Selected Topics from Tidyverse

[daniellecrobinson]

Please link to course content here! And add comments, notes!

[erictleung]

Hey there! I've been putting together the presentation for this. I was broadly going to cover all the different packages that the tidyverse package includes. In general, the tidyverse is single package in R which you can import, which imports a variety of other packages that is designed to work together. All of the packages that are in the tidyverse are:

• broom (convert statistical analysis objects to tidy data frames)
• DBI (database interface)
• dplyr (grammar of data manipulation)
• forcats (working with categorical variable)
• ggplot2 (plotting using grammar of graphics)
• haven (import and export SPSS, Stata, and SAS files)
• httr (works with URLs and HTTP)
• hms (pretty time of day)
• jsonlite (robust, high performance JSON parser)
• lubridate (deal with date data easier)
• magrittr (pipe operator)
• modelr (modelling functions that work with pipe)
• purrr (functional programming in R)
• readr (read tabular data)
• readxl (read Excel files)
• stringr (manipulate and analyze text)
• tibble (alternate data frame)
• rvest (easily scape (harvest) web pages)
• tidyr (tidy up data)
• xml2 (work with XML files)

Let me know which packages sound the most interesting and I can cover them

[laderast]

I think the #1 important concept is to talk about tidy data and how it might differ from data as it's commonly stored in spreadsheets. Then talk about how you can make tidy data (dplyr). Then you can talk about things you can do with tidy data (ggplot2, etc). I might organize the applications of tidy data in terms of a FAQ.

[erictleung]

I can probably give a brief overview of Hadley's paper on "Tidy Data". I think that gives a foundation to the rest of the packages in the tidyverse.

[matthewsundling]

I'm interested in this topic, I'll be there.

[erictleung]

To make this section more accessible and easier to understand what this talk will be about ("What is this tidyverse anyways?"), we can change this presentation title into something like "Intro to Cleaning and Manipulating Your Data in R"

[laderast]

Here is the title of our talk on thursday:

From Messy to Tidy: Intro to Data Carpentry in R

Eric Leung and Ted Laderas talk about getting your data into R and doing some simple manipulations using tidyverse packages.