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Scalable Data Processing in R

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Duration

4 hours

video

15 videos

Module

49 exercises

Learn how to write scalable code for working with big data in R using the bigmemory and iotools packages.

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Datasets are often larger than available RAM, which causes problems for R programmers since by default all the variables are stored in memory. You’ll learn tools for processing, exploring, and analyzing data directly from disk. You’ll also implement the split-apply-combine approach and learn how to write scalable code using the bigmemory and iotools packages. In this course, you’ll make use of the Federal Housing Finance Agency’s data, a publicly available data set chronicling all mortgages that were held or securitized by both Federal National Mortgage Association (Fannie Mae) and Federal Home Loan Mortgage Corporation (Freddie Mac) from 2009-2015.

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Scalable Data Processing in R
Scalable Data Processing in R
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