https://frankzheng.me/en/ Recent content in Frank Zheng's Blog on Frank Zheng | 郑翔 Hugo -- gohugo.io en-us Tue, 31 Jan 2017 00:00:00 +0000 https://frankzheng.me/en/2022/06/run-shiny-apps-locally/ Mon, 06 Jun 2022 00:00:00 +0000 https://frankzheng.me/en/2022/06/run-shiny-apps-locally/ The R code in this post is also available as this GitHub Gist. The easiest way to host and run shiny apps is run them locally. Instead of hosting it in our own server or publishing to shinyapps.io , most of the time, we just need to share and use it internally. Fortunately, shiny::runApp() provides an option to make this work, as it already allows users to specify the port that the application should listen on. https://frankzheng.me/en/2020/06/tsa-checkpoint-travel-number/ Wed, 24 Jun 2020 00:00:00 +0000 https://frankzheng.me/en/2020/06/tsa-checkpoint-travel-number/ TSA Checkpoint Travel Number Comparison Between 2019 and 2020 This data visualization is designed to track when the number of flight passengers will recover back to the pre-covid level. https://frankzheng.me/en/2020/04/knitr-root-directory/ Tue, 21 Apr 2020 00:00:00 +0000 https://frankzheng.me/en/2020/04/knitr-root-directory/ Yes, we all love to use the magical knitr package (Thanks to Yihui) to render .Rmd for reports. And I honestly think knitr, .Rmd, and R Studio makes R programming much better and simpler. However, here’s a minor defect about knitr, by defult, it will only search the same directory as your .Rmd file to locate the dataset or files you need to pull in. It works fine when you have all your data files and . https://frankzheng.me/en/2020/01/wuhan-sir/ Fri, 24 Jan 2020 00:00:00 +0000 https://frankzheng.me/en/2020/01/wuhan-sir/ Coronavirus Disease 2019 (COVID-19) was identified as the cause of a cluster of pneumonia cases in Wuhan, a city in the Hubei Province of China, at the end of 2019. It subsequently spread throughout China and elsewhere, becoming a global health emergency. In February 2020, the World Health Organization (WHO) designated the disease COVID-19, which stands for coronavirus disease 2019. This post will use current data with SIR model and (try to) forcast when the number of coronavirous infected patients reaches its peak and eventually declines.