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Re: Data cleaning workouts

References <mailman.3697.1345708456.4697.python-list@python.org> <5042082c-5764-4c87-897a-776793753f55@r1g2000pbq.googlegroups.com>
Date 2012-08-23 23:48 -0700
From Fg Nu <fgnu32@yahoo.com>
Subject Re: Data cleaning workouts
Newsgroups comp.lang.python
Message-ID <mailman.3741.1345791030.4697.python-list@python.org> (permalink)

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Thanks. I will try the SciPy list. It was a bit of a hail mary anyway. Pretty sure elevated Python types don't actually get their hands dirty with data. ;)



----- Original Message -----
From: rusi <rustompmody@gmail.com>
To: python-list@python.org
Cc: 
Sent: Thursday, August 23, 2012 11:01 PM
Subject: Re: Data cleaning workouts

On Aug 23, 12:52 pm, Fg Nu <fgn...@yahoo.com> wrote:
> List folk,
>
> I am a newbie trying to get used to Python. I was wondering if anyone knows of web resources that teach good practices in data cleaning and management for statistics/analytics/machine learning, particularly using Python.
>
> Ideally, these would be exercises of the form: here is some horrible raw data --> here is what it should look like after it has been cleaned. Guidelines about steps that should always be taken, practices that should be avoided; basically, workflow of data analysis in Python with special emphasis on the cleaning part.

Since no one has answered, I suggest you narrow your searching from
'python' to 'scipy' (or 'numpy').
Also perhaps ipython.
And then perhaps try those specific mailing lists/fora.

Since I dont know this area much, not saying more.
-- 
http://mail.python.org/mailman/listinfo/python-list

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Thread

Data cleaning workouts Fg Nu <fgnu32@yahoo.com> - 2012-08-23 00:52 -0700
  Re: Data cleaning workouts rusi <rustompmody@gmail.com> - 2012-08-23 23:01 -0700
    Re: Data cleaning workouts Fg Nu <fgnu32@yahoo.com> - 2012-08-23 23:48 -0700
    Re: Data cleaning workouts Mark Lawrence <breamoreboy@yahoo.co.uk> - 2012-08-24 09:16 +0100

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