In this assignment, you’ll practice collaborating around a code project with GitHub. You could consider our collective work as building out a book of examples on how to use TidyVerse functions.

You have two tasks:

1. Create an Example Using one or more TidyVerse packages, and any dataset from fivethirtyeight.com or Kaggle, create a programming sample “vignette” that demonstrates how to use one or more of the capabilities of the selected TidyVerse package with your selected dataset. (25 points)

2. Extend an Existing Example Using one of your classmate’s examples (as created above), extend his or her example with additional annotated code. (15 points)

You should fork the provided repository and then clone it locally if you wish. Once you have code to submit, you should make a pull request on the shared repository. Minimally, you should submit .Rmd files. Ideally, you should also submit an .md file and update the README.md file with your example.

If you are going to use RStudio as your version control software, make sure to add *.Rproj and .gitignore to your .gitignore file before you make any commits. Otherwise you run the risk of trying to push that to the master repository in a pull request.

After you’ve completed both parts of the assignment, please submit your GitHub handle name in the submission link provided in the week 1 folder! This will let your instructor know that your work is ready to be graded.

You should complete both parts of the assignment and make your submission no later than end of day on Sunday, November 24th.

• GitHub repository: https://github.com/acatlin/FALL2019TIDYVERSE
• FiveThirtyEight.com datasets: https://data.fivethirtyeight.com/
• Kaggle datasets: https://www.kaggle.com/datasets

Author: Jai Jeffryes

A document term matrix (DTM) is a data structure that can serve as the input to machine learning models. Tidyverse tools can create this structure.

cf. candidate_email_dtm.Rmd

Author: Donny Lofland

FiveThirtyEight has aggregated polling data from a number of sources tracking Trump's approval rating since January 2017. In this programming vignette, we will use TidyVerse packages to load, manipulate, summarize and plot Trump's approval rating over time.

cf. trump_approval_ratings.Rmd

TidyVerse Assignment:

Part 1: Editor: Euclid Zhang Date Completed: 11/11/2019 Action: Create a demonstration of how to use the functions in the purrr package. Rpubs: http://rpubs.com/ezaccountz/TidyVerse_Assignment_EZ

Part 2: Creator: Lin Li Source: https://github.com/lincarrieli/FALL2019TIDYVERSE Updater: Euclid Zhang Date Completed: 11/17/2019 Action: Update with a few examples from TidyVerse package.