(Edit via Slide Master) Name – Job Title From R to Python Robert Mastrodomenico Global Sports Statistics.

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Presentation transcript:

(Edit via Slide Master) Name – Job Title From R to Python Robert Mastrodomenico Global Sports Statistics

Robert Mastrodomenico – Global Sports Statistics Schedule About me My experiences with R Why I moved to Python Whats so good about Python

Robert Mastrodomenico – Global Sports Statistics About me Completed a PhD in statistical genetics at University of Reading in 2008 Worked at Smartodds from 2007 to 2011 Setup Global Sports Statistics in 2011

Robert Mastrodomenico – Global Sports Statistics My experiences with R 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 Why I moved to python 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 Why I moved to python I first used python for an XML parsing task Code was easy to write Results were great This got me curious about what else Python had to offer

Robert Mastrodomenico – Global Sports Statistics Dive into Python 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 Setting up by myself 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 Why Change? Development is faster in Python Easy to write Object Orientated code Fantastic Library of packages Sometimes a change is good!

Robert Mastrodomenico – Global Sports Statistics What Python has to offer Pandas: Data Analysis Library Django: High Level Web Framework NumPy: Package for numerical computing SciPy: Routines for numerical Integration and Optimization

Robert Mastrodomenico – Global Sports Statistics What Python has to offer Matplotlib: 2-D plotting Flask: Microframework Mechanize: Programatic Web Browsring BeautifulSoup: Html Scraping PyQt: GUI building

Robert Mastrodomenico – Global Sports Statistics Rpy2 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 Why move to Python 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 Thank you for you attention