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```
mask = (df['Quradate'] >= date1) & (df['Quradate'] < date2)
```
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https://github.com/pydata/pandas/blob/datetime64/pandas/src/timeseries/c_dates.c
stuff like week, day_of_year, etc.
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I haven't included any deprecations because I'm not clear how this should work yet.
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In [1]: from pandas import *
In [2]: df = DataFrame([0,1], [datetime(2011, 3, 27, 2, 2, 2),datetime(20... | {
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Removed build directory, all *.so files and site_packages/pandas dir/files and tried again -- same.
Listing errors (many occured in several tests):
``` python
lib/python2.7/site-packages/pandas-0.8.0.dev_4e4b2f5-py2.7-linux-x86_64.egg/panda... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/811 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/811/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/811/comments | https://api.github.com/repos/pandas-dev/pandas/issues/811/events | https://github.com/pandas-dev/pandas/issues/811 | 3,340,762 | MDU6SXNzdWUzMzQwNzYy | 811 | DataFrame.join can not have datetime as column names | {
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For DataFrameA.join( DataFrameB , on = 'somecol' ), DataFrameB can not have datetime objects as column labels
Example:
from datetime import datetime
from pandas import DataFrame
str_dates = [ '20120209' , '20120222' ]
dt_dates = [ datetime(2012,2,9) , datetime(2012,2,22)]
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https://api.github.com/repos/pandas-dev/pandas/issues/812 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/812/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/812/comments | https://api.github.com/repos/pandas-dev/pandas/issues/812/events | https://github.com/pandas-dev/pandas/issues/812 | 3,347,341 | MDU6SXNzdWUzMzQ3MzQx | 812 | Reindex with Series with name field drops name | {
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In [34]: df2.pivot('Date', 'Individual')
Out[34]:
Exercises
Individual 1 2
Date
1/1/2001 10 NaN
1/3/2001 NaN 5
In [35]: df2.pivot('Date', 'Individual').reindex(df['Date'])
Out[35]:
Exercises
Individual 1 2
1/1/2001 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/813 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/813/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/813/comments | https://api.github.com/repos/pandas-dev/pandas/issues/813/events | https://github.com/pandas-dev/pandas/issues/813 | 3,348,120 | MDU6SXNzdWUzMzQ4MTIw | 813 | Implement ordered merge function | {
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```
In [87]: df
Out[87]:
Date Px
0 1/1/2001 21.2
1 1/2/2001 22.0
2 1/3/2001 25.0
In [88]: df2
Out[88]:
Individual Date Exercises
0 1 1/1/2001 10
1 2 1/3/2001 5
In [89]: f = lambda x: merge(x, df, how='outer')
In [90]: concat([f(y... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/814 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/814/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/814/comments | https://api.github.com/repos/pandas-dev/pandas/issues/814/events | https://github.com/pandas-dev/pandas/issues/814 | 3,351,401 | MDU6SXNzdWUzMzUxNDAx | 814 | GroupBy case results in malformed DataFrame | {
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In [19]: d
Out[19]:
group zeros ones label
0 g1 0 1 l1
1 g2 0 1 l2
In [20]: d.groupby(['group']).mean()
Out[20]:
ones zeros
group
g1 1 0
g2 1 0
In [21]: d.groupby(['group']).mean().values
Out[21]:
array([[ 0., 1.],
[ 0., 1.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/815 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/815/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/815/comments | https://api.github.com/repos/pandas-dev/pandas/issues/815/events | https://github.com/pandas-dev/pandas/issues/815 | 3,351,567 | MDU6SXNzdWUzMzUxNTY3 | 815 | Add more careful check preventing malformed BlockManager | {
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https://api.github.com/repos/pandas-dev/pandas/issues/816 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/816/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/816/comments | https://api.github.com/repos/pandas-dev/pandas/issues/816/events | https://github.com/pandas-dev/pandas/issues/816 | 3,351,607 | MDU6SXNzdWUzMzUxNjA3 | 816 | np.diff fails when called on a Series | {
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In [13]: s = Series(np.arange(10))
In [14]: np.diff(s)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
/home/wesm/code/pandas/<ipython-input-14-b5f9fe77ab7c> in <module>()
----> 1 np.diff(s)
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https://api.github.com/repos/pandas-dev/pandas/issues/817 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/817/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/817/comments | https://api.github.com/repos/pandas-dev/pandas/issues/817/events | https://github.com/pandas-dev/pandas/issues/817 | 3,358,008 | MDU6SXNzdWUzMzU4MDA4 | 817 | Groupby performance discrepency in timestamped data | {
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serie = pandas.io.parsers.read_csv(f, parse_dates=True,
date_parser=dateParser, index_col=0)
dateRange = pandas.DateRange(start, end, offset=5 *
pandas.datetools.Minute())
grouped = serie.groupby(dateRange.asof)
# version 1
t = time()
for date in serie.index:
k = grouped.grouper(date) # returns t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/818 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/818/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/818/comments | https://api.github.com/repos/pandas-dev/pandas/issues/818/events | https://github.com/pandas-dev/pandas/issues/818 | 3,358,161 | MDU6SXNzdWUzMzU4MTYx | 818 | izip iterator method for DataFrame | {
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Out of curiosity, is there a reason returning an izip iterator of the
index + cols isn't DataFrame method? I've got the following in my
toolbox now:
def iziprows(df):
series = [df[col] for col in df.columns]
series.insert(0,
df.index)
return izip(*series)
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https://api.github.com/repos/pandas-dev/pandas/issues/819 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/819/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/819/comments | https://api.github.com/repos/pandas-dev/pandas/issues/819/events | https://github.com/pandas-dev/pandas/issues/819 | 3,358,618 | MDU6SXNzdWUzMzU4NjE4 | 819 | Bug in groupby when as_index=False | {
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```
In [2]: paste
In [357]: df = DataFrame({'A' : ['foo', 'bar', 'foo', 'bar',
.....: 'foo', 'bar', 'foo', 'foo'],
.....: 'B' : ['one', 'one', 'two', 'three',
.....: 'two', 'two', 'one', 'three'],
.....: 'C' : randn(8... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/820 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/820/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/820/comments | https://api.github.com/repos/pandas-dev/pandas/issues/820/events | https://github.com/pandas-dev/pandas/issues/820 | 3,358,752 | MDU6SXNzdWUzMzU4NzUy | 820 | dtype of result of string comparison wrong | {
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```
from pandas import *
df = DataFrame([{ "a" : 1, "b" : "foo" }, {"a" : 2, "b" : "bar"}])
print df
mask_a = df.a > 1
print "Mask A"
print mask_a
print mask_a.dtype
print df[mask_a]
print df[-mask_a]
mask_b = df.b == "foo"
print "Mask B"
print mask_b
prin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/821 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/821/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/821/comments | https://api.github.com/repos/pandas-dev/pandas/issues/821/events | https://github.com/pandas-dev/pandas/issues/821 | 3,361,300 | MDU6SXNzdWUzMzYxMzAw | 821 | Implement fast C, C++, or Cython file parser | {
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https://api.github.com/repos/pandas-dev/pandas/issues/822 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/822/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/822/comments | https://api.github.com/repos/pandas-dev/pandas/issues/822/events | https://github.com/pandas-dev/pandas/issues/822 | 3,363,879 | MDU6SXNzdWUzMzYzODc5 | 822 | Non-string columns should get casted to string in DataFrame.to_records | {
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```
In [36]: df
Out[36]:
0 1 2 3 4 5 6 7 8 9
0 2.1670 1.7100 0.61340 3.0150 2.5060 0.6787 1.6970 4.0460 1.2010 0.6134
1 1.2920 0.6526 0.33930 0.9789 1.9320 0.3915 0.6526 1.9710 1.0310 0.5221
2 0.4176 0.3002 0.01305 0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/823 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/823/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/823/comments | https://api.github.com/repos/pandas-dev/pandas/issues/823/events | https://github.com/pandas-dev/pandas/issues/823 | 3,365,749 | MDU6SXNzdWUzMzY1NzQ5 | 823 | Handling of dict return values in groupby.apply | {
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https://api.github.com/repos/pandas-dev/pandas/issues/824 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/824/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/824/comments | https://api.github.com/repos/pandas-dev/pandas/issues/824/events | https://github.com/pandas-dev/pandas/issues/824 | 3,373,553 | MDU6SXNzdWUzMzczNTUz | 824 | provide rebuild option in appending to an HDFStore | {
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] | closed | false | null | [] | null | 1 | 2012-02-24T14:58:59Z | 2012-11-24T22:22:34Z | 2012-11-24T22:22:34Z | CONTRIBUTOR | null | currently if you try to append to an existing table in an HDFStore and the fields are different from the existing fields,
pandas raises an Exception("append items do not match existing")
the reason for this the current structure of an HDFStore table is: index (time column), column (a string), values (a float array)
t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/825 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/825/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/825/comments | https://api.github.com/repos/pandas-dev/pandas/issues/825/events | https://github.com/pandas-dev/pandas/issues/825 | 3,374,850 | MDU6SXNzdWUzMzc0ODUw | 825 | Maybe add limit option to fillna | {
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https://api.github.com/repos/pandas-dev/pandas/issues/826 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/826/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/826/comments | https://api.github.com/repos/pandas-dev/pandas/issues/826/events | https://github.com/pandas-dev/pandas/issues/826 | 3,378,547 | MDU6SXNzdWUzMzc4NTQ3 | 826 | Try to workaround Yahoo! finance 404 errors, better error messages | {
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```
import pandas
import pandas.io.data as pd
def get_close(ticker, start, end):
stock = pd.DataReader(ticker, 'yahoo', start, end)
adj_close = stock['Adj Close']
return adj_close[-1]
start = datetime.datetime(2010,1,1)
end = datetime.datetime(2012,1,24)
ticker = ['TLT', 'IEF',... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/827 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/827/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/827/comments | https://api.github.com/repos/pandas-dev/pandas/issues/827/events | https://github.com/pandas-dev/pandas/issues/827 | 3,379,412 | MDU6SXNzdWUzMzc5NDEy | 827 | rename fill_method to method in dataframe/series align | {
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https://api.github.com/repos/pandas-dev/pandas/issues/828 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/828/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/828/comments | https://api.github.com/repos/pandas-dev/pandas/issues/828/events | https://github.com/pandas-dev/pandas/pull/828 | 3,379,498 | MDExOlB1bGxSZXF1ZXN0ODgzMzk5 | 828 | attempting to deflect more issues to the github tracker via the docs | {
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https://api.github.com/repos/pandas-dev/pandas/issues/829 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/829/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/829/comments | https://api.github.com/repos/pandas-dev/pandas/issues/829/events | https://github.com/pandas-dev/pandas/pull/829 | 3,379,780 | MDExOlB1bGxSZXF1ZXN0ODgzNTQw | 829 | DataFrame_repr_html changes according to #772 discussion. | {
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Implemented changes as discussed in #772.
Not so crazy on the scrollable div. For now i left the div max sizes as they were, could use suggestion on _good_ values.
I don't use the notebook often, what i noticed just now is that in combination with the IPython notebook `get_terminal_size()` returns the s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/830 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/830/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/830/comments | https://api.github.com/repos/pandas-dev/pandas/issues/830/events | https://github.com/pandas-dev/pandas/pull/830 | 3,380,103 | MDExOlB1bGxSZXF1ZXN0ODgzNzAz | 830 | BUG: close #811, fix index.intersection where indices are incomparable | {
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https://api.github.com/repos/pandas-dev/pandas/issues/831 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/831/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/831/comments | https://api.github.com/repos/pandas-dev/pandas/issues/831/events | https://github.com/pandas-dev/pandas/issues/831 | 3,391,642 | MDU6SXNzdWUzMzkxNjQy | 831 | Pass list of arrays to create MultiIndex | {
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https://api.github.com/repos/pandas-dev/pandas/issues/832 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/832/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/832/comments | https://api.github.com/repos/pandas-dev/pandas/issues/832/events | https://github.com/pandas-dev/pandas/issues/832 | 3,391,969 | MDU6SXNzdWUzMzkxOTY5 | 832 | Add means to apply group operations to the DataFrame's index instead of only the columns | {
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https://api.github.com/repos/pandas-dev/pandas/issues/833 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/833/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/833/comments | https://api.github.com/repos/pandas-dev/pandas/issues/833/events | https://github.com/pandas-dev/pandas/issues/833 | 3,393,898 | MDU6SXNzdWUzMzkzODk4 | 833 | api for timeseries interval pivoting | {
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"f... | 9 | 2012-02-26T22:35:48Z | 2018-07-06T19:40:06Z | 2018-07-06T19:40:00Z | CONTRIBUTOR | null | For example, want easy to and from timeseries for following data.
```
Out[179]:
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1949 112 118 132 129 121 135 148 148 136 119 104 118
1950 115 126 141 135 125 149 170 170 158 133 114 140
1951 145 150 178 163 172 178 199 19... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/834 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/834/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/834/comments | https://api.github.com/repos/pandas-dev/pandas/issues/834/events | https://github.com/pandas-dev/pandas/pull/834 | 3,396,311 | MDExOlB1bGxSZXF1ZXN0ODg4NjM4 | 834 | Bug Fix for Issue #513 Fractional seconds lost in HDFStore for datetime indexes | {
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"followers_url": "https://api.github.com/users/wesm/f... | 3 | 2012-02-27T05:37:36Z | 2014-08-18T07:04:37Z | 2012-02-28T17:35:05Z | CONTRIBUTOR | null | PyTables Time64Col is in fact a float64 alias so adding fractional seconds and using the correct dtype fixes this issue
#513
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https://api.github.com/repos/pandas-dev/pandas/issues/835 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/835/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/835/comments | https://api.github.com/repos/pandas-dev/pandas/issues/835/events | https://github.com/pandas-dev/pandas/issues/835 | 3,400,466 | MDU6SXNzdWUzNDAwNDY2 | 835 | When parsing a CSV file without an index, if the list with columns names is too short or too long, one gets a "Index contains duplicate entries" exception. | {
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Just a minor bug submisson:
When parsing a CSV file without an index, if the list with columns names is too short or too long, one gets a "Index contains duplicate entries" exception.
E.g.:
The file test.csv contains:
abc,1,a
abc,2,b
def,3,c
Running:
`table = pandas.read_csv('reports/9/test.csv', header=Non... | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-02-27T22:36:48Z | 2012-05-08T23:17:11Z | 2012-05-08T23:12:32Z | MEMBER | null | Could reindex a float array in a single swipe instead of producing an intermediate copy. Currently very inefficient if the result object is small relative to the source object
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https://api.github.com/repos/pandas-dev/pandas/issues/837 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/837/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/837/comments | https://api.github.com/repos/pandas-dev/pandas/issues/837/events | https://github.com/pandas-dev/pandas/issues/837 | 3,415,391 | MDU6SXNzdWUzNDE1Mzkx | 837 | ExcelFile throws an exception if parsing a file with only two lines | {
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Test Test1
aaaa bbbbb
``` python
excel_data = pandas.ExcelFile("test.xls")
parsed = pandas.parse("Sheet1")
/usr/lib64/python2.7/site-packages/pandas/io/parsers.pyc in parse(self, sheetname, header, skiprows, index_col, parse_dates, date_parser, na_values, chunksize)
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"followers_url": "https://api.github.com/users/wesm/f... | 3 | 2012-02-28T14:45:23Z | 2012-02-28T19:32:58Z | 2012-02-28T19:32:58Z | NONE | null | I tried to create a DateRange in five minute steps.
`In [40]: DateRange(datetime(2011,11,11), datetime(2011,11,12), offset=DateOffset(minute=5))`
The %CPU is 100 and it consumes a lot of memory but nothing happens, no result and no error. I continued to experiment and realized that i wrote 'minute' instead of 'minut... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/839 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/839/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/839/comments | https://api.github.com/repos/pandas-dev/pandas/issues/839/events | https://github.com/pandas-dev/pandas/issues/839 | 3,429,079 | MDU6SXNzdWUzNDI5MDc5 | 839 | int64 Series and NA assignment | {
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"followers_url": "https://api.github.com/users/wesm/f... | 3 | 2012-02-29T00:19:35Z | 2012-02-29T18:04:21Z | 2012-02-29T18:04:21Z | CONTRIBUTOR | null | I think a bug:
In [1]: s = Series(arange(10))
In [2]: s
Out[2]:
0 0
1 1
2 2
3 3
4 4
5 5
6 6
7 7
8 8
9 9
In [3]: s[::2] = np.nan
In [4]: s
Out[4]:
0 -9223372036854775808
1 1
2 -9223372036854775808
3 3
4 -9223372036854775808
5 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/840 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/840/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/840/comments | https://api.github.com/repos/pandas-dev/pandas/issues/840/events | https://github.com/pandas-dev/pandas/issues/840 | 3,433,496 | MDU6SXNzdWUzNDMzNDk2 | 840 | error during line-wise iteration over DataFrame | {
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```
In [37]: a = pandas.DataFrame(rand(4, 2), columns = list('ab'))
In [38]: print a
a b
0 0.372630 0.680347
1 0.557162 0.815903
2 0.058282 0.371265
3 0.772931 0.925008
In [39]: for l in a.ix:
....: print l... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/841 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/841/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/841/comments | https://api.github.com/repos/pandas-dev/pandas/issues/841/events | https://github.com/pandas-dev/pandas/issues/841 | 3,440,791 | MDU6SXNzdWUzNDQwNzkx | 841 | "approximate" datetime reindexing | {
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"f... | 1 | 2012-02-29T17:40:30Z | 2014-05-23T22:43:06Z | 2014-05-23T22:43:06Z | CONTRIBUTOR | null | From the mailing list:
It would be nice to have a general, useful algorithm for doing
"approximate" reindexing like you describe. I'm thinking:
def approx_resample(obj, base, multiple, tolerance, offset=0, mode='nearest'):
...
then you would do:
result = approx_resample(df, 'min', 15, 5)
obviously
'min' <=> Mi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/842 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/842/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/842/comments | https://api.github.com/repos/pandas-dev/pandas/issues/842/events | https://github.com/pandas-dev/pandas/issues/842 | 3,456,134 | MDU6SXNzdWUzNDU2MTM0 | 842 | Release Notes Issues not Linked | {
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[[[ - Add `to_clipboard` function to pandas namespace f... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/843 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/843/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/843/comments | https://api.github.com/repos/pandas-dev/pandas/issues/843/events | https://github.com/pandas-dev/pandas/pull/843 | 3,456,805 | MDExOlB1bGxSZXF1ZXN0OTEyMDcz | 843 | References Linked | {
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https://api.github.com/repos/pandas-dev/pandas/issues/844 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/844/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/844/comments | https://api.github.com/repos/pandas-dev/pandas/issues/844/events | https://github.com/pandas-dev/pandas/issues/844 | 3,467,328 | MDU6SXNzdWUzNDY3MzI4 | 844 | Applying np.sum to empty series results in NaN | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2012-03-01T23:11:21Z | 2012-03-15T20:36:07Z | 2012-03-15T20:35:43Z | NONE | null | ``` python
In [1]: import pandas
In [2]: pandas.__version__
Out[2]: '0.7.1'
In [3]: empty = pandas.Series([], index=[])
In [4]: import numpy as np
In [5]: np.__version__
Out[5]: '1.6.1'
In [6]: np.sum(empty)
Out[6]: nan
In [7]: np.sum(empty.values)
Out[7]: 0.0
```
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https://api.github.com/repos/pandas-dev/pandas/issues/845 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/845/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/845/comments | https://api.github.com/repos/pandas-dev/pandas/issues/845/events | https://github.com/pandas-dev/pandas/pull/845 | 3,467,829 | MDExOlB1bGxSZXF1ZXN0OTE1MTI3 | 845 | Adding links to change log bullets | {
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https://api.github.com/repos/pandas-dev/pandas/issues/846 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/846/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/846/comments | https://api.github.com/repos/pandas-dev/pandas/issues/846/events | https://github.com/pandas-dev/pandas/issues/846 | 3,468,266 | MDU6SXNzdWUzNDY4MjY2 | 846 | Buggy creation of int DataFrame from data containing NAs | {
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In [5]: df = DataFrame([[np.nan, 1], [1, 0]], dtype=np.int64)
In [6]: df
Out[6]:
0 1
0 -9223372036854775808 1
1 1 0
```
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https://api.github.com/repos/pandas-dev/pandas/issues/847 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/847/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/847/comments | https://api.github.com/repos/pandas-dev/pandas/issues/847/events | https://github.com/pandas-dev/pandas/issues/847 | 3,478,669 | MDU6SXNzdWUzNDc4NjY5 | 847 | Don't raise exception if HDFStore file is read only | {
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https://api.github.com/repos/pandas-dev/pandas/issues/848 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/848/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/848/comments | https://api.github.com/repos/pandas-dev/pandas/issues/848/events | https://github.com/pandas-dev/pandas/issues/848 | 3,492,818 | MDU6SXNzdWUzNDkyODE4 | 848 | Annotated DataFrame | {
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Are there any plans on creating an object similar to R/Bioconductor's AnnotatedDataFrame ( http://rss.acs.unt.edu/Rdoc/library/Biobase/html/class.AnnotatedDataFrame.html )? It wouldn't seem sensible to carry over the aspects ... | {
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will be nearly identical setup with some Cython code to do _expanding_moment
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https://api.github.com/repos/pandas-dev/pandas/issues/850 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/850/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/850/comments | https://api.github.com/repos/pandas-dev/pandas/issues/850/events | https://github.com/pandas-dev/pandas/issues/850 | 3,493,301 | MDU6SXNzdWUzNDkzMzAx | 850 | Fix int32 overflow in groupby | {
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https://api.github.com/repos/pandas-dev/pandas/issues/852 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/852/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/852/comments | https://api.github.com/repos/pandas-dev/pandas/issues/852/events | https://github.com/pandas-dev/pandas/issues/852 | 3,493,564 | MDU6SXNzdWUzNDkzNTY0 | 852 | Add option to adjoin DataFrames in same sheet with to_excel | {
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The argument "parse_dates" will try to parse every column in the index.
Most of the times I have a dataset which looks like below and the first n columns will be used to set the multi-index.
Notice that my first column "date" is a date while the column "unitcode" is a integer.
If you use "parse_dat... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/854 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/854/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/854/comments | https://api.github.com/repos/pandas-dev/pandas/issues/854/events | https://github.com/pandas-dev/pandas/issues/854 | 3,497,256 | MDU6SXNzdWUzNDk3MjU2 | 854 | make easier to parse european-style dates in to_csv | {
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Example:
data1 = '''date;value
01/05/2010;1
15/05/2010;2
31/05/2010;3
'''
df = pd.read_csv(StringIO(data1),sep=";",converters={'date':pd.datetools.dateutil.parser.parse})
print df.to_string()
Returns the first row wrong:
date value
0 2010-01-05 00:00:00 1
1 2010-05-... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/856 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/856/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/856/comments | https://api.github.com/repos/pandas-dev/pandas/issues/856/events | https://github.com/pandas-dev/pandas/issues/856 | 3,497,352 | MDU6SXNzdWUzNDk3MzUy | 856 | Fix unhelpful error message in parsers ("tried columns 1-X as index") | {
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```
if not index._verify_integrity():
dups = index.get_duplicates()
err_msg = 'Tried columns 1-X as index but found duplicates %s'
raise Exception(err_msg % str(dups))
```
this was added as I recall to give a somewhat better error message when IN... | {
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In [58]: df[df > 0.5]
ERROR: An unexpected error occurred while tokenizing input
The following traceback may be corrupted or invalid
## The error message is: ('EOF in multi-line statement', (63, 0))
KeyError Traceback (most recent call last... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/862 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/862/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/862/comments | https://api.github.com/repos/pandas-dev/pandas/issues/862/events | https://github.com/pandas-dev/pandas/pull/862 | 3,499,634 | MDExOlB1bGxSZXF1ZXN0OTI2MDMx | 862 | Fixed bug in ewmcov | {
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How much can be just plugged in, with datetime64 <-> interval conversions only where necessary?
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eg, something like
ts.first("5W") # first five weeks of data
ts.first("7D") # first seven days
ts.last("3W").first("3B") # first 3 biz days of last three weeks
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https://github.com/statsmodels/statsmodels/issues/168
We may have to change some of the forecast dates code when pandas switches over to the ordinal timestamp representation. Right now, our current implementation is broken with the new datetime branch installed. To replicate, install... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/868 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/868/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/868/comments | https://api.github.com/repos/pandas-dev/pandas/issues/868/events | https://github.com/pandas-dev/pandas/issues/868 | 3,516,453 | MDU6SXNzdWUzNTE2NDUz | 868 | Create an AnnotatedDataFrame-like data structure? | {
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Have there been any thoughts on creating a data s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/870 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/870/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/870/comments | https://api.github.com/repos/pandas-dev/pandas/issues/870/events | https://github.com/pandas-dev/pandas/issues/870 | 3,517,464 | MDU6SXNzdWUzNTE3NDY0 | 870 | nosetest failures in reshape | {
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File "/Users/welch/src/pandas/pandas/core/reshape.py", line 95, in _make_selectors
group_mask.p... | {
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``` python
>>> frame1 = pandas.DataFrame({"test1":["a", "b", "c"], "test2":[1,2,3], "test3": [4.5, 3.2, 1.2]})
>>> frame2 = pandas.DataFrame({"test4": [5.2, 2.2, 4.3]})
>>> pandas.concat([frame1, frame2], ignore_index=True, axis=1)
/usr/lib64/python2.7/site-packages/pandas/tools/merge.pyc in concat(objs, ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/872 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/872/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/872/comments | https://api.github.com/repos/pandas-dev/pandas/issues/872/events | https://github.com/pandas-dev/pandas/issues/872 | 3,526,390 | MDU6SXNzdWUzNTI2Mzkw | 872 | DataFrame.to_string() does not always use formatters argument | {
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In [28]: myformatter = lambda x: '[%4.1f]' % x
In [29]: df = pandas.DataFrame(np.random.randn(2,2), columns=['A', 'B'])
In [30]: df
Out[30]:
A B
0 -0.478634 1.143561
1 0.043301 1.006389
In [31]: print df.to_string(formatters={'A': myformatter})
A B
0 [-0.5] 1.143561
1 ... | {
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```
for value, typ in izip(sheet.row_values(i), sheet.row_types(i)):
```
To:
```
for value, typ in izip(sheet.row_values... | {
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"f... | 4 | 2012-03-07T15:52:40Z | 2014-06-03T01:19:49Z | 2014-06-03T01:19:49Z | CONTRIBUTOR | null | Sometimes, ASCII data can contain strange fragments such as "/", "-", "%", "`", "#", "~" in the numerical data columns.
These charaters could either be inserted by a mal-functioning data logger (obeservation data), differencing conventions on NoData or wrong exports from other programs.
Before processing such data int... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/877 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/877/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/877/comments | https://api.github.com/repos/pandas-dev/pandas/issues/877/events | https://github.com/pandas-dev/pandas/issues/877 | 3,553,620 | MDU6SXNzdWUzNTUzNjIw | 877 | Handle Carrage Return in read_csv | {
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from pandas import *
import pandas
import numpy as np
df = DataFrame({'a': np.random.randn(6),
'b': ['foo', 'bar'] * 3,
'c': np.random.randn(6)})
df.ix[2:4, ['b','c']]
---------------------------------------------------------------------------
TypeError ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/880 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/880/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/880/comments | https://api.github.com/repos/pandas-dev/pandas/issues/880/events | https://github.com/pandas-dev/pandas/issues/880 | 3,566,418 | MDU6SXNzdWUzNTY2NDE4 | 880 | failure in multiindex-based access in Panel | {
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import pandas as pn
ind = pn.MultiIndex.from_tuples([('a', 1), ('a', 2), ('b', 1), ('b',2)], names=['fist', 'second'])
wp = pn.Panel(np.random.random((4,5,5)), items=ind,
major_axis=np.arange(5), minor_axis=np.arange(5))
In [10]: wp['a']
...
KeyError: 'no item named a'
In [11]: wp.ix['a']
...
KeyError: 'no ... | {
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In [27]: df
Out[27]:
a b c d
0 2 0.103795 -0.066523 NaN
1 3 -0.939895 -0.208760 NaN
2 9 1.968456 0.419374 NaN
3 6 -0.105170 0.162064 NaN
4 7 0.381707 2.126133 NaN
In [28]: df[df['a']==3]
Out[28]:
a b c d
1 3 -0.939895 -0.20876 NaN
In [29]: df[df['a']==2]
Out[... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/884 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/884/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/884/comments | https://api.github.com/repos/pandas-dev/pandas/issues/884/events | https://github.com/pandas-dev/pandas/issues/884 | 3,570,554 | MDU6SXNzdWUzNTcwNTU0 | 884 | Enable pivot_table to do group-wise correlations between variables more easily | {
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https://api.github.com/repos/pandas-dev/pandas/issues/886 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/886/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/886/comments | https://api.github.com/repos/pandas-dev/pandas/issues/886/events | https://github.com/pandas-dev/pandas/issues/886 | 3,571,101 | MDU6SXNzdWUzNTcxMTAx | 886 | Implement weighted moving average (pass array of weights) | {
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http://en.wikipedia.org/wiki/Exponential_smoothing#The_weighted_moving_average
cf http://stackoverflow.com/questions/9621362/how-do-i-compute-a-weighted-moving-average-using-pandas
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from pandas import DataFrame
df = DataFrame()
sdf = df.to_sparse()
sdf.combineAdd(DataFrame())
pandas\core\frame.pyc in combineAdd(self, other)
3861 DataFrame
3862 """
-> 3863 return self.add(other, fill_value=0.)
3864
3865 def combineMult... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/889 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/889/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/889/comments | https://api.github.com/repos/pandas-dev/pandas/issues/889/events | https://github.com/pandas-dev/pandas/issues/889 | 3,580,795 | MDU6SXNzdWUzNTgwNzk1 | 889 | conditional assignment raises exception | {
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df[df['column']==1] = 5
raises an exception, so i have to use
df.ix[df['column']==1,'column'] = 5
or iterate through the whole DataFrame.
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``` python
In [31]: df
Out[31]:
a b c d
0 4 -0.548572 -0.333272 NaN
1 1 -0.502314 0.975798 NaN
2 9 0.283227 1.486831 NaN
3 3 1.514658 ... | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2012-03-09T14:15:05Z | 2012-03-15T21:10:38Z | 2012-03-15T21:09:53Z | CONTRIBUTOR | null | see also [mailing list](https://groups.google.com/forum/?fromgroups#!topic/pystatsmodels/e5J1yvCGmmI)
``` python
In [34]: df = pandas.DataFrame({'A': [u'\u03c3']})
In [35]: df
Out[35]:
A
0 σ
In [36]: print df.to_html()
---------------------------------------------------------------------------
UnicodeEncodeError... | {
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> > > from pandas import *
> > > x = DataFrame(columns=[0,1], index=[3,4])
> > > x
> > > 0 1
> > > 3 NaN NaN
> > > 4 NaN NaN
> > >
> > > x[0]= [None,... | {
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For example:
I retrieve Data from an SQL DB (postgres in my case) and then I have a list of tuples with "None" (in SQL NULL) values.
I then convert to a DF by using DataFrame.from_records()
Now, to avoid object Series it would be nice to have None automati... | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-03-10T00:22:44Z | 2012-04-13T01:37:40Z | 2012-04-13T01:37:40Z | CONTRIBUTOR | null | would it be possible to shorten:
```
index = DateRange('1/1/2000 00:00', periods=8, offset=datetools.Hour())
```
to
```
index = DateRange('1/1/2000 00:00', periods=8, offset=h)
```
(maybe I am still spoiled by scikits.timeseries)
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https://api.github.com/repos/pandas-dev/pandas/issues/895 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/895/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/895/comments | https://api.github.com/repos/pandas-dev/pandas/issues/895/events | https://github.com/pandas-dev/pandas/issues/895 | 3,592,272 | MDU6SXNzdWUzNTkyMjcy | 895 | DateRange in docs not working | {
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rng = DateRange(start, end, offset=BDay())
```
triggers:
NameError: name 'BDay' is not defined
should be
```
rng = DateRange(start, end, offset=datetools.BDay())
```
http://pandas.pydata.org/pandas-docs/stable/timeseries.html#generating-date-ranges-daterange
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https://api.github.com/repos/pandas-dev/pandas/issues/896 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/896/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/896/comments | https://api.github.com/repos/pandas-dev/pandas/issues/896/events | https://github.com/pandas-dev/pandas/issues/896 | 3,592,363 | MDU6SXNzdWUzNTkyMzYz | 896 | DateRange for 12 month not created | {
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base data
```
rng = DateRange('1/1/2000 00:00', periods=8760, offset=datetools.Hour())
ts = Series(randn(len(rng)), index=rng)
```
the range
```
ts.index[0]
Out[95]: datetime.datetime(2000, 1, 1, 0, 0)
ts.index[-1]
Out[96]: datetime.datetime(2000, 12, 30, 23, 0)
mrg = DateRan... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/897 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/897/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/897/comments | https://api.github.com/repos/pandas-dev/pandas/issues/897/events | https://github.com/pandas-dev/pandas/issues/897 | 3,592,723 | MDU6SXNzdWUzNTkyNzIz | 897 | to xlsx no working | {
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730 self.fm_date = xlwt.easyxf(num_format_str='YYYY-MM-DD')
731 else:
--> 732 from openpyxl import Workbook
733 self.book = Workbook(optimized_write = True)
734 self.path = path
ImportError: cannot import name Workbook
```
I think should be workb... | {
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```
import numpy as np
import pandas
data1 = np.arange(24)
data2 = 24 - np.arange(24)
dates = pandas.DateRange(start=datetime.datetime(2005,1,1),
periods=24, offset=pandas.datetools.MonthEnd())
DF = pandas.DataFrame({'data1':data1, 'data2':data2}, index=dates)
ann_range = pandas.DateRange(start=datetime.dateti... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/899 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/899/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/899/comments | https://api.github.com/repos/pandas-dev/pandas/issues/899/events | https://github.com/pandas-dev/pandas/issues/899 | 3,601,513 | MDU6SXNzdWUzNjAxNTEz | 899 | Skip tests requiring pytz | {
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https://api.github.com/repos/pandas-dev/pandas/issues/900 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/900/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/900/comments | https://api.github.com/repos/pandas-dev/pandas/issues/900/events | https://github.com/pandas-dev/pandas/issues/900 | 3,602,535 | MDU6SXNzdWUzNjAyNTM1 | 900 | timeseries branch, fix labels in plotting | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-03-11T18:27:25Z | 2012-05-01T17:05:56Z | 2012-05-01T17:05:56Z | CONTRIBUTOR | null | They come out as ints
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