Academic Resources
December 31, 2019 - 2 minutes
I am passionate about automation in my daily work. Here are some academic resources that I created to facilitate my research and teaching. I will be very happy if these tools could help others.
- scrapol: This is an R package developed for automatic data collection with the help of Hadley Wickham’s
rvest
package. It was written specifically for collecting information about city councilmembers' Party IDs and districts given their URLs on Ballotpedia. This package makes automatic data collection possible with a URL alone, and users don’t need to have any knowledge about web scraping. This package has not been submitted to CRAN yet, but it is available on my Github page. If interested, please click here to check it out. - pqview: This is a simple web app or dashboard developed with Shiny to facilitate teaching. When I taught statistics, a critical topic was probabilities and quantiles in a continuous distribution. The traditional way of covering this topic is to resort to some Z tables or T tables, but students usually get frustrated with dense decimals in a table. Besides, ‘static’ tables cannot display all possible degrees of freedom, quantiles and significance levels. For these reasons, I created this dashboard to visualize the relationship between quantiles and probabilities in four widely used continuous distributions: standard normal distribution, Student’s t-distribution, F distribution, and Chi-square distribution. This dashboard permits both one-tailed and two-tailed scenarios. It is available via this link.
- rselect: Group projects are important teaching components to develop team spirit. This web app can help instructors group or sample students randomly. It supports two application scenarios. First, instructors can divide a list of students into a designated number of groups. Second, they can also extract a random sample of students given a list and a sample size. The dashboard allows users to upload a roster file. Additionally, it also permits inputting names manually with a comma as a separator. After the grouping or sampling is done, users can export the results as a csv file by making use of the download buttons. The link to the dashboard is here.
If you run into any issues while using these resources, please feel free to contact me at huizhou68@gmail.com.