{"id":13857878,"url":"https://github.com/underthecurve/r-data-cleaning-tricks","last_synced_at":"2026-01-30T05:49:52.739Z","repository":{"id":77711684,"uuid":"93438447","full_name":"underthecurve/r-data-cleaning-tricks","owner":"underthecurve","description":"Data Cleaning Tricks in R for Boston University's \"Storytelling with Data\" 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Tricks for cleaning your data in R\n\nData + Code for **\"Tricks for cleaning your data in R\"** at the [Storytelling with Data](https://www.bu.edu/com/data-storytelling/) workshop at Boston University on Tuesday, June 6th 2017.\n\nEquivalent materials for **\"Advancing with data visualization in R using ggplot2\"** available [here](https://github.com/underthecurve/r-dataviz-ggplot2).\n\n## Links to install R and RStudio\n\n* [R](https://www.r-project.org/): website for the R software\n* [RStudio](https://www.rstudio.com/): website for RStudio, a powerful graphical user interface for R\n\n## Files included\n\n### Annotated code and step-by step instructions for the workshop\n* [R-datacleaning-tricks.md](https://github.com/underthecurve/r-data-cleaning-tricks/blob/master/R-datacleaning-tricks.md): Markdown file (for viewing on the web)\n* [R-datacleaning-tricks.pdf](https://github.com/underthecurve/r-data-cleaning-tricks/blob/master/R-datacleaning-tricks.pdf): PDF file (for printing out)\n\n### R code\n* [R-datacleaning-tricks.R](https://github.com/underthecurve/r-data-cleaning-tricks/blob/master/R-datacleaning-tricks.R): the R code, which can be run in RStudio\n\n### Underlying data needed to run the R code\n* [employee-earnings-report-2016.csv](https://github.com/underthecurve/r-data-cleaning-tricks/blob/master/employee-earnings-report-2016.csv): data on earnings for Boston's municipal employees, from the city's [open data portal](https://data.boston.gov/dataset/employee-earnings-report)\n* [unemployment.xlsx](https://github.com/underthecurve/r-data-cleaning-tricks/blob/master/unemployment.xlsx): data on global unemployment rates from 2012 to 2016, from the [International Monetary Fund](https://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx)\n* [attendees.csv](https://github.com/underthecurve/r-data-cleaning-tricks/blob/master/attendees.csv): data on some attendees of this workshop, with names and identifying information removed\n\n## How to follow this workshop\n\n* You can clone or download this repository by clicking on the green button above, \"Clone or download\"\n* Open the `.R` file in RStudio \n* Follow along by reading the `.md` file online or printing the `.pdf` file out by clicking the Github links above\n\n## Questions / Feedback?\n\nychristinezhang at gmail dot com\n\nor on Twitter\n\n[@christinezhang](https://twitter.com/christinezhang)\n\n\u003ca rel=\"license\" href=\"http://creativecommons.org/licenses/by/4.0/\"\u003e\u003cimg alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by/4.0/88x31.png\" /\u003e\u003c/a\u003e\u003cbr /\u003eThis work is licensed under a \u003ca rel=\"license\" href=\"http://creativecommons.org/licenses/by/4.0/\"\u003eCreative Commons Attribution 4.0 International License\u003c/a\u003e.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Funderthecurve%2Fr-data-cleaning-tricks","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Funderthecurve%2Fr-data-cleaning-tricks","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Funderthecurve%2Fr-data-cleaning-tricks/lists"}