gayathri nagarajan | 10 Nov 23:40 2014
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unable to install iopro

Hi,

 I receive the below error when i try to install iopro.Could not connect to http://repo.continuum.io/pkgs/free/win-64/iopro-1.6.7-np19p
y27_p0.tar.bz2. The server has limited internet access. 

Thank you 

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Jeff Reback | 8 Nov 23:24 2014
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ANN: pandas v0.15.1

Hello,

We are proud to announce v0.15.1 of pandas, a minor release from 0.15.0. 

This release includes a small number of API changes, several new features,
enhancements, and performance improvements along with a large number of bug fixes. 

This was a short release of 3 weeks with 59 commits by 20 authors encompassing 87 issues.

We recommend that all users upgrade to this version.

For a more a full description of Whatsnew for v0.15.1 here:

pandas is a Python package providing fast, flexible, and expressive data
structures designed to make working with “relational” or “labeled” data both
easy and intuitive. It aims to be the fundamental high-level building block for
doing practical, real world data analysis in Python. Additionally, it has the
broader goal of becoming the most powerful and flexible open source data
analysis / manipulation tool available in any language.


Documentation:
http://pandas.pydata.org/pandas-docs/stable/

Source tarballs, windows binaries are available on PyPI:

windows binaries are courtesy of  Christoph Gohlke and are built on Numpy 1.8
macosx wheels will be available soon, courtesy of Matthew Brett

Please report any issues here:
https://github.com/pydata/pandas/issues


Thanks

The Pandas Development Team


Contributors to the 0.15.1 release

  • Aaron Staple
  • Andrew Rosenfeld
  • Anton I. Sipos
  • Artemy Kolchinsky
  • Bill Letson
  • Dave Hughes
  • David Stephens
  • Guillaume Horel
  • Jeff Reback
  • Joris Van den Bossche
  • Kevin Sheppard
  • Nick Stahl
  • Sanghee Kim
  • Stephan Hoyer
  • TomAugspurger
  • WANG Aiyong
  • behzad nouri
  • immerrr
  • jnmclarty
  • jreback
  • pallav-fdsi
  • unutbu

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Adam Hughes | 6 Nov 17:53 2014
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Does pandas bundle any sample data?

Hi,

Most pandas examples I've seen use numpy arrays to randomly generate sample data for a DataFrame.  Is any data actually bundled with pandas, out of curiousity?  IE  

   from pandas.sample_data import fooset

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Miki Tebeka | 6 Nov 15:36 2014
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Vectorizing operation on tree like DataFrame

Greetings,

I have a DataFrame where one of the columns is the id of the parent of this row. I'd like to run some calculations on the children of some row (for example "sum"). I can do that with a for loop as below but was wondering if there's a way to do it vectorized.

    import numpy as np
   
import pandas as pd

   
# Create dummy data frame
    size
= 10
    df
= pd.DataFrame()
    df
['id'] = np.arange(size)
    df
['val'] = np.random.rand(size)
    df
['parent'] = (df['id'] % 3)  # Assign parents

   
# Calculate sum of children
    df
['sum'] = np.zeros(size)
   
for p in df.parent.unique():
        total
= df[df['parent'] == p]['val'].sum()
        df
['sum'][df['id'] == p] = total


Thanks,
Miki

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Pablo Navarro | 5 Nov 23:52 2014
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Help with pandas groupby

Hi I have a dataframe and the I want to sort it by two columns. All that is done easily by df1= df.groupby([data.exp_month2, data.strike])
The next step I am having trouble with is accesing each element. Normally I would do that using df1.get_group() but whe I groupby 2 columns this does not work.
This is how the df1 looks like. I specifically need to access Jun from exp_month2 and from that strike 188.5


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Skipper Seabold | 5 Nov 18:28 2014
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[ANN] statsmodels version 0.6.0 released

Hi All,

The statsmodels development team is happy to announce the release of
statsmodels 0.6.0. This the culmination of another year's worth of
work -- over 1500 commits from 37 different developers. It is a
combination of bug fixes and feature enhancements. All users are
encouraged to upgrade to this version.

Highlights
========

* Generalized Estimating Equation models
* Linear Mixed Effects Models
* Wrapper code for using X-12-ARIMA/X13-ARIMA-SEATS
* Substantial optimization in the ARIMA estimation code
* Some seasonal time-series features for plotting and decomposition
* Many other feature enhancments and bug fixes

Full Release Notes:
http://statsmodels.sourceforge.net/stable/release/version0.6.html
Issues Closed: http://statsmodels.sourceforge.net/stable/release/github-stats-0.6.html#issues-list-06
Installers: https://pypi.python.org/pypi/statsmodels

Thanks To
=========

git log v0.5.0..v0.6.0 --format='* %aN' | sort -u

* Alex Griffing
* Alex Parij
* Ana Martinez Pardo
* Andrew Clegg
* Ben Duffield
* Chad Fulton
* Chris Kerr
* Eric Chiang
* Evgeni Burovski
* gliptak
* Hans-Martin von Gaudecker
* Jan Schulz
* jfoo
* Joe Hand
* Josef Perktold
* jsphon
* Justin Grana
* Kerby Shedden
* Kevin Sheppard
* Kyle Beauchamp
* Lars Buitinck
* m
* Max Linke
* Miroslav Batchkarov
* Padarn Wilson
* Paul Hobson
* Pietro Battiston
* Radim Řehůřek
* Ralf Gommers
* Richard T. Guy
* Roy Hyunjin Han
* Skipper Seabold
* Tom Augspurger
* Trent Hauck
* Valentin Haenel
* Vincent Arel-Bundock
* Yaroslav Halchenko

What is it
========
Statsmodels is a Python module that allows users to explore data,
estimate statistical models, and perform statistical tests. An
extensive list of descriptive statistics, statistical tests, plotting
functions, and result statistics are available for different types of
data and each estimator. Researchers across fields may find that
statsmodels fully meets their needs for statistical computing and data
analysis in Python.

Dependencies
===========

Required dependencies:
    python >= 2.6
    numpy >= 1.5.1
    scipy >= 0.9.0
    pandas >= 0.7.1
    patsy >= 0.3.0

Build dependencies:
    Cython >= 0.20.1 (If building from github repo)
    C compiler

Optional dependencies:
    matplotlib >= 1.1 : needed for plotting
    sphinx >= 1.0.0 : needed to build the docs
    ipython >= 1.0 : needed to build the notebook examples
    nose >= 1.0.0 : needed to run the tests
    X-12-ARIMA or X-13ARIMA-SEATS : for time-series analysis. See INSTALL.

Links
======

Documentation: http://statsmodels.sourceforge.net/
Mailing List: https://groups.google.com/forum/#!forum/pystatsmodels
PyPi: https://pypi.python.org/pypi/statsmodels
Github: https://github.com/statsmodels/statsmodels/
Bug Tracker: https://github.com/statsmodels/statsmodels/issues

Cheers,

Skipper

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Tom Augspurger | 5 Nov 14:44 2014
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Pyowa

Hey all,

On the off chance that any of you are in Iowa, I'll be talking about pandas at the next [Pyowa](http://www.pyowa.org/) meeting, on November 13th.

-Tom

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Vincent Davis | 5 Nov 02:51 2014

Combining date/time columns and missing data

I am sporting some data were the "date" column in the data and other columns have time, in this example "arrival".
df = read_csv('DH_timing_prep_stata_v4.csv', sep=',', index_col='pt_id', parse_dates=[['date', 'arrival']], keep_date_col=True)
The problem I have is that when "arrival" is missing the new col, date_arrival, is not nan/nat but rather "2/14/2014 nan" for example and the column in not dtype: datetime64[ns]
How should I fix or deal with this?

Thanks

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gayathri nagarajan | 4 Nov 19:17 2014
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Chunksize not working in pandas.DataFrame.to_sql

I use 0.15 version of panda. I use the below code, but the chunksize parameter is not working,It doesn't  write the records in batches to the DB. I totally have 50,000 records in my DF and it takes more time to execute. Kindly help. 

from sqlalchemy import create_engine
import iopro.pyodbc
engine = create_engine('mssql+pyodbc://147.117.20.144/HRMS_Test')
df.to_sql('test',engine, if_exists='append',index= False, index_label=None, chunksize=100)



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0nir | 28 Oct 20:09 2014
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[pydata] Joining a calculated dataframe to itself using inner join…error while joining on the same column

I have created a dataframe 'dfExceptions' out of 'Table1', which groupsby the column 'ABC' having count(XYZ) = 1 as can be seen below.

dfCount = dfGrpby.XYZ.count() dfExceptions = dfCount[dfCount == 1]

The dataframe 'dfExceptions' looks like below -

ABC 3101 1 3102 1 3103 1 3104 1 3105 1 Name: XYZ, dtype: int64

Now, I want to join 'dfExceptions' back to the origin 'table1' & pull some more columns using an inner join. This part is not working. Please suggest. The syntax I am using is -

dfMerge = pd.merge(dfExceptions, srcDict['Table1'], on=['ABC'], how='inner')

Note : I have saved Table1 in a sourceDict called scrDict['Table1']. Also field ABC is common to both.

Thanks.

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Alexander Wütz | 25 Oct 15:36 2014
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DataFrame.merge causes MemoryError

Hi all together,

i'm currently facing an issue with pandas.

I need to merge two DataFrames (both 3 columns  +index column), one of them contains 2 Million entries, the other about 10 Million entries.
After some time of merging, my script crashes with the message: MemoryError occured from join.pyx

File "join.pyx", line 31, in pandas.algos.inner_join (pandas/algos.c:42834)

Had someone of you the same issue? Any advice, what to do?

Greetings Alex

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Gmane