13:31:14Z | CONTRIBUTOR | null | The following call fails with a `PackValueError: recursion limit exceeded.`, spamming the console with references to `pandas.msgpack.Packer._pack` lines `3295` and `2391`:
```
df = pd.DataFrame([0], index=[datetime.time(1, 2, 3)])
df.to_msgpack()
```
This also happens for other unsupported data like a custom object `... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9104 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9104/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9104/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9104/events | https://github.com/pandas-dev/pandas/pull/9104 | 52,353,420 | MDExOlB1bGxSZXF1ZXN0MjYyOTM2Mjg= | 9,104 | BUG: Bug in DatetimeIndex iteration, related to (GH8890), fixed in (GH9100) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9105 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9105/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9105/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9105/events | https://github.com/pandas-dev/pandas/pull/9105 | 52,366,881 | MDExOlB1bGxSZXF1ZXN0MjYzMDE5MDQ= | 9,105 | Refs BUG-9099: Support simultaneous copy and dtype args in DataFrame init | {
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This is a somewhat brute-force fix for supporting copy and dtype arguments in DataFrame constructor. Some data might be copied twice if both arguments are set, but if I did the operations in a different order, one other unit test would fail.
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https://api.github.com/repos/pandas-dev/pandas/issues/9106 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9106/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9106/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9106/events | https://github.com/pandas-dev/pandas/issues/9106 | 52,414,744 | MDU6SXNzdWU1MjQxNDc0NA== | 9,106 | DataFrame.replace with inplace=True fails when column names are not unique | {
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... | 13 | 2014-12-18T20:52:51Z | 2021-10-29T02:17:28Z | null | NONE | null | - [ ] replace should not itself do anything internally w.r.t. chained indexing (should be slightly refactored)
- [ ] might need a test to show the `SettingWithCopyWarning` on this example
``` python
data = pd.DataFrame.from_items([(0, ['a', 'b', 'c']), (0, ['1', '2', '3'])])
data.index=['<3', 'u', 'i']
index_order = [... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9107 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9107/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9107/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9107/events | https://github.com/pandas-dev/pandas/issues/9107 | 52,429,762 | MDU6SXNzdWU1MjQyOTc2Mg== | 9,107 | to_datetime returns NaT for old dates with coerce=True | {
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"followers_url": "https://api.github.com/users/wesm... | 4 | 2014-12-18T23:25:59Z | 2019-09-12T12:50:29Z | 2019-09-12T12:50:29Z | CONTRIBUTOR | null | When use `coerce=True` in `pandas.to_datetime` old dates (before 1677-09-22) return NaT. The same dates without `coerce` are parsed correctly:
```
print pd.to_datetime('13000101', format='%Y%m%d', coerce=True)
print pd.to_datetime('13000101', format='%Y%m%d')
```
returns
```
NaT
1300-01-01 00:00:00
```
pandas: 0.1... | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-12-19T15:39:55Z | 2014-12-20T22:05:18Z | 2014-12-20T22:05:18Z | MEMBER | null | Added a `SetUpClass` to skip the full class when no connection can be made to the database, and made some of the other methods class methods, to be able to use them in `SetUpClass`
Eg if you are testing locally and don't have one of the databases available, then it will test the connection and skip each individual tes... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9111 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9111/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9111/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9111/events | https://github.com/pandas-dev/pandas/issues/9111 | 52,547,981 | MDU6SXNzdWU1MjU0Nzk4MQ== | 9,111 | StringMethods should have the same methods as standard str | {
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"closed_at": "2015-06-13T17:49:05Z",
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"followers_url": "https://api.github.... | 6 | 2014-12-20T02:03:31Z | 2015-06-09T12:24:19Z | 2015-06-09T00:39:23Z | MEMBER | null | Should `StringMethods` be compatible with standard `str`, or have only useful methods? Sometimes I have to adjust text formats before converting other types, and I've chosen additionals which makes formatting / adjustments easier. Any ideas?
- [x] `str.find` (#9386)
- [x] `str.rfind` (#9386)
- [x] `str.isalnum` (#9282)... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9112 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9112/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9112/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9112/events | https://github.com/pandas-dev/pandas/pull/9112 | 52,548,801 | MDExOlB1bGxSZXF1ZXN0MjY0MTA5MDI= | 9,112 | API: Index.duplicated should return np.array | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-12-20T02:31:55Z | 2015-02-15T03:26:28Z | 2014-12-20T20:10:58Z | MEMBER | null | For 2nd issue of #8875.
- Change `Index.duplicated` to return `np.array`.
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https://api.github.com/repos/pandas-dev/pandas/issues/9113 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9113/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9113/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9113/events | https://github.com/pandas-dev/pandas/issues/9113 | 52,552,774 | MDU6SXNzdWU1MjU1Mjc3NA== | 9,113 | BUG: replace int64 dtype with bool coerces to int64 | {
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"de... | closed | false | null | [] | {
"closed_at": "2020-01-30T12:18:05Z",
"closed_issues": 2207,
"created_at": "2012-09-13T02:13:00Z",
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2014-12-20T05:23:50Z | 2019-11-03T01:42:18Z | 2019-11-03T01:42:18Z | MEMBER | null | ```
# NG
s = pd.Series([1, 2, 3])
s.replace(2, True)
#0 1
#1 1
#2 3
# dtype: int64
```
If target has `object` dtype, it works.
```
s = pd.Series(['x', 2, 3])
s.replace(2, True)
#0 x
#1 True
#2 3
# dtype: object
```
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https://api.github.com/repos/pandas-dev/pandas/issues/9114 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9114/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9114/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9114/events | https://github.com/pandas-dev/pandas/issues/9114 | 52,557,767 | MDU6SXNzdWU1MjU1Nzc2Nw== | 9,114 | BUG: datetime64[us] arrays with NaT cannot be cast to DatetimeIndex | {
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... | closed | false | null | [] | {
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In [11]: t = pd.to_datetime(['2000-01-01T00:00', 'NaT']).values.astype('datetime64[us]')
In [12]: pd.DatetimeIndex(t)
OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 294247-01-09 19:59:05
In [13]: pd.to_datetime(t)
Out[13]:
<class 'pandas.tseries.index.DatetimeIndex'>
[2000-01-01, NaT]
Length: 2, Freq: N... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9115 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9115/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9115/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9115/events | https://github.com/pandas-dev/pandas/issues/9115 | 52,574,621 | MDU6SXNzdWU1MjU3NDYyMQ== | 9,115 | TST: wb test failing | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-12-20T19:46:39Z | 2014-12-23T03:13:20Z | 2014-12-23T03:13:20Z | CONTRIBUTOR | null | cc @jnmclarty
can you take a look
```
FSS.S
======================================================================
FAIL: test_wdi_download (pandas.io.tests.test_wb.TestWB)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/Users/jreback/pandas/pandas/ut... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9116 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9116/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9116/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9116/events | https://github.com/pandas-dev/pandas/pull/9116 | 52,577,147 | MDExOlB1bGxSZXF1ZXN0MjY0MjEwNjA= | 9,116 | API: Datetime-like indexes `summary` should output the same format | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2014-12-20T21:26:08Z | 2015-01-17T03:34:52Z | 2015-01-05T23:48:24Z | MEMBER | null | Related to #6469. Made all datetime-like indexes `summary` should output the same format.
#### Before
```
didx = pd.date_range('2014-12-20', freq='M', periods=3)
pidx = pd.period_range('2014-12-20', freq='M', periods=3)
tdidx = pd.timedelta_range(start='1 days', freq='D', periods=3)
didx.summary()
# DatetimeIndex: 3 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9117 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9117/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9117/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9117/events | https://github.com/pandas-dev/pandas/pull/9117 | 52,577,792 | MDExOlB1bGxSZXF1ZXN0MjY0MjEzMzM= | 9,117 | ENH: get_dummies can accept value and na_value kw | {
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"followers_url": "https://api.github.com/users/jorisva... | 12 | 2014-12-20T21:55:54Z | 2015-11-14T05:26:47Z | 2015-05-11T14:55:18Z | MEMBER | null | Closes #8028. It is still under work, but want to clarify a point. Currently it works as:
```
s = pd.Series(['A', 'B', 'A', 'C'])
s
#0 A
#1 B
#2 A
#3 C
# dtype: object
pd.get_dummies(s)
# A B C
#0 1 0 0
#1 0 1 0
#2 1 0 0
#3 0 0 1
pd.get_dummies(s, value='YES', na_value='NO')
# A ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9118 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9118/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9118/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9118/events | https://github.com/pandas-dev/pandas/issues/9118 | 52,578,162 | MDU6SXNzdWU1MjU3ODE2Mg== | 9,118 | BLD: drop support for python 3.2 | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-12-20T22:09:48Z | 2015-06-22T08:46:37Z | 2015-06-22T08:46:37Z | CONTRIBUTOR | null | someone want to sample the scientific stack and see who still supoorts 3.2?
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https://api.github.com/repos/pandas-dev/pandas/issues/9119 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9119/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9119/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9119/events | https://github.com/pandas-dev/pandas/issues/9119 | 52,580,498 | MDU6SXNzdWU1MjU4MDQ5OA== | 9,119 | BUG: Resampling a TZ-aware Series fails if rule='W': "Values falls before first bin" | {
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"followers_url": "https://api.github... | 3 | 2014-12-20T23:50:47Z | 2018-10-03T15:25:45Z | 2018-10-03T15:25:45Z | CONTRIBUTOR | null | ``` python
In [1]: import pandas as pd
In [2]: rng = pd.date_range("2013-04-01", "2013-05-01", tz='Europe/London', freq='H')
In [4]: series = pd.Series(index=rng)
In [6]: series.resample('W')
---------------------------------------------------------------------------
ValueError Traceba... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9120 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9120/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9120/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9120/events | https://github.com/pandas-dev/pandas/pull/9120 | 52,582,089 | MDExOlB1bGxSZXF1ZXN0MjY0MjI5MjY= | 9,120 | fix an nbviewer link in tutorials | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9121 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9121/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9121/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9121/events | https://github.com/pandas-dev/pandas/issues/9121 | 52,592,233 | MDU6SXNzdWU1MjU5MjIzMw== | 9,121 | Enable Sourcegraph | {
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I want to use [Sourcegraph code search and code review](https://sourcegraph.com) with pandas. A project maintainer needs to enable it to set up a webhook so the code is up-to-date there.
Could you please enable pandas on @Sourcegraph by going to https://sourcegraph.com/github.com/pydata/pandas and clicking on ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9122 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9122/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9122/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9122/events | https://github.com/pandas-dev/pandas/pull/9122 | 52,598,424 | MDExOlB1bGxSZXF1ZXN0MjY0MjkxMDk= | 9,122 | Remove bar line | {
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Closes https://github.com/pydata/pandas/issues/7128
Votes on whether we should
1. Remove the line entirely
2. Add a parameter to `.plot` control whether the line should be added.
I vote for 1, but I can go either way.
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https://api.github.com/repos/pandas-dev/pandas/issues/9123 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9123/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9123/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9123/events | https://github.com/pandas-dev/pandas/pull/9123 | 52,602,717 | MDExOlB1bGxSZXF1ZXN0MjY0MzA4MTI= | 9,123 | Use tz.gettz() instead of zoneinfo.gettz() | {
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"followers_url": "https://api.github.... | 14 | 2014-12-21T18:45:24Z | 2015-06-02T19:26:59Z | 2015-05-15T20:26:37Z | CONTRIBUTOR | null | zoneinfo.gettz() seems to have problems (1 & 2) on system which do not install
the zoninfo tarball (e.g. Debian, Gentoo and Fedora) but rely on the system
zoneinfo files. This results in test failures (3 & 4)
tz.gettz() doesn't suffer from this problem.
1 https://github.com/dateutil/dateutil/issues/8
2 https://github.... | {
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From an API design and discoverability perspective, this seems less than ideal. If we had separate methods, standard introspection tools like IPython and autocomplete could help users figure out whi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9125 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9125/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9125/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9125/events | https://github.com/pandas-dev/pandas/pull/9125 | 52,610,197 | MDExOlB1bGxSZXF1ZXN0MjY0MzM5NjU= | 9,125 | PERF: use labels to find duplicates in multi-index | {
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-------------------------------------------------------------------------------
Test name | head[ms] | base[ms] | ratio |
-------------------------------------------------------------------------------
multiindex_duplicated | 139.2883 | 469.6666 | 0.296... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9126 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9126/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9126/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9126/events | https://github.com/pandas-dev/pandas/issues/9126 | 52,622,684 | MDU6SXNzdWU1MjYyMjY4NA== | 9,126 | Why is DataFrame.loc[[1]] 1,800x slower than df.ix [[1]] and 3,500x than df.loc[1]? | {
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s=pd.Series(xrange(5000000))
%timeit s.loc[[0]] # You need pandas 0.15.1 or newer for it to be that slow
1 loops, best of 3: 445 ms per loop
Also see the question and the answer here: http://stackoverflow.com/questions/27596832/why-is-dataframe-loc1-1-800x-slower-than-df-ix-1-and-3-500x-than-df-loc... | {
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```
-------------------------------------------------------------------------------
Test name | head[ms] | base[ms] | ratio |
-------------------------------------------------------------------------------
series_loc_list_like | 0.2840 | 125.0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9128 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9128/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9128/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9128/events | https://github.com/pandas-dev/pandas/pull/9128 | 52,643,310 | MDExOlB1bGxSZXF1ZXN0MjY0NTI3MTg= | 9,128 | ENH: Expanduser in to_file methods GH9066 | {
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First time contributor, tried to follow all rules as good as possible.
If something is missing please let me know.
As specified in task 9066 tilde in a pathname get resolved into a absolute path.
In case the object is a buffer the buffer will be returned.
I did not add additional tests, since I could no... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9129 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9129/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9129/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9129/events | https://github.com/pandas-dev/pandas/issues/9129 | 52,649,462 | MDU6SXNzdWU1MjY0OTQ2Mg== | 9,129 | isnull not detecting NaT in PeriodIndex | {
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"description": "np.nan, pd.NaT, pd.NA, d... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-12-22T13:29:35Z | 2014-12-23T03:22:57Z | 2014-12-23T03:22:57Z | CONTRIBUTOR | null | ```
In [158]: x = pd.to_datetime([np.nan, '2000-1-1'])
In [159]: y = x.to_period(freq='m')
In [160]: y
Out[160]:
<class 'pandas.tseries.period.PeriodIndex'>
[NaT, 2000-01]
Length: 2, Freq: M
In [161]: pd.isnull(x)
Out[161]: array([ True, False], dtype=bool)
In [162]: pd.isnull(y)
Out[162]: array([False, False], dt... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9130 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9130/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9130/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9130/events | https://github.com/pandas-dev/pandas/pull/9130 | 52,663,287 | MDExOlB1bGxSZXF1ZXN0MjY0NjUxMDE= | 9,130 | PERF: json support for blocks GH9037 | {
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"followers_url": "https://api.github.com/users/jr... | 19 | 2014-12-22T16:13:48Z | 2014-12-24T18:27:30Z | 2014-12-24T15:53:17Z | CONTRIBUTOR | null | This adds block support to the JSON serialiser, as per #9037. I also added code to directly cast and serialise numpy data, which replaces the previous use of intermediate Python objects.
Large performance improvement (~25x) for mixed frames containing datetimes / timedeltas.
```
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https://api.github.com/repos/pandas-dev/pandas/issues/9131 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9131/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9131/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9131/events | https://github.com/pandas-dev/pandas/issues/9131 | 52,671,184 | MDU6SXNzdWU1MjY3MTE4NA== | 9,131 | DataFrame constructor acts differently with lists and Numpy arrays | {
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] | closed | false | null | [] | null | 5 | 2014-12-22T17:38:25Z | 2014-12-23T10:49:50Z | 2014-12-23T10:49:50Z | CONTRIBUTOR | null | Hello,
I noticed a strange behavior when a Numpy array is given to a Pandas DataFrame constructor.
I don't know really if it should be considered as an issue (or a feature)...
but anyway a tip to fix this will be nice.
```
import pandas as pd
import numpy as np
lst = [{'a':1, 'b':2}, {'a':3, 'b':2, 'c':3}]
In []: pd... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9132 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9132/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9132/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9132/events | https://github.com/pandas-dev/pandas/issues/9132 | 52,679,834 | MDU6SXNzdWU1MjY3OTgzNA== | 9,132 | BUG: Series datatypes not preserved in DataFrame constructor | {
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"color": "AD7... | closed | false | null | [] | null | 6 | 2014-12-22T19:24:19Z | 2014-12-23T14:19:49Z | 2014-12-22T19:36:50Z | CONTRIBUTOR | null | There is an inconsistency apparently in the way dtypes are parsed when DataFrames are created from Series:
```
>>> import pandas as pd
>>> df = pd.DataFrame({'f':pd.Series([1.5,], dtype='float32'), 'i':pd.Series([1,], dtype='int32')})
>>> df.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 1 entries, 0 to 0
Da... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9133 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9133/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9133/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9133/events | https://github.com/pandas-dev/pandas/issues/9133 | 52,680,039 | MDU6SXNzdWU1MjY4MDAzOQ== | 9,133 | ENH: Enable passing in dict to specify datatypes to DataFrame constructor | {
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"color": "AD7... | closed | false | null | [] | null | 2 | 2014-12-22T19:26:32Z | 2014-12-22T19:38:42Z | 2014-12-22T19:37:48Z | CONTRIBUTOR | null | The following seems like very natural syntax to specify the dtypes of various columns passed into the DataFrame constructor:
```
df = pd.DataFrame({'a':[1,2,3], 'b':[2.5,3.5,6.7]}, dtype={'a':'int32','b':'float32'})
```
However, right now it raises an error. Perhaps something worth implementing? See also http://sta... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9134 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9134/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9134/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9134/events | https://github.com/pandas-dev/pandas/pull/9134 | 52,688,087 | MDExOlB1bGxSZXF1ZXN0MjY0ODA1NzM= | 9,134 | PERF: use unique and isnull in nunique instead of value_counts. | {
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Currently, `Series.nunique` [(source)](https://github.com/pydata/pandas/blob/master/pandas/core/base.py#L429) calls `Series.value_counts` [(source)](https://github.com/pydata/pandas/blob/master/pandas/core/base.py#L371), which by default, sorts the values.
Counting unique values certainly doesn't requir... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9135 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9135/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9135/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9135/events | https://github.com/pandas-dev/pandas/pull/9135 | 52,693,319 | MDExOlB1bGxSZXF1ZXN0MjY0ODM4Mjg= | 9,135 | fixup unicode compat with 3.2 in test_index.py | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9136 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9136/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9136/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9136/events | https://github.com/pandas-dev/pandas/pull/9136 | 52,698,188 | MDExOlB1bGxSZXF1ZXN0MjY0ODY4MDU= | 9,136 | Remove codepath asymmetry in dataframe count() | {
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"followers_url": "https://api.github.com/users/jr... | 11 | 2014-12-22T23:05:39Z | 2014-12-24T15:55:26Z | 2014-12-24T15:55:19Z | CONTRIBUTOR | null | @jreback I noticed a codepath asymmetry in core.frame.count that leads to a substantial difference in dropna() performance depending on the axis. Using the path `df.dropna(axis=0)` takes yields a 2.5-5x improvement.
```
$ python vb_suite/test_perf.py -b upstream/master -t HEAD -r "dropna" -S -n 30
Invoked with :
--nca... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9137 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9137/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9137/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9137/events | https://github.com/pandas-dev/pandas/pull/9137 | 52,706,875 | MDExOlB1bGxSZXF1ZXN0MjY0OTE4OTk= | 9,137 | TST: Fix failing test due to revision in WB data #9115 | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-12-23T01:41:05Z | 2015-02-09T00:37:14Z | 2014-12-23T03:13:20Z | CONTRIBUTOR | null | Closes #9115
I just round the expected and result data for the failing test. I have no idea why the WB would be revising 2003 and 2004 data, but they did.
I would have redesigned the test, but spending that time has minimal benefit.
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https://api.github.com/repos/pandas-dev/pandas/issues/9138 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9138/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9138/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9138/events | https://github.com/pandas-dev/pandas/pull/9138 | 52,729,587 | MDExOlB1bGxSZXF1ZXN0MjY1MDM4MDk= | 9,138 | FIX: to_sql dtype argument accepting SQLAlchemy type instance (GH9083) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9139 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9139/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9139/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9139/events | https://github.com/pandas-dev/pandas/issues/9139 | 52,758,265 | MDU6SXNzdWU1Mjc1ODI2NQ== | 9,139 | to_excel incorrectly sets time to midnight for exported datetime column | {
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I try this:
```
import requests
from pandas.io.json import json_normalize
import json
import pandas as pd
response = requests.get("http://api.openweathermap.org/data/2.5/history/station?start=1356220800&end=1356307200&type=hour&id=5530")
df = json_normalize(json.loads(response.text)['list'])
df['dt'] = pd.to_d... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9140 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9140/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9140/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9140/events | https://github.com/pandas-dev/pandas/issues/9140 | 52,762,010 | MDU6SXNzdWU1Mjc2MjAxMA== | 9,140 | Referencing a panel with an object causes an inf loop in 0.15.2 | {
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```
import pandas
import numpy
class TestObject:
def __str__(self):
return "TestObject"
obj = TestObject()
wp = pandas.Panel(numpy.random.randn(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9141 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9141/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9141/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9141/events | https://github.com/pandas-dev/pandas/pull/9141 | 52,769,270 | MDExOlB1bGxSZXF1ZXN0MjY1Mjg1MjA= | 9,141 | Check whether GBQ Job is finished | {
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"followers_url": "https://api.github.com/users/jr... | 8 | 2014-12-23T19:46:31Z | 2015-01-18T21:09:18Z | 2015-01-18T21:09:11Z | CONTRIBUTOR | null | xref #8728
jobComplete can be False in query_reply. Simply checking for the existence of the field isn't enough, as a False value will cause a KeyError when checking for query_reply['totalRows']
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https://api.github.com/repos/pandas-dev/pandas/issues/9142 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9142/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9142/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9142/events | https://github.com/pandas-dev/pandas/issues/9142 | 52,785,946 | MDU6SXNzdWU1Mjc4NTk0Ng== | 9,142 | Object indexes on the items/info axis of Panel | {
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``` python
import pandas as pd
import numpy as np
class Key:
def __init__(self, name, id):
self.name = name
self.id = id
def __repr__(self):
return "Key(name={name}, id={id})".format(**... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9143 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9143/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9143/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9143/events | https://github.com/pandas-dev/pandas/pull/9143 | 52,790,202 | MDExOlB1bGxSZXF1ZXN0MjY1NDE3Nzk= | 9,143 | BUG: Bug in Panel indexing with an object-like (GH9140) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9144 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9144/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9144/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9144/events | https://github.com/pandas-dev/pandas/issues/9144 | 52,794,133 | MDU6SXNzdWU1Mjc5NDEzMw== | 9,144 | Wired behavior: 0 / dataframe = inf while 0.0 / dataframe = 0.0 | {
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"description": "Unexpected or buggy dtyp... | closed | false | null | [] | {
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In [3]: s = pd.Series([1.0, 2.0])
In [4]: 0 / s
Out[4]:
0 inf
1 inf
dtype: float64
In [5]: 0.0 / s
Out[5]:
0 0
1 0
dtype: float64
```
This is seems quite wired. Should not 0/s be 0 as well?
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... | 6 | 2014-12-24T08:18:37Z | 2020-05-07T22:14:01Z | 2020-05-07T22:14:01Z | CONTRIBUTOR | null | Hello,
try
```python
import requests
from pandas.io.json import json_normalize
import json
import pandas as pd
response = requests.get("http://api.openweathermap.org/data/2.5/history/station?start=1356220800&end=1356307200&type=hour&id=5530")
df = json_normalize(json.loads(response.text)['list'])
df['dt'] ... | {
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"followers_url": "https://api.github.com/users/j... | 3 | 2014-12-24T18:19:01Z | 2018-01-06T17:33:07Z | 2018-01-06T17:33:07Z | CONTRIBUTOR | null | Add a round-trippable json orient (maybe "roundtrip") to provide enough metadata to reconstruct a frame or series with 100% fidelity. As discussed in #9130
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... | 2 | 2014-12-24T18:26:46Z | 2019-08-27T18:45:52Z | 2019-08-27T18:45:52Z | CONTRIBUTOR | null | To explicitly encourage / support serialisation of other objects (e.g. numpy arrays) and better support custom JSON serialisation of Pandas types. As discussed in #9130.
Would welcome more thoughts / ideas on this. Not 100% sold myself.
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To reproduce: (my dataset is 60 cols, 100000 rows)
I imported a csv and one column was all null (np.nan). The column dtype was set to object. (that's one issue, wh... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9150 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9150/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9150/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9150/events | https://github.com/pandas-dev/pandas/issues/9150 | 52,835,373 | MDU6SXNzdWU1MjgzNTM3Mw== | 9,150 | Runtime terminate it in an unusual way | {
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Running any python script with the pandas produce 'Runtime to terminate it in an unusual way'
To reproduce the error use:
- Pandas version 0.15.2, C Python
- Python 2.7.6 (default, Nov 10 2013, 19:24:18) [MSC v.1500 32 bit (Intel)] on win32
- SO windows 7
create a python script (myfile.py)... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9151 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9151/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9151/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9151/events | https://github.com/pandas-dev/pandas/pull/9151 | 52,840,621 | MDExOlB1bGxSZXF1ZXN0MjY1NzA2MDY= | 9,151 | PERF: improves merge performance when key space exceeds i8 bounds | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2014-12-24T23:50:09Z | 2014-12-29T15:43:56Z | 2014-12-28T23:43:38Z | CONTRIBUTOR | null | In join operations, current master switches to [a less efficient path](https://github.com/pydata/pandas/blob/def58c9bcabd5bda63696a30f25d4012ab1160ac/pandas/tools/merge.py#L471) if the key space exceeds `int64` bounds. This commit improves performance and memory usage:
on master:
```
In [1]: np.random.seed(2718281)
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https://api.github.com/repos/pandas-dev/pandas/issues/9153 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9153/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9153/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9153/events | https://github.com/pandas-dev/pandas/issues/9153 | 52,857,149 | MDU6SXNzdWU1Mjg1NzE0OQ== | 9,153 | import pandas hangs save file matplotlib dialog | {
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``` python
import pandas
import matplotlib.pyplot as plt
plt.plot([1, 2, 3])
plt.show()
```
freezes matplotlib file save dialog (the same issue with wxpython FilePickerCtrl).
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I did
```python
import numpy as np
import pandas as pd
from matplotlib.pyplot as plt
idx = pd.date_range('20140101', '20140201')
df = pd.DataFrame(index=idx)
df['col0'] = np.random.randn(len(idx))
s_idx = pd.Series(idx, index=idx) # need to do this because we can't shift index
diff_idx = (s_idx-s... | {
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"description": "read_excel, to_excel",
"id": 49254273,
"name": "IO Excel",
"node_id": "MDU6TGFiZWw0OTI1NDI3Mw==",
"url": "https://api.github.com/repos/pandas-dev/pandas/labels/IO%20Excel"
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"followers_url": "https://api.github.com/users/j... | 4 | 2014-12-26T10:07:40Z | 2018-01-27T16:56:34Z | 2018-01-27T16:56:34Z | CONTRIBUTOR | null | Hello,
`to_excel` method with `engine='xlwt'` doesn't support `pandas.tslib.Timedelta`
```
import numpy as np
import pandas as pd
idx = pd.date_range('20140101', '20140201')
df = pd.DataFrame(index=idx)
df['col0'] = np.random.randn(len(idx))
s_idx = pd.Series(idx, index=idx)
diff_idx = (s_idx-s_idx.shift(1)).fillna(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9156 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9156/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9156/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9156/events | https://github.com/pandas-dev/pandas/issues/9156 | 52,938,033 | MDU6SXNzdWU1MjkzODAzMw== | 9,156 | ValueError: setting an array element with a sequence. | {
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] | closed | false | null | [] | null | 13 | 2014-12-26T20:31:30Z | 2014-12-28T04:04:26Z | 2014-12-27T17:55:50Z | CONTRIBUTOR | null | This works fine:
```
In [24]: np.asarray(np.array([np.asarray([10, 20])]), np.float32)
Out[24]:
array([[ 10., 20.]], dtype=float32)
```
but this does not work:
```
In [25]: np.asarray(pd.Series([np.asarray([10, 20])]), np.float32)
---------------------------------------------------------------------------
ValueErr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9157 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9157/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9157/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9157/events | https://github.com/pandas-dev/pandas/issues/9157 | 52,952,632 | MDU6SXNzdWU1Mjk1MjYzMg== | 9,157 | Clearer error message for pd.concat if empty iterator is passed | {
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"followers_url": "https://api.github.com/users/jr... | 9 | 2014-12-27T09:12:06Z | 2019-12-12T23:13:35Z | 2015-08-15T17:05:31Z | CONTRIBUTOR | null | I just saw following problem on stackoverflow: http://stackoverflow.com/questions/27665560/concatenating-files-with-python-pandas
It is not possible to concatenate an empty sequence of data frames.
This tiny code fragment
```
import pandas as pd
dfs = []
pd.concat(dfs)
```
Throws following error:
```
/Users/ch/min... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9158 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9158/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9158/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9158/events | https://github.com/pandas-dev/pandas/issues/9158 | 52,957,258 | MDU6SXNzdWU1Mjk1NzI1OA== | 9,158 | x tick labels not shown when using secondary_y=True on figure with multiple subplots | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-12-27T13:38:05Z | 2015-04-20T18:41:21Z | 2015-04-20T18:41:21Z | NONE | null | This worked on 0.15.1, but not anymore on 0.15.2:
``` python
import pandas as pd
d = {'A' : [1., 2., 3., 4.], 'B' : [4., 3., 2., 1.], 'C': [5, 1, 3, 4]}
df = pd.DataFrame(d, index=pd.date_range('2014 10 11', '2014 10 14'))
axes = df[['A','B']].plot(subplots=True)
df['C'].plot(ax=axes[0], secondary_y=True) # x tick ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9159 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9159/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9159/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9159/events | https://github.com/pandas-dev/pandas/issues/9159 | 52,959,580 | MDU6SXNzdWU1Mjk1OTU4MA== | 9,159 | Add shuffling behavior / utility method | {
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"description": "D... | closed | false | null | [] | null | 1 | 2014-12-27T15:35:55Z | 2014-12-27T17:58:58Z | 2014-12-27T17:58:50Z | CONTRIBUTOR | null | Ideally some utility method that works to shuffle both dataframes, series and numpy arrays.
For example to shuffle a Dataframe: df.ix[shuffle(df.index)].
See https://github.com/scikit-learn/scikit-learn/issues/4008 for discussion.
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https://api.github.com/repos/pandas-dev/pandas/issues/9160 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9160/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9160/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9160/events | https://github.com/pandas-dev/pandas/issues/9160 | 52,959,618 | MDU6SXNzdWU1Mjk1OTYxOA== | 9,160 | Feature request: quick way to save a plot to file. | {
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"description": nul... | closed | false | null | [] | null | 2 | 2014-12-27T15:37:59Z | 2014-12-27T18:32:14Z | 2014-12-27T18:32:14Z | NONE | null | I rarely use Pandas without calling some_dataframe.plot() at the end of some processing.
Saving a plot to disk is a very common requirement.
Having a handy df.plot(save_as="filename") would feel very natural.
By the way, the figsize keyword requires a tuple in inches. It would be nice to support sizes in pixels as well... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9161 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9161/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9161/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9161/events | https://github.com/pandas-dev/pandas/issues/9161 | 52,969,171 | MDU6SXNzdWU1Mjk2OTE3MQ== | 9,161 | area plots are causing my unit tests to fail | {
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... | 9 | 2014-12-28T00:11:19Z | 2016-08-10T12:25:06Z | 2016-08-10T12:25:06Z | NONE | null | I'm using the latest matplotlib and pandas. If you run the following code, do the legends look right to you? The unit tests don't like them.
``` python
df = DataFrame(
np.random.rand(10, 3),
index=list(string.ascii_letters[:10]))
df.plot(kind='area', subplots=True, sharex=True, legend=True)
`... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9162 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9162/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9162/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9162/events | https://github.com/pandas-dev/pandas/issues/9162 | 52,971,279 | MDU6SXNzdWU1Mjk3MTI3OQ== | 9,162 | NDFrame Virtualization | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2014-12-28T02:50:28Z | 2020-01-01T16:02:30Z | 2020-01-01T15:54:42Z | CONTRIBUTOR | null | I had mentioned this at one of the pydata talks. Just to put a couple of ideas down.
Currently the internal structure of a `NDFrame` is a collection of `Block` objects, managed by a `BlockManager`. Each of these is a nd-dim array of a single dtype (generally these are the same dim as the parent object, eg. a DataFrame... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9163 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9163/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9163/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9163/events | https://github.com/pandas-dev/pandas/pull/9163 | 52,976,686 | MDExOlB1bGxSZXF1ZXN0MjY2MjIxNDg= | 9,163 | PERF: Utilize mixed dtypes in df.count() with MultiIndexes | {
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Basically, we're transposing a potentially mixed-type frame before calling `notnull(frame.values)`; the same result can be obtained by deferring the transpose until after `notnull` gives us a non-mixed frame.
Here are the vbench res... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9164 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9164/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9164/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9164/events | https://github.com/pandas-dev/pandas/pull/9164 | 52,982,304 | MDExOlB1bGxSZXF1ZXN0MjY2MjQ0NzQ= | 9,164 | BUG: hidden ticklabels with sharex and secondary | {
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``` python
import pandas as pd
d = {'A' : [1., 2., 3., 4.], 'B' : [4., 3., 2., 1.], 'C': [5, 1, 3, 4]}
df = pd.DataFrame(d, index=pd.date_range('2014 10 11', '2014 10 14'))
axes = df[['A','B']].plot(subplots=True)
df['C'].plot(ax=axes[0], secondary_y=True) # x tic... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9165 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9165/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9165/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9165/events | https://github.com/pandas-dev/pandas/issues/9165 | 53,008,666 | MDU6SXNzdWU1MzAwODY2Ng== | 9,165 | DOC: missing apt.rst links | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2014-12-28T20:12:12Z | 2015-08-06T11:23:55Z | 2014-12-29T14:06:30Z | CONTRIBUTOR | null | might be nice to adapt this scipy script: https://github.com/scipy/scipy/blob/master/tools/refguide_check.py
- To find all things that are not documented
- make an issue so they can get fixed.
- add this procedure to the wiki
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This doesn't affect spreadsheets created with `to_excel()`. However, it does prevent the user from overwriting the cell format with a column format.
For example consider the following program... | {
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```
some_quantity
timestamp
2014-10-06 18:00:40.063000-04:00 0.568000
2014-10-06 18:00:41.361000-04:00 3.014770
2014-10-06 18:00:42.896000-04:00 0.878154
2014-10-06 18:00:43.040000-04:00 0.723077
2014-10-06 18:00:44.791... | {
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code changes were done in https://github.com/pydata/pandas/pull/9101 and https://github.com/pydata/pandas/pull/9061. just adding tests to confirm bugs reported there are handled.
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https://api.github.com/repos/pandas-dev/pandas/issues/9170 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9170/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9170/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9170/events | https://github.com/pandas-dev/pandas/issues/9170 | 53,091,477 | MDU6SXNzdWU1MzA5MTQ3Nw== | 9,170 | Index._shallow_copy does not handle data types | {
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] | closed | false | null | [] | null | 1 | 2014-12-30T03:55:22Z | 2015-01-02T15:43:23Z | 2015-01-02T15:43:15Z | CONTRIBUTOR | null | integer index with float data types:
```
>>> i
Int64Index([1, 2], dtype='int64')
>>> i._shallow_copy(i.values.astype('f8'))
Int64Index([1.0, 2.0], dtype='float64')
```
another issue: an index which is not equal to its copy:
```
>>> i
Float64Index([1.0, 2.0], dtype='float64')
>>> j = i._shallow_copy(i.values.astype('... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9171 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9171/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9171/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9171/events | https://github.com/pandas-dev/pandas/pull/9171 | 53,092,855 | MDExOlB1bGxSZXF1ZXN0MjY2NzM0Mjc= | 9,171 | BUG: Fix for extraneous default cell format in xlsxwriter files. | {
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'General' format to cells if no other format is applied. This
isn't a bug, per se, but it prevents other row or column formatting.
closes #9167
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This is a first attempt to improve the error message when trying to concat an empty list/set of objects:
`pd.concat([])` currently raises following error:
```
/Users/ch/miniconda/envs/sci33/lib/python3.3/site-packages/pandas/tools/merge.py in __init__(self, objs, axis, join, join_axes, keys, levels, na... | {
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... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-12-30T14:24:52Z | 2015-03-11T12:10:42Z | 2015-03-11T12:10:42Z | NONE | null | I just upgraded to pandas 0.15.2 and now hit this when I do resample. It worked fine in 0.15.1 (I rolled back to 0.15.1 to confirm). As far as I can tell it occurs when the first date in the index is during daylight savings and the last is not, or vice versa.
For example, with a date just before and another just afte... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9174 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9174/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9174/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9174/events | https://github.com/pandas-dev/pandas/issues/9174 | 53,130,104 | MDU6SXNzdWU1MzEzMDEwNA== | 9,174 | mean of series of dataframes gives TypeError | {
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``` python
import pandas as pd
import numpy... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9175 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9175/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9175/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9175/events | https://github.com/pandas-dev/pandas/pull/9175 | 53,164,314 | MDExOlB1bGxSZXF1ZXN0MjY3MTM2Mjk= | 9,175 | BUG: Fix for Timestamp handling in xlwt and xlsxwriter engines. | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2014-12-31T03:04:58Z | 2015-01-15T02:35:28Z | 2015-01-15T02:35:28Z | CONTRIBUTOR | null | Fix for writing Timestamp objects using the xlwt and xlsxwriter
engines. Both modules write Excel dates and times using
datetime.timedelta which differs from pandas.Timedelta. This
fix coerces Timestamp objects to datetime objects.
fixes #9139.
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https://api.github.com/repos/pandas-dev/pandas/issues/9176 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9176/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9176/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9176/events | https://github.com/pandas-dev/pandas/pull/9176 | 53,168,119 | MDExOlB1bGxSZXF1ZXN0MjY3MTU1ODE= | 9,176 | BUG: "index_col=False" not working when "usecols" is specified in read_csv (GH9082) | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-12-31T05:32:02Z | 2015-01-10T17:33:28Z | 2015-01-10T17:33:28Z | CONTRIBUTOR | null | Fixes #9082
My access to the internet is spotty for the next few days. This fixes 9082 and does not break any of the existing tests so hopefully it won't break anyone's existing code. Happy New Year!
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https://api.github.com/repos/pandas-dev/pandas/issues/9177 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9177/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9177/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9177/events | https://github.com/pandas-dev/pandas/pull/9177 | 53,190,705 | MDExOlB1bGxSZXF1ZXN0MjY3MjgwNzQ= | 9,177 | BUG: Fix not to reindex on non-Categorical groups (GH9049) | {
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closes #9344
_self._was_factor_ is not appropriate to judge whether grouper is Categorical or not, because it can be "True" when we groupby indices (not columns). So, I added another flag _self._is_categorical_ to judge Categorical state.
Also, I added a GroupBy test for MultiIndexed data, which was fa... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9178 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9178/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9178/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9178/events | https://github.com/pandas-dev/pandas/issues/9178 | 53,200,037 | MDU6SXNzdWU1MzIwMDAzNw== | 9,178 | Crash on read_html(url, flavor="bs4") if table has only one column | {
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```
Traceback (most recent call last):
File "./posti.py", line 69, in <module>
dfs = read_html(html)
File "/usr/lib/python3.4/site-packages/pandas/io/html.py", line 851, in read_html
parse_dates, tupleize_cols, thous... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9179 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9179/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9179/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9179/events | https://github.com/pandas-dev/pandas/issues/9179 | 53,224,409 | MDU6SXNzdWU1MzIyNDQwOQ== | 9,179 | Implement a DataFrame.view() method to interactively display data | {
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] | closed | false | null | [] | null | 10 | 2015-01-01T17:36:22Z | 2015-03-29T15:40:01Z | 2015-03-29T15:40:01Z | NONE | null | R has a very rudimentary function (utils::View()) to display data interactively. On X11 it's so broken I basically never used it, yet, it would be very nice if pandas had something similar.
With python, there's tabview: https://github.com/firecat53/tabview/
which can be used as a module as well:
```
import tabview.t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9180 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9180/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9180/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9180/events | https://github.com/pandas-dev/pandas/issues/9180 | 53,231,995 | MDU6SXNzdWU1MzIzMTk5NQ== | 9,180 | Support ndjson -- newline delimited json -- for streaming data. | {
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I'm a developer on [dat project](https://github.com/maxogden/dat) (git for data) and we are building a python library to interact with the data store.
Everything in dat is streaming, and we use newline delimited json as the official transfer format between processes.
[Take a look at the specification for ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9182 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9182/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9182/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9182/events | https://github.com/pandas-dev/pandas/pull/9182 | 53,235,628 | MDExOlB1bGxSZXF1ZXN0MjY3NDkwOTY= | 9,182 | FIX: Fix problems with Series text representation. | {
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closes #8532
closes #7508
Before
```
In [1]: import pandas as pd
In [2]: pd.options.display.max_rows = 10
In [3]: s = pd.Series([1,1,1,1,1,1,1,1,1,1,0.9999,1,1]*10)
In [4]: s
Out[4]:
0 1
1 1
2 1
...
127 0.9999
128 1.0000
129 1.0000
L... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9183 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9183/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9183/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9183/events | https://github.com/pandas-dev/pandas/issues/9183 | 53,241,478 | MDU6SXNzdWU1MzI0MTQ3OA== | 9,183 | Bug Report: IndexError when skiprows > 0 and index_col=False | {
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] | closed | false | null | [] | null | 3 | 2015-01-02T07:55:50Z | 2015-01-02T17:48:23Z | 2015-01-02T17:48:23Z | NONE | null | I am using Pandas 0.15.2. I am trying to read the following space-delimited file, which needs first three lines to be skipped:
```
from pandas import *
tumor_df = read_csv("http://www.stat.columbia.edu/~gelman/book/data/rats.asc", index_col=False, skiprows=3, delim_whitespace=True)
```
However, it results in an Inde... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9184 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9184/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9184/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9184/events | https://github.com/pandas-dev/pandas/issues/9184 | 53,254,821 | MDU6SXNzdWU1MzI1NDgyMQ== | 9,184 | str.contains - returns series of zeroes instead of series of bools when all values are NaNs. | {
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import pandas as pd
df = pd.DataFrame({'a': ['x', 'y', 'z'], 'b': [np.nan, np.nan, np.nan]})
```
Applying to string column - produces correct result:
```
df['a'].str.contains('c', na=False)
0 False
1 False
2 False
Name: a, dtype: bool
```
Applying to float column - returns **zeroes** instead of **bools*... | {
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I think breaking compatibility with the ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9186 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9186/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9186/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9186/events | https://github.com/pandas-dev/pandas/issues/9186 | 53,262,851 | MDU6SXNzdWU1MzI2Mjg1MQ== | 9,186 | KeyError when using pivot_table with an aggfunc and and empty column | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2015-01-02T16:50:11Z | 2020-01-03T23:23:44Z | 2020-01-03T23:23:44Z | NONE | null | This is a bit of an edge case, but in Pandas 0.15.2 when you try to pivot on an empty column you should get back an empty dataframe. This is the behaviour when the default aggregation function is used, but if you specify an aggfunc argument it fails.
Setup dataframe with empty column:
```
>>> df = pd.DataFrame({'A':... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9188 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9188/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9188/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9188/events | https://github.com/pandas-dev/pandas/issues/9188 | 53,275,265 | MDU6SXNzdWU1MzI3NTI2NQ== | 9,188 | BUG: concat of all-nan with empty frame produces object dtype | {
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The resultant has all missing and when concat with an empty frame should result in the same dtype (and not promotion)
```
In [1]: df_1 = pd.DataFrame({"Row":[0,1,1], "EmptyCol":np.nan, "NumberCol":[1,2,3]})
In [2]: df_2 = pd.DataFrame(columns = df_1.columns)
In [3]: df_concat = pd.concat([df_1, df_2], ax... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9189 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9189/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9189/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9189/events | https://github.com/pandas-dev/pandas/pull/9189 | 53,279,706 | MDExOlB1bGxSZXF1ZXN0MjY3NzIxNTk= | 9,189 | Docstring: pd.to_datetime (issue #9107) | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-01-02T21:38:28Z | 2015-01-06T11:17:47Z | 2015-01-04T22:36:13Z | CONTRIBUTOR | null | Following the issue "to_datetime returns NaT for old dates with coerce=True".
Do I understand correctly that online documentation is build automatically from docstrings? I.e. are there any other files to change?
Also it would be good to make a link to [this section of "Caveats and Gotchas"](http://pandas.pydata.org/p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9190 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9190/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9190/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9190/events | https://github.com/pandas-dev/pandas/issues/9190 | 53,282,700 | MDU6SXNzdWU1MzI4MjcwMA== | 9,190 | Feature Request: categorical.reset_order | {
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] | closed | false | null | [] | null | 13 | 2015-01-02T22:37:18Z | 2015-03-29T17:15:11Z | 2015-03-29T17:15:11Z | NONE | null | This is a first attempt at addressing #9179
We add a DataFrame.view method to visualize the contents of a dataframe interactively.
The viewing itself is performed using the "tabview" module from https://github.com/firecat53/tabview
A few initial notes:
- tabview requires python3 currently, so please test using pytho... | {
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] | closed | false | null | [] | null | 19 | 2015-01-03T15:50:34Z | 2015-05-14T15:48:28Z | 2015-05-09T15:59:50Z | CONTRIBUTOR | null | addresses part of issue #8263.
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closes #9178
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Quandl was already described in Ecosystem / API section, so I've added link to pydatastream that targets Thomson Reuters Datastream.
closes #5630.
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] | closed | false | null | [] | null | 8 | 2015-01-03T22:49:35Z | 2015-01-05T09:19:55Z | 2015-01-05T00:54:07Z | NONE | null | Why is this hardcoded to 63?
https://github.com/pydata/pandas/blob/master/pandas/io/sql.py#L1212
It's causing my data to be truncated. Should I submit a PR to change it to text?
-Hanley
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```
In [1]: import pandas as pd
In [2]: import numpy as np
In [3]: s = pd.Series(np.ones(5))
In [4]: s.kurt()
ZeroDivisionError: float division by zero
```
This is not consistent with the case when `kurt()` is called on a... | {
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---
This is an update of PR #9024.
closes #9010
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] | closed | false | null | [] | null | 6 | 2015-01-05T10:23:17Z | 2019-06-07T19:06:28Z | 2019-06-07T19:06:28Z | NONE | null | I am deploying an application using cx_freeze on Python 2.7.8.final.0 and pandas 0.15.2.
I get the following error with pandas 0.15.2 but no error with 0.15.1. [SO: http://stackoverflow.com/questions/27705163/error-3-on-dateutil-zoneinfo-using-cx-freeze-and-pandas]
I have include the dateutil/zoneinfo files with the i... | {
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Here is an example. First, create the two DataFr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9201 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9201/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9201/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9201/events | https://github.com/pandas-dev/pandas/issues/9201 | 53,476,956 | MDU6SXNzdWU1MzQ3Njk1Ng== | 9,201 | Issues with numeric_only for DataFrame.std() | {
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"description": "Arithmetic, Comparison, ... | closed | false | null | [] | {
"closed_at": "2015-03-23T10:50:37Z",
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-01-06T03:25:17Z | 2015-03-12T12:08:53Z | 2015-03-12T12:08:53Z | CONTRIBUTOR | null | The docstring shows a `numeric_only` option for `DataFrame.std()` but it does not seem to actually be implemented. I'm happy to take a crack at fixing it but I'm not sure whether it's the doc or the implementation that needs fixing.
To see this consider a mixed-type `DataFrame` where I'm setting one entry to be a `str... | {
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