Transcript From R to Python

From R to Python
Robert Mastrodomenico
Global Sports Statistics
(Edit via Slide Master) Name – Job Title
[email protected]
Schedule
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About me
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My experiences with R
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Why I moved to Python
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Whats so good about Python
Robert Mastrodomenico – Global Sports Statistics
[email protected]
About me
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Completed a PhD in statistical genetics at
University of Reading in 2008
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Worked at Smartodds from 2007 to 2011
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Setup Global Sports Statistics in 2011
Robert Mastrodomenico – Global Sports Statistics
[email protected]
My experiences with R
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Initially used R at PhD level integrated with
C to do analysis
R was the primary programming language
once I started work
R used for data analysis and maintenance
tasks
Robert Mastrodomenico – Global Sports Statistics
[email protected]
Why I moved to python
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R was used due to the ease of data
manipulation and large statistical library
However R was also being used for other
tasks such web scraping and html/xml
parsing
R was becoming the only choice used for
scripting
Robert Mastrodomenico – Global Sports Statistics
[email protected]
Why I moved to python
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I first used python for an XML parsing task
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Code was easy to write
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Results were great
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This got me curious about what else
Python had to offer
Robert Mastrodomenico – Global Sports Statistics
[email protected]
Dive into Python
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To learn more about Python I read “Dive
into Python”
Syntactically and stylistically Python was
much different to R
The more I learnt the more I used it
Robert Mastrodomenico – Global Sports Statistics
[email protected]
Setting up by myself
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In 2011 Global Sports Statistics was
created
Everything had to be setup from scratch
Used the opporunity to do something
different
Robert Mastrodomenico – Global Sports Statistics
[email protected]
Why Change?
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Development is faster in Python
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Easy to write Object Orientated code
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Fantastic Library of packages
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Sometimes a change is good!
Robert Mastrodomenico – Global Sports Statistics
[email protected]
What Python has to offer
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Pandas: Data Analysis Library
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Django: High Level Web Framework
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NumPy: Package for numerical computing
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SciPy: Routines for numerical Integration
and Optimization
Robert Mastrodomenico – Global Sports Statistics
[email protected]
What Python has to offer
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Matplotlib: 2-D plotting
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Flask: Microframework
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Mechanize: Programatic Web Browsring
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BeautifulSoup: Html Scraping
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PyQt: GUI building
Robert Mastrodomenico – Global Sports Statistics
[email protected]
Rpy2
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But what if you want to use an R package
Rpy2 allows use of any R functionality from
within Python
It also supports use of any packages that R
has to offer
Robert Mastrodomenico – Global Sports Statistics
[email protected]
Why move to Python
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Im not saying you need to
However I believe a lot of what people do
in R can be done faster in Python
Try it out whats the worst that can happen?
Robert Mastrodomenico – Global Sports Statistics
[email protected]
Thank you for you attention
Robert Mastrodomenico – Global Sports Statistics
[email protected]