https://github.com/bgonzalezbustamante/ncov2019
query stats of infected coronavirus cases
Science Score: 23.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
○codemeta.json file
-
○.zenodo.json file
-
✓DOI references
Found 4 DOI reference(s) in README -
✓Academic publication links
Links to: medrxiv.org -
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (11.8%) to scientific vocabulary
Last synced: 10 months ago
·
JSON representation
Repository
query stats of infected coronavirus cases
Basic Info
- Host: GitHub
- Owner: bgonzalezbustamante
- Default Branch: master
- Homepage: https://guangchuangyu.github.io/nCov2019/
- Size: 12.4 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Fork of GuangchuangYu/nCov2019
Created about 6 years ago
· Last pushed about 6 years ago
https://github.com/bgonzalezbustamante/nCov2019/blob/master/
# nCov2019: An R package with real-time data, historical data and Shiny app
## :house: Data Sources
#### Real-time data
+ [Tencent SARS-COV-2 website](https://news.qq.com/zt2020/page/feiyan.htm).
#### Historical data (three public data sources):
1. [Wuhan-2019-nCoV GitHub repository](https://github.com/canghailan/Wuhan-2019-nCoV).
- This data source contains detailed city level data in China, and country level data in worldwide.
2. [National Health Commission of the Peoples Republic of China](http://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml)
- This data source contains province level data in China.
3. [DXY.cn. Pneumonia. 2020.](https://ncov.dxy.cn/ncovh5/view/pneumonia)
- We collect historical city level data in China from this source.
4. [](https://i.snssdk.com/ugc/hotboard_fe/hot_list/template/hot_list/forum_tab.html)
- We collect historical province level data for oversea countries form this source. (Start from 2020-03-15)
The user can obtain the historical provincial data in `China`, `South Korea`, `United States`, `Japan`, `Iran`, `Italy`, `Germany` and `United Kingdom` now.
For example, the below will return the historical data for Italy.
```r
library(nCov2019)
nCov2019_set_country(country = 'Italy')
x['province'] # this will return Italy data only.
```
**For more details see our [vignette](https://guangchuangyu.github.io/nCov2019/), [Preprint](https://www.medrxiv.org/content/10.1101/2020.02.25.20027433v2), and [Shiny app](http://www.bcloud.org/e/).**
## :writing\_hand: Authors
+ Guangchuang YU (package creator and maintainer)
- School of Basic Medical Sciences, Southern Medical University
-
+ Xijin Ge (Shiny app)
- Department of Mathematics and Statistics, South Dakota State University
-
+ Tianzhi Wu, Erqiang Hu and Patrick Tung (contributors)
If you use `nCov2019`, please cite the following preprint:
Tianzhi Wu, Erqiang Hu, Xijin Ge\*, Guangchuang Yu\*. [Open-source analytics tools for studying the COVID-19 coronavirus outbreak](https://www.medrxiv.org/content/10.1101/2020.02.25.20027433v2). **medRxiv**, 2020.02.25.20027433. doi:
## :arrow\_double\_down: Installation
Get the development version from github:
``` r
## install.packages("remotes")
remotes::install_github("GuangchuangYu/nCov2019")
```
+ `get_nCov2019()` to query online latest information
+ `load_nCov2019()` to get historical data
+ `nCov2019_set_country()` to set country options
+ `summary` and `[` to access data
+ `plot` to present data on map
+ `dashboard()` to open Shiny app dashboard
## :art: Example
Run the script [example.R](example.R) in R using `source("example.R")`, will produce the following figure:

## :book: Documents
+ **online vignette**: [nCov2019 for studying COVID-19 coronavirus outbreak](https://guangchuangyu.github.io/nCov2019/)
+ [An R Package to Explore the Novel Coronavirus](https://towardsdatascience.com/an-r-package-to-explore-the-novel-coronavirus-590055738ad6)
+ [R](https://mp.weixin.qq.com/s/_0D8ENb-4lGm4UV16Ok28A)
+ [](https://mp.weixin.qq.com/s/lrQWGKj-mReWrxfi_4Sw9A)
+ [](https://mp.weixin.qq.com/s/iWyOvOoLDl2q9VCUEDY52A)
+ [nCov2019](https://mp.weixin.qq.com/s/wTqeSVWZCH3YP8YzAj20EQ)
+ [nCov2019](https://mp.weixin.qq.com/s/u50yCKAGJfrcXgvHHhLbsA)
+ [](https://mp.weixin.qq.com/s/tTmd7IJt9U9en62Hl1kBnw)
+ [RnCov-2019gganimate](https://mp.weixin.qq.com/s/54cAS4jOJEJw3_SvRJUjDg)
+ [](https://mp.weixin.qq.com/s/ZIZr9zmxVIqjlAFQdK-t7A)
+ [](https://mp.weixin.qq.com/s/lY1TpDqrMce5fB0_GsTlgA)
+ [](https://mp.weixin.qq.com/s/m1FW20a7RJUhZ7MISkPrrg)
## :chart\_with\_upwards\_trend: Shiny Apps that use `nCov2019`
+ [Coronavirus Tracking dashboard](https://coronavirus.john-coene.com/)
+ [Novel Coronavirus Pneumonia (NCP-2019) Dashboard](https://github.com/gaospecial/NCPdashboard)
+ [Coronavirus COVID-19 outbreak statistics and forecast](http://www.bcloud.org/e/)
+ [](http://www.bcloud.org/v/)
+ [](http://14.215.135.56:3838/COVID-19-public/)
## :sparkling\_heart: Collected in resource list
+ [Open-Source-COVID-19](https://weileizeng.github.io/Open-Source-COVID-19/)
+ [Top 7 R resources on COVID-19 Coronavirus](https://www.statsandr.com/blog/top-r-resources-on-covid-19-coronavirus/)
+ [COVID-19 Coronavirus Disease resources](http://covirusd.com/resources/)
Owner
- Name: Bastián González-Bustamante
- Login: bgonzalezbustamante
- Kind: user
- Location: Oxford
- Company: University of Oxford
- Website: https://bgonzalezbustamante.com
- Twitter: bastiangb
- Repositories: 8
- Profile: https://github.com/bgonzalezbustamante
DPhil (PhD) in Politics programme, Department of Politics and International Relations and St Hilda's College, University of Oxford.