https://github.com/solanto/covid-19-mapped
😷 a user-friendly COVID-19 dashboard written for Shiny, featuring on-the-fly map switching and digestible summaries
https://github.com/solanto/covid-19-mapped
csse-data dashboard data-science gis gis-data jhu mapping maps r rlang rshiny rshinydashboard shiny shiny-apps shinydashboard
Last synced: 5 months ago
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😷 a user-friendly COVID-19 dashboard written for Shiny, featuring on-the-fly map switching and digestible summaries
- Host: GitHub
- URL: https://github.com/solanto/covid-19-mapped
- Owner: solanto
- Created: 2021-11-25T19:24:16.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2022-01-26T19:29:18.000Z (over 4 years ago)
- Last Synced: 2024-01-30T00:16:22.180Z (over 2 years ago)
- Topics: csse-data, dashboard, data-science, gis, gis-data, jhu, mapping, maps, r, rlang, rshiny, rshinydashboard, shiny, shiny-apps, shinydashboard
- Language: R
- Homepage: https://solanto.shinyapps.io/covid-19-mapped
- Size: 765 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
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README
# COVID-19 mapped
Written for JHU's EN.560.291 CaSE Coding course.
## description
This app:
1. imports the latest COVID-19 data from [HealthData.gov](https://healthdata.gov) and the [Johns Hopkins Center for Systems Science and Engineering](https://systems.jhu.edu/)
2. wrangles and geocodes the data
3. generates choropleth maps and textual summaries from the data
4. defines an interactive [Shiny](https://www.rstudio.com/products/shiny/) dashboard
5. handles user input to switch maps and summaries on-the-fly
All data wrangling and view generation happens in [`global.r`](global.r). Using these results, the Shiny app is then defined in [`ui.r`](ui.r) and [`server.r`](server.r). Finally, the app is styled as detailed in [`styles.scss`](styles.scss), taking inspiration from Statistics Sweden's [Kommuner i siffror](https://kommunsiffror.scb.se/) (*Municipalities in Numbers*) visualization.
## usage
### online
Access the app online on [shinyapps.io](https://solanto.shinyapps.io/covid-19-mapped/).
### local
To run the app locally, you'll need to have an [R interpreter](https://www.r-project.org/) installed. As well, to build dependencies, you will need [Rtools](https://cran.r-project.org/bin/windows/Rtools/).
Through an R shell, install the project's dependencies.
```R
install.packages(c("shiny", "magrittr", "dplyr", "leaflet", "formattable", "sass", "remotes"))
library(remotes)
install_github("hrbrmstr/albersusa")
```
Clone the repository and run the following in an R shell whose working directory is the repository's root directory:
```R
library(shiny)
runApp()
```
Alternatively, open the project in RStudio and run the app using the IDE's built-in Shiny capabilities.