README.md

COVID19CHN

R build
status

The goal of COVID19CHN is to help launching the shiny app with datasets and functions, which helps with basic analysis of COVID-19 daily cases of every province in China, including confirmed cases, death cases and recovered cases as of 30 September 2020.

Installation

You can install the development version of COVID19CHN from GitHub with:

# install.packages("devtools")
devtools::install_github("etc5523-2020/r-package-assessment-Lulu-Pi")

Example

This is a basic example which shows you what the package includes:

The dataset of COVID-19 daily cases in each province in China

#> # A tibble: 8,349 x 8
#>    `Province/State`   Lat  Long Date       Confirmed Deaths Recovered Month
#>    <chr>            <dbl> <dbl> <date>         <dbl>  <dbl>     <dbl> <dbl>
#>  1 Anhui             31.8  117. 2020-01-22         1      0         0     1
#>  2 Anhui             31.8  117. 2020-01-23         8      0         0     1
#>  3 Anhui             31.8  117. 2020-01-24         6      0         0     1
#>  4 Anhui             31.8  117. 2020-01-25        24      0         0     1
#>  5 Anhui             31.8  117. 2020-01-26        21      0         0     1
#>  6 Anhui             31.8  117. 2020-01-27        10      0         0     1
#>  7 Anhui             31.8  117. 2020-01-28        36      0         0     1
#>  8 Anhui             31.8  117. 2020-01-29        46      0         2     1
#>  9 Anhui             31.8  117. 2020-01-30        48      0         0     1
#> 10 Anhui             31.8  117. 2020-01-31        37      0         1     1
#> # ... with 8,339 more rows

The COVID-19 cases per month from January in China

Month Province/State Confirmed Deaths Recovered 1 Anhui 237 0 3 1 Beijing 139 1 5 1 Chongqing 211 0 1 1 Fujian 120 0 0 1 Gansu 29 0 0 1 Guangdong 436 0 11 1 Guangxi 87 0 2 1 Guizhou 29 0 2 1 Hainan 52 1 1 1 Hebei 82 1 0

COVID19 daily cases trend in some provinces or states China



etc5523-2020/r-package-assessment-Lulu-Pi documentation built on Jan. 1, 2021, 1:11 a.m.