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https://api.github.com/repos/pandas-dev/pandas/issues/8101 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8101/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8101/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8101/events | https://github.com/pandas-dev/pandas/issues/8101 | 40,970,024 | MDU6SXNzdWU0MDk3MDAyNA== | 8,101 | Series.isbetween(min,max) method | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8102 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8102/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8102/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8102/events | https://github.com/pandas-dev/pandas/pull/8102 | 40,973,260 | MDExOlB1bGxSZXF1ZXN0MjAyMDg4OTY= | 8,102 | BENCH: add benchmarks for SQL | {
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WIP for now: intitial benchmarks for sql functions
- Where should the benches be placed? Because there is `io_bench.py`, `packers.py` and `parsers_vb.py` which all contain io related benchmarks. Or should I create a new file?
- The first tests are a generic mixed-type frame writing/reading, both wit... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8103 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8103/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8103/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8103/events | https://github.com/pandas-dev/pandas/pull/8103 | 40,974,479 | MDExOlB1bGxSZXF1ZXN0MjAyMDkzNDc= | 8,103 | BUG: pivot_table raises KeyError with nameless index and columns | {
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```
df = pd.DataFrame({'dt1': [datetime.datetime(2011, 1, 1), datetime.datetime(2011, 2, 1),
datetime.datetime(2011, 3, 1), ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8104 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8104/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8104/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8104/events | https://github.com/pandas-dev/pandas/pull/8104 | 40,988,915 | MDExOlB1bGxSZXF1ZXN0MjAyMTQ5ODA= | 8,104 | TST: Moving testing method outside of TestCase | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2014-08-23T23:37:38Z | 2014-12-01T00:57:26Z | 2014-12-01T00:57:09Z | CONTRIBUTOR | null | Make assert_numpy_array_equal available without subclassing TestCase; see #8023
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https://api.github.com/repos/pandas-dev/pandas/issues/8105 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8105/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8105/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8105/events | https://github.com/pandas-dev/pandas/issues/8105 | 41,003,922 | MDU6SXNzdWU0MTAwMzkyMg== | 8,105 | SQL: read_sql with a stored procedure | {
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pandas.io.sql.read_sql(sql,dbconn) does not work if the string sql does not have 'select' in it. If I'm reading a sproc, sql will start with 'exec' and no 'select'.
There is a test on line 377 in pandas\io\sql.py
if 'select' in sql.lower()
I modified it to
if 'select' in sql.lower() or 'exec' in sql.l... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8106 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8106/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8106/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8106/events | https://github.com/pandas-dev/pandas/pull/8106 | 41,018,649 | MDExOlB1bGxSZXF1ZXN0MjAyMjM1NzQ= | 8,106 | CLN: Partially add future division imports | {
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... | 11 | 2014-08-24T20:43:49Z | 2015-03-06T16:29:14Z | 2015-03-06T16:29:14Z | CONTRIBUTOR | null | Adds division import to cases where something is already imported from **future** . #5445
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https://api.github.com/repos/pandas-dev/pandas/issues/8107 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8107/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8107/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8107/events | https://github.com/pandas-dev/pandas/pull/8107 | 41,022,520 | MDExOlB1bGxSZXF1ZXN0MjAyMjQ4Nzg= | 8,107 | DOC: setuptools is a required runtime dependency | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8108 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8108/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8108/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8108/events | https://github.com/pandas-dev/pandas/pull/8108 | 41,028,561 | MDExOlB1bGxSZXF1ZXN0MjAyMjczNTQ= | 8,108 | BUG: reindexing a frame fails to pick nan value | {
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```
>>> df = pd.DataFrame([[1, 2], [3, 5], [7, 11], [9, 23]],
... index=[2, np.nan, 1, 5], columns=['joe', 'jim'])
>>> df
joe jim
2 1 2
NaN 3 5
1 7 11
5 9 23
>>> df.reindex([2, np.nan, 1])
joe jim
2 1 2
NaN NaN NaN
1 7 11
```
with this patch:
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"followers_url": "https://api.github.com/users/jr... | 4 | 2014-08-25T13:44:05Z | 2014-08-29T20:43:41Z | 2014-08-29T20:43:30Z | CONTRIBUTOR | null | See https://travis-ci.org/pydata/pandas/jobs/33461059
```
The command "echo "script"" exited with 0.
0.18s$ ci/script.sh
inside ci/script.sh
nosetests --exe -w /tmp -A not slow and not disabled pandas --with-xunit --xunit-file=/tmp/nosetests.xml
Traceback (most recent call last):
File "/home/travis/virtualenv/python... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8110 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8110/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8110/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8110/events | https://github.com/pandas-dev/pandas/pull/8110 | 41,065,850 | MDExOlB1bGxSZXF1ZXN0MjAyNDg3MTg= | 8,110 | ER: clarify import error message of BeautifulSoup (read_html) | {
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@cpcloud
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https://api.github.com/repos/pandas-dev/pandas/issues/8111 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8111/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8111/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8111/events | https://github.com/pandas-dev/pandas/pull/8111 | 41,068,211 | MDExOlB1bGxSZXF1ZXN0MjAyNTAwNTA= | 8,111 | DOC: fix formatting in dependencies in install.rst | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8112 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8112/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8112/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8112/events | https://github.com/pandas-dev/pandas/issues/8112 | 41,074,058 | MDU6SXNzdWU0MTA3NDA1OA== | 8,112 | BUG: groupby drops columns if the column name is the same as the grouper | {
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... | closed | false | null | [] | {
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>>> df = pd.DataFrame(np.random.randint(1, 9, (2, 3)), columns=['jim', 'joe', 'jolie'])
>>> df
jim joe jolie
0 4 7 8
1 7 8 3
>>> ts = df['joe'] * 0
>>> ts.name
'joe'
>>> gr = df.groupby(ts)
>>> gr.nth(0) # this invokes _set_selection_from_grouper internally
jim jolie
joe
7 4 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8113 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8113/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8113/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8113/events | https://github.com/pandas-dev/pandas/issues/8113 | 41,098,901 | MDU6SXNzdWU0MTA5ODkwMQ== | 8,113 | VIS: DataFrame.plot drops datetime data when kind is scatter | {
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"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... | 27 | 2014-08-25T19:55:47Z | 2020-01-01T16:26:02Z | 2020-01-01T16:26:02Z | CONTRIBUTOR | null | This works fine:
``` python
In [13]: df = pd.DataFrame(np.random.randn(300), columns=['a'])
In [14]: df['dtime'] = pd.DatetimeIndex(start='2014-01-01', freq='h', periods=300).time
In [15]: df.plot(x='dtime', y='a')
Out[15]: <matplotlib.axes._subplots.AxesSubplot at 0x118fd17f0>
```
This raises a `KeyError`
``` pytho... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8114 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8114/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8114/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8114/events | https://github.com/pandas-dev/pandas/pull/8114 | 41,104,137 | MDExOlB1bGxSZXF1ZXN0MjAyNzA4Njg= | 8,114 | BUG: fixed df.info() output missing new line | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2014-08-25T20:45:24Z | 2014-09-12T13:47:03Z | 2014-09-12T13:47:03Z | CONTRIBUTOR | null | Had this minor bug working with pandas from the command line
```
>>> df.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 891 entries, 0 to 890
Data columns (total 12 columns):
PassengerId 891 non-null int64
# ... etc
Embarked 889 non-null object
dtypes: float64(2), int64(5), object(5)>>>
```
(The int... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8115 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8115/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8115/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8115/events | https://github.com/pandas-dev/pandas/issues/8115 | 41,175,547 | MDU6SXNzdWU0MTE3NTU0Nw== | 8,115 | BUG: read_table with full line comment and delim_whitespace=True | {
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``` python
In [2]: !cat test.txt
# comment
0 1 2 3 4
5 6 7 8 9
# comment
10 11 12 13 15
In [3]: df = pd.read_table("test.txt", skipin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8116 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8116/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8116/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8116/events | https://github.com/pandas-dev/pandas/issues/8116 | 41,187,770 | MDU6SXNzdWU0MTE4Nzc3MA== | 8,116 | Pandas broadcast with numpy scalars | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-08-26T15:50:21Z | 2014-08-29T16:19:48Z | 2014-08-29T16:19:48Z | NONE | null | Pandas objects (`Series`, `DataFrame`, etc...) can broadcast operations with python scalars. For example:
```
import pandas as pd
pd.DataFrame([1,2,3])*2
```
But when performing the same operation with a [numpy scalar array](http://docs.scipy.org/doc/numpy/reference/arrays.scalars.html):
```
import pandas as pd
impo... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8117 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8117/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8117/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8117/events | https://github.com/pandas-dev/pandas/issues/8117 | 41,196,410 | MDU6SXNzdWU0MTE5NjQxMA== | 8,117 | can't plot multi-row subplots | {
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``` python
g = np.random.choice([1,2,3], 10)
s = np.random.normal(size=10)
s2 =np.random.normal(size=10)
df = pd.DataFrame([g, s, s2]).T
df.columns = ['key', 's1', 's2']
gb = df.groupby('key')
fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(12, 4))
i = 0
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8118 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8118/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8118/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8118/events | https://github.com/pandas-dev/pandas/issues/8118 | 41,210,430 | MDU6SXNzdWU0MTIxMDQzMA== | 8,118 | Prevent dataframes from having duplicate column names | {
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df = pd.DataFrame({'name': ('jimmy', 'hortense', 'knut'), 'age': (10, 13, 20)})
df = df[['name','name','... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8119 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8119/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8119/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8119/events | https://github.com/pandas-dev/pandas/pull/8119 | 41,242,511 | MDExOlB1bGxSZXF1ZXN0MjAzNDkxODk= | 8,119 | BUG: broadcasting with numpy scalars (GH8116) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8120 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8120/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8120/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8120/events | https://github.com/pandas-dev/pandas/issues/8120 | 41,272,346 | MDU6SXNzdWU0MTI3MjM0Ng== | 8,120 | read_stata unable to read version 7 stata files ... | {
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"color": "5319e... | closed | false | null | [] | null | 5 | 2014-08-27T11:21:46Z | 2014-08-29T10:23:50Z | 2014-08-28T13:11:35Z | CONTRIBUTOR | null | ... but R using the foreign package can.
Is some support for those old stata files planned ?
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https://api.github.com/repos/pandas-dev/pandas/issues/8121 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8121/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8121/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8121/events | https://github.com/pandas-dev/pandas/issues/8121 | 41,280,535 | MDU6SXNzdWU0MTI4MDUzNQ== | 8,121 | get_group sometimes throws an exception when using an index of tuples with different lengths | {
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```
df = pd.DataFrame(pd.Series([(1,), (1,2), (1,), (1, 2)]), columns = ['ids'])
gb = df.groupby('ids')
for i in gb.size().index :
print i
gb.get_group(i)
```
The issues is that in _get_index of GroupBy, these lines assume that if there ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8122 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8122/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8122/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8122/events | https://github.com/pandas-dev/pandas/pull/8122 | 41,292,885 | MDExOlB1bGxSZXF1ZXN0MjAzNzkxNTM= | 8,122 | Made line comments work with delim_whitespace and custom line terminator | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8123 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8123/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8123/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8123/events | https://github.com/pandas-dev/pandas/pull/8123 | 41,293,958 | MDExOlB1bGxSZXF1ZXN0MjAzNzk4NDU= | 8,123 | BUG: fix groupby with tuple bug | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8124 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8124/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8124/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8124/events | https://github.com/pandas-dev/pandas/issues/8124 | 41,310,251 | MDU6SXNzdWU0MTMxMDI1MQ== | 8,124 | DataFrame.loc throws AttributeError with rows of datetime objects | {
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```
import pandas as pd
from datetime import time
x = pd.DataFrame({'name': ['A', 'B', 'C', 'D'],
'time': [time(14, 12), time(12, 14), time(2, 45), time(5, 55)],
'category': ['X', 'X', 'Y', 'Y']})
y = x.set_index(['category', 'name']).transpose()
y.loc['time', ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8125 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8125/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8125/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8125/events | https://github.com/pandas-dev/pandas/pull/8125 | 41,311,666 | MDExOlB1bGxSZXF1ZXN0MjAzOTA1OTI= | 8,125 | DOC: Link to Python standard encodings from read_csv documentation | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8126 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8126/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8126/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8126/events | https://github.com/pandas-dev/pandas/pull/8126 | 41,337,124 | MDExOlB1bGxSZXF1ZXN0MjA0MDYzMTI= | 8,126 | BUG: Fix bad axis limits when boxplotting with 'by' (#7528) | {
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The original bug involved the y-limits for boxplots being wrong when using `'by': turns out it has to do with the dummy axis that gets created when the plots don't fill the axis layout, e.g. when we're plotting 3 columns in a 2 by 2 layout.
The fix for this basically involves not setting the `sharey`/`sh... | {
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] | closed | false | null | [] | null | 3 | 2014-08-28T00:30:53Z | 2015-10-21T17:17:47Z | 2015-10-20T22:39:56Z | CONTRIBUTOR | null | The following code works when `sz = 1000000`, but produces IndexError when `sz=10000000`. Seems similar to #5727.
```
df = pd.DataFrame({'A':np.random.randint(0, sz, sz),
'B':np.random.randint(0, 2, sz),
'C':np.random.randn(sz)})
df.set_index(['A', 'B'])\
.groupby(level=[0, 1])... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8128 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8128/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8128/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8128/events | https://github.com/pandas-dev/pandas/pull/8128 | 41,350,857 | MDExOlB1bGxSZXF1ZXN0MjA0MTQ5NDk= | 8,128 | PERF: speed up multi-key groupby | {
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```
In [3]: pd.__version__
Out[3]: '0.14.1-276-g995f91c'
In [4]: np.random.seed(2718281)
In [5]: n = 20000
In [6]: df = pd.DataFrame(np.random.randint(1, n, (n, 3)),
...: columns=['jim', 'joe', 'jolie'])
In [7]: %timeit df.groupby(['jim', 'joe'])['jolie'].t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8129 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8129/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8129/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8129/events | https://github.com/pandas-dev/pandas/issues/8129 | 41,365,948 | MDU6SXNzdWU0MTM2NTk0OA== | 8,129 | TypeError casting int64 to int32 when shifting time series | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-08-28T08:25:11Z | 2014-09-17T15:30:14Z | 2014-09-17T15:30:14Z | CONTRIBUTOR | null | I think I hit another 32bits issue. This happens in Win7 32 bits:
```
Python 2.7.6 (default, Nov 10 2013, 19:24:18) [MSC v.1500 32 bit (Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import pandas as pd
>>> index = pd.date_range('2000-01-01', periods=5, freq='D')
>>> s1 = p... | {
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```
$ python setup.py install
running install
running bdist_egg
running egg_info
writing requirements to pandas.egg-info/requires.txt
writing pandas.egg-info/PKG-INFO
writing top-level names to pandas.egg-info/top_level.txt
wr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8131 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8131/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8131/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8131/events | https://github.com/pandas-dev/pandas/issues/8131 | 41,386,063 | MDU6SXNzdWU0MTM4NjA2Mw== | 8,131 | BUG: setting a sparse column in a frame buggy | {
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thought this was well tested.....
```
df = pd.DataFrame({'c_1':['a', 'b', 'c'], 'n_1': [1., 2., 3.]})
df['new_column'] = pd.Series([0, 0, 1]).to_sparse(fill_value=0)
# AssertionError: Shape of new values must ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8132 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8132/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8132/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8132/events | https://github.com/pandas-dev/pandas/issues/8132 | 41,386,491 | MDU6SXNzdWU0MTM4NjQ5MQ== | 8,132 | BUG: multiindex slicers edge cases | {
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```
df = pd.DataFrame({'A': ['A0'] * 5 + ['A1']*5 + ['A2']*5,
'B': ['B0','B0','B1','B1','B2'] * 3,
'DATE': ["2013-06-11",
"2013-07-02",
"2013-07-09"... | {
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``` python
In [17]: data
Out[17]:
PassengerId Survived Pclass \
0 1 0 3
1 2 1 1
Name Sex Age SibSp \
0 Braund, Mr. Owen Harris... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8134 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8134/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8134/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8134/events | https://github.com/pandas-dev/pandas/pull/8134 | 41,395,116 | MDExOlB1bGxSZXF1ZXN0MjA0NDEzMTk= | 8,134 | BUG: Bug in multi-index slicing with various edge cases (GH8132) | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-08-28T14:21:03Z | 2014-08-28T15:04:07Z | 2014-08-28T15:04:07Z | CONTRIBUTOR | null | closes #8132
```
# A1 - Works - Get all values under "A0" and "A1"
df1.loc[(slice('A1')),:]
VALUES
A B DATE
A0 B0 2013-06-11 22
2013-07-02 35
B1 2013-07-09 14
2013-07-30 9
B2 2013-08-06 4
A1 B0 2013-06-11 40
2013-07-02 18
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https://api.github.com/repos/pandas-dev/pandas/issues/8136 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8136/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8136/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8136/events | https://github.com/pandas-dev/pandas/issues/8136 | 41,447,618 | MDU6SXNzdWU0MTQ0NzYxOA== | 8,136 | Series of just None not converted to NaN | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2014-08-28T21:43:22Z | 2016-11-11T10:37:00Z | 2016-11-11T10:37:00Z | CONTRIBUTOR | null | I was a little surprised by this
```
In [11]: pd.Series([])
Out[11]: Series([], dtype: float64)
In [12]: pd.Series([None]) # should be NaN / float ?
Out[12]:
0 None
dtype: object
In [13]: pd.Series([None, 1])
Out[13]:
0 NaN
1 1
dtype: float64
```
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``` python
df['Col3'] = df.Col1 + df.Col2
```
what I actually wrote was this:
``` python
df['Col3'] = df[df.Col1] + df[df.Col2]
```
This is c... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8138 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8138/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8138/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8138/events | https://github.com/pandas-dev/pandas/issues/8138 | 41,489,016 | MDU6SXNzdWU0MTQ4OTAxNg== | 8,138 | BUG: inconsistent behaviour of Groupby with empty bins when grouping by single/multiple keys | {
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I just stumbled upon an inconsistent behaviour of the groupby function which is causing me a lot of trouble. When grouping on bins, I expect the empty bins to be kept as NA values, for dimension consistency when one wants to aggregate and compare data.
This is effectively the case when grouping on a s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8139 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8139/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8139/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8139/events | https://github.com/pandas-dev/pandas/issues/8139 | 41,497,529 | MDU6SXNzdWU0MTQ5NzUyOQ== | 8,139 | ENH: Add prefix parameters for join method. | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2014-08-29T12:57:52Z | 2017-07-08T02:30:53Z | 2017-07-08T02:30:49Z | NONE | null | It would be nice if the join method had `lprefix` and `rprefix` parameters in analogy to `lsuffix` and `rsuffix`.
P.S. No pull request, sorry.
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https://api.github.com/repos/pandas-dev/pandas/issues/8140 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8140/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8140/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8140/events | https://github.com/pandas-dev/pandas/pull/8140 | 41,504,849 | MDExOlB1bGxSZXF1ZXN0MjA1MDE3ODk= | 8,140 | ENH: let get_dummies take a DataFrame | {
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Thoughts? I encode every column with `object` dtype. You can control the ones that get encoded with `categorical_variables`. The encoded columns are `concat`ed to the columns that don't need encoding.
`prefix` and `prefix_sep` can be passed as a string, list, or dic... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8141 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8141/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8141/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8141/events | https://github.com/pandas-dev/pandas/issues/8141 | 41,521,874 | MDU6SXNzdWU0MTUyMTg3NA== | 8,141 | API: Consistency in prefix / prefix_sep | {
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"f... | 2 | 2014-08-29T17:21:38Z | 2021-04-11T05:07:59Z | null | CONTRIBUTOR | null | Currently `get_dummies` has both `prefix` and `prefix_sep` parameters. This is inconsistent with the rest of pandas prefix / suffix arguments that have you included the separator in the pre/suffix.
- `read_csv`
- `join`
probably others.
We should add a warning to `get_dummies` to have users change `prefix_sep` to `'... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8142 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8142/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8142/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8142/events | https://github.com/pandas-dev/pandas/issues/8142 | 41,524,096 | MDU6SXNzdWU0MTUyNDA5Ng== | 8,142 | Index __sub__ should check for instance of Index | {
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def **add**(self, other):
if isinstance(other, Index):
return self.union(other)
else:
return Index(np.array(self) + other)
but subtraction falls straight through to diff.
so if index_object is an Int64Index, the following behavior takes place... | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-08-29T19:17:29Z | 2014-08-29T20:44:25Z | 2014-08-29T20:44:25Z | CONTRIBUTOR | null | Should this work?
``` python
In [70]: cat = pd.Categorical(['a', 'b', 'c'])
In [71]: obj = pd.Series(['a', 'b', 'c'])
In [72]: num = pd.Series([1, 2, 3])
In [73]: df = pd.concat([pd.Series(cat), obj, num], axis=1, keys=['cat', 'obj', 'num'])
In [74]: df
Out[74]:
cat obj num
0 a a 1
1 b b 2
2 c ... | {
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Possibly should do this on other benches as well.
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https://api.github.com/repos/pandas-dev/pandas/issues/8147 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8147/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8147/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8147/events | https://github.com/pandas-dev/pandas/issues/8147 | 41,549,184 | MDU6SXNzdWU0MTU0OTE4NA== | 8,147 | Slow MySQL Connections since switch to SQLAlchemy | {
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``` python
from sqlalchemy import create_engine
import pandas as pd
query = "select count(*) from transactions where started > '2014-08-29'"
engine = create... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8148 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8148/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8148/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8148/events | https://github.com/pandas-dev/pandas/pull/8148 | 41,553,302 | MDExOlB1bGxSZXF1ZXN0MjA1MzE0ODc= | 8,148 | BUG: use stable sort for group_index in groupby | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2014-08-30T02:31:57Z | 2014-09-06T16:55:50Z | 2014-09-04T00:57:15Z | CONTRIBUTOR | null | Following on https://github.com/pydata/pandas/pull/8128, for certain `groupby` operations such as,
```
df.groupby(key)[col].transfrom('first')
```
it is necessary to use stable sort for group indices. As a result, `numpy.argsort` should be called with argument `kind='mergesort'`.
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https://api.github.com/repos/pandas-dev/pandas/issues/8149 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8149/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8149/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8149/events | https://github.com/pandas-dev/pandas/pull/8149 | 41,558,172 | MDExOlB1bGxSZXF1ZXN0MjA1MzM0NzQ= | 8,149 | DOC: add some links in install.rst | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8150 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8150/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8150/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8150/events | https://github.com/pandas-dev/pandas/issues/8150 | 41,572,151 | MDU6SXNzdWU0MTU3MjE1MQ== | 8,150 | VIS: datetime plots x axis format: labels now rotated? | {
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The xaxis labels (the date/time indications) are now rotated ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8151 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8151/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8151/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8151/events | https://github.com/pandas-dev/pandas/pull/8151 | 41,597,909 | MDExOlB1bGxSZXF1ZXN0MjA1NTAzMTY= | 8,151 | BUG: consistency between logical ops & type casts | {
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... | 8 | 2014-08-31T22:39:18Z | 2015-05-10T19:52:12Z | 2015-05-10T19:37:37Z | CONTRIBUTOR | null | Closes [#6528](https://github.com/pydata/pandas/issues/6528).
Currently series logical operations are bound to return a series with `dtype='bool'`. That being a good decision or not, it is good to have some internal consistency:
```
>>> a = pd.Series([nan, nan, nan])
>>> b = pd.Series([False, True, nan])
>>> a | b == ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8152 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8152/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8152/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8152/events | https://github.com/pandas-dev/pandas/issues/8152 | 41,605,254 | MDU6SXNzdWU0MTYwNTI1NA== | 8,152 | BUG: warnings import missing for panel | {
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```
In [1]: import numpy as np
In [2]: import pandas as pd
In [3]: pd.__version__
Out[3]: '0.14.1'
In [4]: p = pd.Panel(np.random.rand(3, 3, 3))
In [5]: p.major_xs(1, copy=False)
---------------------------------------------------------------------------
Na... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8153 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8153/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8153/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8153/events | https://github.com/pandas-dev/pandas/pull/8153 | 41,634,203 | MDExOlB1bGxSZXF1ZXN0MjA1NzAwMjY= | 8,153 | Fixups for categoricals | {
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See #8078 for the ToDos.
Closes: #8077 -> API/FIX: wrap result cut/qut in Series and make it ordered
Closes: #8074 -> Discussion
Closes: #8078 -> Todos
This has a (passing) unittest for #8138 but no code changes. Not sure what was the change which fixed the bu... | {
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... | 7 | 2014-09-01T13:19:44Z | 2015-10-06T03:42:13Z | 2015-10-06T03:42:13Z | MEMBER | null | Say you have to parse some nicely ISO formatted date strings, you can just parse this with `todatetime` very fast. But if you were 'overcautious' and provided the `format="%Y-%m-%d %H:%M:%S"` for safety, this seems to be around 20 times slower.
Would it be possible to provide a fastpath for certain provided format str... | {
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```
-------------------------------------------------------------------------------
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https://api.github.com/repos/pandas-dev/pandas/issues/8156 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8156/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8156/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8156/events | https://github.com/pandas-dev/pandas/issues/8156 | 41,646,301 | MDU6SXNzdWU0MTY0NjMwMQ== | 8,156 | Importing Datetime values from SQL Server with SQL Alchemy | {
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`data = pd.read_sql('select top 10 timestamp from mytable',db)`
'MyTable' contains a column 'Timestamp', which is of type DateTime2.
If `db` is a pyodbc database connection this works fine, and my timestamps are returned as data t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8157 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8157/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8157/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8157/events | https://github.com/pandas-dev/pandas/pull/8157 | 41,665,467 | MDExOlB1bGxSZXF1ZXN0MjA1ODY4ODM= | 8,157 | BUG: add 'import warnings' statement in panel.py (GH8152) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8158 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8158/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8158/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8158/events | https://github.com/pandas-dev/pandas/issues/8158 | 41,693,148 | MDU6SXNzdWU0MTY5MzE0OA== | 8,158 | ENH: convert datetime components (year, month, day, ...) in different columns to datetime | {
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I didn't find an issue about this, but it has come up some times at stackoverflow: having columns with integers for year, month, day, hour, ..., how do you convert this to a datetime column/index ?
http://stackov... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8159 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8159/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8159/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8159/events | https://github.com/pandas-dev/pandas/issues/8159 | 41,708,824 | MDU6SXNzdWU0MTcwODgyNA== | 8,159 | read_html parse_dates not working | {
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I am using read_html to pull data from a table. Several of the columns are parsed as dates incorrectly. If I use parse_dates=False this has no effect. Using infer_types=False works, but it is going to be deprecated.
Sorry if I'm not reporting this correctly, new to GitHub ;-)
``` python
import pandas as pd
url =... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8160 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8160/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8160/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8160/events | https://github.com/pandas-dev/pandas/issues/8160 | 41,714,260 | MDU6SXNzdWU0MTcxNDI2MA== | 8,160 | DOC/BUG? pivot functionality confusing/inconsistent | {
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"f... | 2 | 2014-09-02T14:21:44Z | 2019-10-21T19:52:14Z | null | CONTRIBUTOR | null | 1. The docstring of the (non-member) `pivot()` function, http://pandas.pydata.org/pandas-docs/stable/generated/pandas.pivot.html#pandas.pivot, says `Produce ‘pivot’ table based on 3 columns of this DataFrame. Uses unique values from index / columns and fills with values.` But there is no DataFrame argument, and so no "... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8161 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8161/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8161/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8161/events | https://github.com/pandas-dev/pandas/issues/8161 | 41,725,189 | MDU6SXNzdWU0MTcyNTE4OQ== | 8,161 | Extremely slow construction of large DataFrames out of ndarrays? | {
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"default"... | closed | false | null | [] | null | 5 | 2014-09-02T15:58:01Z | 2014-09-02T16:18:07Z | 2014-09-02T16:17:08Z | CONTRIBUTOR | null | I was trying to figure out what's the most efficient way to create a dataframe out of a large numpy record array (I initially naively thought this could be done in a zero-copy way) and ran some simple tests:
---
``` python
n_columns = 2
n_records = int(15e6)
data = np.zeros((n_columns, n_records), np.int32)
arr = np... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8162 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8162/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8162/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8162/events | https://github.com/pandas-dev/pandas/issues/8162 | 41,754,074 | MDU6SXNzdWU0MTc1NDA3NA== | 8,162 | Allowing the index to be referenced by name, like a column | {
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"f... | 19 | 2014-09-02T20:58:40Z | 2021-04-11T05:09:19Z | null | CONTRIBUTOR | null | - [ ] #13243 use df.index/df.columns names to automatically choose axis along which to broadcast
- [ ] #11373 Request for some kind of named arguments loc
- [ ] #4036 Partial Selection on MultiIndex: The need for empty slice support & dict indexing
What if we allowed the index of a dataframe to be referred to in the u... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8163 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8163/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8163/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8163/events | https://github.com/pandas-dev/pandas/issues/8163 | 41,774,947 | MDU6SXNzdWU0MTc3NDk0Nw== | 8,163 | DOC: {Series,DataFrame}.dot() not listed under API Reference | {
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They are documented:
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.dot.html
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.dot.html
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flexible to use on mixed-type dataframe. User can now select among returning
numeric, categorical, or both, as well as 'auto' (previous behaviour, default),
and 'same', which keep columns identical (useful, e.g. with groupby())
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https://api.github.com/repos/pandas-dev/pandas/issues/8165 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8165/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8165/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8165/events | https://github.com/pandas-dev/pandas/issues/8165 | 41,803,280 | MDU6SXNzdWU0MTgwMzI4MA== | 8,165 | BUG: round-trip of tz in an index using fixed-format for HDF5 | {
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... | 10 | 2014-09-03T10:47:12Z | 2015-10-22T13:26:30Z | 2015-10-22T13:26:30Z | NONE | null | xref #9270
With Python 2.7.6, pandas 0.13.1 and numpy 1.8.1, pytables 3.1.1, both 32 and 64bit (Python x,y and WinPython), I can load my hdf5 file.
With Python 3.4.1 64bit, pandas 0.14.1, numpy 1.8.2, pytables 3.1.1 (Anaconda3 2.0.1) I get the following error:
Traceback (most recent call last):
File "<ipython-i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8166 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8166/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8166/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8166/events | https://github.com/pandas-dev/pandas/pull/8166 | 41,820,957 | MDExOlB1bGxSZXF1ZXN0MjA2NzkyNzI= | 8,166 | ENH: added api_rst_coverage.py | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8167 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8167/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8167/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8167/events | https://github.com/pandas-dev/pandas/issues/8167 | 41,823,597 | MDU6SXNzdWU0MTgyMzU5Nw== | 8,167 | 0.13.1: strange PyTables error | {
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```
File "C:\Python27\lib\site-packages\pandas\io\pytables.py", line 914, in append
**kwargs)
File "C:\Python27\lib\site-packages\pandas\io\pytables.py", line 1273, in _write_to_group
s.write(obj=value, append=append, complib=complib, **kwargs)
File "C:\Python27\lib\site-package... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8168 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8168/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8168/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8168/events | https://github.com/pandas-dev/pandas/issues/8168 | 41,829,776 | MDU6SXNzdWU0MTgyOTc3Ng== | 8,168 | HDFStore inside thread provokes a segmentation fault. | {
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pandas==0.14.1
``` python
import pandas as pd
import threading
def thread():
'''
Stupid thread reading a DataFrame.
'''
store = pd.HDFStore('/tmp/df.h5')
dataframe = store['/data']
store.close()
def main():
'''
Main funct... | {
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something odd going on here:
```
vals = np.hstack((np.random.randint(0,5,(100,2)), np.random.randint(0,2,(100,2))))
df = pd.DataFrame(vals, columns=['a', 'b', 'c', 'd'])
df[df==2] = np.n... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8170 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8170/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8170/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8170/events | https://github.com/pandas-dev/pandas/pull/8170 | 41,851,454 | MDExOlB1bGxSZXF1ZXN0MjA2OTczOTY= | 8,170 | BUG: not raising error on Newey-West corrections when clustering | {
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"followers_url": "https://api.github.com/users/jr... | 10 | 2014-09-03T18:47:48Z | 2014-09-22T16:36:11Z | 2014-09-13T19:27:40Z | CONTRIBUTOR | null | closes #5884, OLS does not correctly apply Newey-West corrections when clustering
is being used. Add an assertion to check for this.
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https://api.github.com/repos/pandas-dev/pandas/issues/8171 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8171/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8171/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8171/events | https://github.com/pandas-dev/pandas/pull/8171 | 41,881,237 | MDExOlB1bGxSZXF1ZXN0MjA3MTQ0NTk= | 8,171 | BUG: GroupBy.count() with float32 data type does not exclude nan | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2014-09-04T00:24:19Z | 2014-09-06T20:50:14Z | 2014-09-06T20:45:00Z | CONTRIBUTOR | null | Previously I had submitted https://github.com/pydata/pandas/pull/7853. Given that we are sorting indexers, for performance reasons I should have used `groupsort_indexer` instead of `np.argsort`.
on master:
```
In [7]: np.random.seed(2718281)
In [8]: n = 50000
In [9]: left = DataFrame(np.random.randint(1, n/500, (n,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8174 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8174/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8174/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8174/events | https://github.com/pandas-dev/pandas/issues/8174 | 41,952,336 | MDU6SXNzdWU0MTk1MjMzNg== | 8,174 | Regression: divmod(my_series, some_integer) no longer works since version 0.13. | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-09-04T15:47:50Z | 2016-09-19T21:07:02Z | 2016-09-19T21:07:02Z | NONE | null | In Pandas version 0.12, you could apply the Python built-in `divmod` function to a `Series` and an integer:
```
Enthought Canopy Python 2.7.6 | 64-bit | (default, Jun 4 2014, 16:42:26)
[GCC 4.2.1 (Apple Inc. build 5666) (dot 3)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> imp... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8175 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8175/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8175/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8175/events | https://github.com/pandas-dev/pandas/issues/8175 | 41,965,216 | MDU6SXNzdWU0MTk2NTIxNg== | 8,175 | Stacked bar plot negative values do not work correctly if dataframe contains NaN values | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-09-04T17:51:45Z | 2014-09-07T00:30:07Z | 2014-09-07T00:30:07Z | CONTRIBUTOR | null | While trying to produce a stacked bar plot which includes negative values, I found that if the dataframe contains NaN values the bar plot does not display correctly.
Specifically, this code:
``` python
df = pd.DataFrame([[10,20,5,40],[-5,5,20,30],[np.nan,-10,-10,20],[10,20,20,-40]], columns = ['A','B','C','D'])
df.pl... | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-09-04T18:11:29Z | 2014-09-04T18:58:18Z | 2014-09-04T18:58:17Z | CONTRIBUTOR | null | related #2578
from [SO](http://stackoverflow.com/questions/25670760/copying-a-row-screws-up-pandas-column-data-types-how-to-avoid)
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This makes barplot more consistent with how NaN's are handled in AreaPlots and PiePlots.
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... | 1 | 2014-09-05T02:24:42Z | 2017-05-10T11:04:19Z | 2017-05-10T11:04:19Z | CONTRIBUTOR | null | start of enhancing performance section should begin with tips for speeding up pandas, e.g. no apply, vectorization, pandas methods etc.
Initially I put in:
> This tutorial assumes you have refactored as much as possible in python, for example trying to remove for loops and making use of numpy vectorization, it’s alwa... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8179 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8179/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8179/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8179/events | https://github.com/pandas-dev/pandas/pull/8179 | 42,012,852 | MDExOlB1bGxSZXF1ZXN0MjA3ODc0NDA= | 8,179 | DOC: added release note, this fixes #8173 | {
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Adds a warning if the provided table name in `to_sql` and the actually used table name in the database do not match (eg converted to lower case due to case insensitivity settings of database, eg MySQL on Windows). When user is not aware of this, and keeps using the upper case table name, this leads to bug... | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-09-05T13:56:08Z | 2014-09-17T19:33:59Z | 2014-09-17T19:33:59Z | CONTRIBUTOR | null | Very much an edge case:
``` python
In [17]: df = pd.DataFrame(np.random.randn(100, 4))
In [18]: df.loc[:, 0] = np.nan
In [19]: df.plot(kind='box')
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-19-06... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8182 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8182/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8182/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8182/events | https://github.com/pandas-dev/pandas/issues/8182 | 42,049,315 | MDU6SXNzdWU0MjA0OTMxNQ== | 8,182 | API: kdeplot fails with NaNs. | {
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``` python
In [65]: df = pd.DataFrame(np.random.uniform(size=(100, 4)))
In [66]: df.loc[0, 0] = np.nan
In [67]: df.plot(kind='kde')
---------------------------------------------------------------------------
ValueError Traceback (mo... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8183 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8183/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8183/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8183/events | https://github.com/pandas-dev/pandas/pull/8183 | 42,049,353 | MDExOlB1bGxSZXF1ZXN0MjA4MDk1NzE= | 8,183 | BUG: scatter with errorbar raises IndexError | {
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Also fixes a color problem with `c` kw found in #7780. (But should work with single color. It looks `errorbar` doesn't accept multiple colors).
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https://api.github.com/repos/pandas-dev/pandas/issues/8184 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8184/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8184/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8184/events | https://github.com/pandas-dev/pandas/pull/8184 | 42,052,606 | MDExOlB1bGxSZXF1ZXN0MjA4MTE2OTY= | 8,184 | ENH: create Timedelta scalar / TimedeltaIndex | {
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closes #8187
closes #8209
closes #4533
closes #8190
closes #7869
closes #8214
This PR creates a new `timedelta` sub-class, the scalar `Timedelta`, very similar to how `Timestamp` sub-classes `datetime`. Further it creates a `TimedeltaIndex` modelled on `DatetimeIndex` that holds the underlying data (bo... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8185 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8185/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8185/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8185/events | https://github.com/pandas-dev/pandas/issues/8185 | 42,052,872 | MDU6SXNzdWU0MjA1Mjg3Mg== | 8,185 | ENH: read_csv to have a parse_timedelta kw to automatically parse into timedelta64 | {
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original from #3009
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"des... | closed | false | null | [] | null | 2 | 2014-09-05T16:04:42Z | 2017-05-04T19:07:32Z | 2017-05-04T19:07:32Z | CONTRIBUTOR | null | I'm trying to find a home for this function: https://gist.github.com/TomAugspurger/9156696
Output is shown [here](http://tomaugspurger.github.io/blog/2014/02/22/Visualizing%20Missing%20Data/).
Basically it highlights the locations of missing data.
Should it go
- Under `df.plot(kind='missing')`
- As a recipe in the co... | {
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In [6]: s = pd.Series(pd.date_range(start='2014-01-01', periods=30, freq='d'))
In [7]: s.dt.tz_localize('US/Central')
```
Would return a Series with the same index whose values are Timestamps with the timezone set.
I haven't looked at this code too closely, so I'm not sure how difficult it would be and if it's d... | {
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I have pandas dataframes with diverse data types and structures, including lists. The csv-writer saves the lists without trouble, but I prefer to also save in excel format for collaboration with my colleagues.
Currently the ExcelWriter returns a TypeError if the dataframe contains a list.
`TypeErro... | {
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```
In [58]: tz = pd.DatetimeIndex(start='2010-01-01', periods=10, freq='d', tz='US/Central')
In [59]: df = pd.DataFrame(np.random.randn(10, 2), columns=['A', 'B'])
In [60]: df['time'] = tz
In [62]: df.dtypes
Out[62]:
A float64
B float64
time object
dtype: o... | {
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All the logic to do the conversions already exists, it just needs better parsing.
Related: #7611
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] | closed | false | null | [] | null | 3 | 2014-09-05T20:23:23Z | 2015-10-20T22:42:08Z | 2015-10-20T22:42:08Z | NONE | null | I want to have thousands separators in Excel, but when I pass float_format="%,.2f" in I get an unsupported character error. I also tried "{0:,}". Am I missing something or is this unsupported?
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https://api.github.com/repos/pandas-dev/pandas/issues/8192 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8192/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8192/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8192/events | https://github.com/pandas-dev/pandas/issues/8192 | 42,089,855 | MDU6SXNzdWU0MjA4OTg1NQ== | 8,192 | Value.Error | {
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on MacOs 10.9,
with Python2.7.5
(ipython 2.2.0)
Numpy 1.8.2 and Pandas 0.14.1
(successfully) installed with "pip",
I got the following when I try to import Pandas
```
ValueError: numpy.dtype has the wrong size, try recompiling
```
then,
I installed pandas from github (uninstalling the pip packages before), ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8193 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8193/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8193/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8193/events | https://github.com/pandas-dev/pandas/issues/8193 | 42,098,740 | MDU6SXNzdWU0MjA5ODc0MA== | 8,193 | Passing a dictionary of columns names and colors | {
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http://stackoverflow.com/questions/25689558/pandas-bar-plot-specify-bar-color-by-column
Having the ability to natively pass in a dictionary of the column names and the desired color could be a nice addition to simplify specifying what color you want each line/bar to be.
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https://api.github.com/repos/pandas-dev/pandas/issues/8194 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8194/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8194/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8194/events | https://github.com/pandas-dev/pandas/issues/8194 | 42,101,545 | MDU6SXNzdWU0MjEwMTU0NQ== | 8,194 | ENH: DataFrame.name | {
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It would be useful for `DataFrame` similarly to have a `name` member, so that when a `DataFrame` is produced by slicing a `Panel`, the name of the sliced... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8195 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8195/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8195/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8195/events | https://github.com/pandas-dev/pandas/pull/8195 | 42,102,671 | MDExOlB1bGxSZXF1ZXN0MjA4NDIwNDM= | 8,195 | ENH: more verbosity to PyTables import failures | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8196 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8196/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8196/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8196/events | https://github.com/pandas-dev/pandas/pull/8196 | 42,104,759 | MDExOlB1bGxSZXF1ZXN0MjA4NDMzMzQ= | 8,196 | API: kdeplot fails with NaNs. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8197 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8197/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8197/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8197/events | https://github.com/pandas-dev/pandas/pull/8197 | 42,107,220 | MDExOlB1bGxSZXF1ZXN0MjA4NDQ3MDg= | 8,197 | ENH: Add prefix parameters for join method. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8198 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8198/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8198/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8198/events | https://github.com/pandas-dev/pandas/issues/8198 | 42,116,244 | MDU6SXNzdWU0MjExNjI0NA== | 8,198 | VIS: NaN Handling in Pie Plots | {
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"followers_url": "https://api.github.com/users/jr... | 8 | 2014-09-06T13:04:45Z | 2014-10-04T19:57:56Z | 2014-10-04T19:57:38Z | CONTRIBUTOR | null | From https://github.com/pydata/pandas/pull/8177#issuecomment-54711316, how should we handle NaNs in Pie Plots. Right now the documented behavior is to fill 0s and plot. This can result in some unattractive labeling depending on where the NaNs are at in the series.
``` python
In [11]: series = Series(3 * np.random.rand... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8199 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8199/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8199/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8199/events | https://github.com/pandas-dev/pandas/pull/8199 | 42,126,281 | MDExOlB1bGxSZXF1ZXN0MjA4NTMxNTU= | 8,199 | BUG: fix variable overwriting in radviz | {
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] | closed | false | null | [] | null | 9 | 2014-09-06T20:43:30Z | 2014-10-02T13:42:16Z | 2014-09-18T12:30:01Z | CONTRIBUTOR | null | The variable `n` is set to number of rows in dataframe, and then it overwritten with number of columns, but after that there is loop that should iterate over rows and it uses new value in `n` that holds number of columns already.
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https://api.github.com/repos/pandas-dev/pandas/issues/8200 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8200/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8200/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8200/events | https://github.com/pandas-dev/pandas/issues/8200 | 42,128,196 | MDU6SXNzdWU0MjEyODE5Ng== | 8,200 | read_html ignores commas | {
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... | 10 | 2014-09-06T22:13:38Z | 2016-04-17T14:00:03Z | 2016-04-17T14:00:03Z | NONE | null | Hello,
I'm trying to parse a file with the extension 'xls' which is not an Excel file but it's clearly an html file (open with a text editor it's clearly html code).
One of my columns uses the italian convention of using the comma instead of the dot before decimals: 5,5 instead of 5.5. I was hoping to parse it at lea... | {
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