underthecurve / R Data Cleaning Tricks
Data Cleaning Tricks in R for Boston University's "Storytelling with Data" workshop
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Tricks for cleaning your data in R
Data + Code for "Tricks for cleaning your data in R" at the Storytelling with Data workshop at Boston University on Tuesday, June 6th 2017.
Equivalent materials for "Advancing with data visualization in R using ggplot2" available here.
Links to install R and RStudio
- R: website for the R software
- RStudio: website for RStudio, a powerful graphical user interface for R
Files included
Annotated code and step-by step instructions for the workshop
- R-datacleaning-tricks.md: Markdown file (for viewing on the web)
- R-datacleaning-tricks.pdf: PDF file (for printing out)
R code
- R-datacleaning-tricks.R: the R code, which can be run in RStudio
Underlying data needed to run the R code
- employee-earnings-report-2016.csv: data on earnings for Boston's municipal employees, from the city's open data portal
- unemployment.xlsx: data on global unemployment rates from 2012 to 2016, from the International Monetary Fund
- attendees.csv: data on some attendees of this workshop, with names and identifying information removed
How to follow this workshop
- You can clone or download this repository by clicking on the green button above, "Clone or download"
- Open the
.Rfile in RStudio - Follow along by reading the
.mdfile online or printing the.pdffile out by clicking the Github links above
Questions / Feedback?
ychristinezhang at gmail dot com
or on Twitter
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