R by Example: Analyzing RECS using data.table

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In the R by Example series of workshops, we’ll discuss example analyses in R as a vehicle for learning  commonly used tools and programming patterns.  The “Analyzing RECS using data.table” workshop will focus on analyzing winter home temperatures in the US using data from the Residential Energy Consumption Survey (https://www.eia.gov/consumption/residential/).  We’ll use the data.table package for data manipulations and ggplot2 for plotting.  The workshop will be organized in a parallel fashion, with participants given time to build an analysis from scratch by adapting presented examples step by step. In the process, participants will become familiar with core data.table functionality including its pivot methods.  This workshop is geared towards beginner to intermediate R users or those new to data.table.

Data management in R with data.table

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Matt Dowle, author of the data.table package, describes it as, “provid[ing] a high-performance version of base R’s data.frame with syntax and feature enhancements for ease of use, convenience and programming speed.” In this workshop I will first introduce the data.table syntax using generic SQL and the dplyr R package as reference points.  Topics to be discussed include subsetting, aggregating, and merging data frames.  I will then discuss updating by reference and its role in efficiently working with large data sets.  Other advanced uses of the powerful data.table syntax will be covered as time permits.

If you have questions about this workshop, please send an email to jbhender@umich.edu