README.md

In etc5523-2020/r-package-assessment-1029YanMa: Communicating With Data Course Assignment COVID19 Data Explore Package

cwdcovid19

This package contains the shiny app which explores the data of COVID-19. This is an package for cwd course assignment. You could use this package to check the daily COVID-19 cases data of Chile or Bolivia using the launch_dt() function. Or use the launch_confirm_period() function to see the confirmed cases of your selected time period in these two country.

The goal of cwdcovid19 is to …

Installation

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("etc5523-2020/r-package-assessment-1029YanMa")

Example

This package contains the dataset from the ‘coronavirous’ R package and provide a long form and a wide form of the data:

library(cwdcovid19)
library(tibble)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

coronavirus %>% 
  head(10)
#>          date province     country      lat     long      type cases
#> 1  2020-01-22          Afghanistan 33.93911 67.70995 confirmed     0
#> 2  2020-01-23          Afghanistan 33.93911 67.70995 confirmed     0
#> 3  2020-01-24          Afghanistan 33.93911 67.70995 confirmed     0
#> 4  2020-01-25          Afghanistan 33.93911 67.70995 confirmed     0
#> 5  2020-01-26          Afghanistan 33.93911 67.70995 confirmed     0
#> 6  2020-01-27          Afghanistan 33.93911 67.70995 confirmed     0
#> 7  2020-01-28          Afghanistan 33.93911 67.70995 confirmed     0
#> 8  2020-01-29          Afghanistan 33.93911 67.70995 confirmed     0
#> 9  2020-01-30          Afghanistan 33.93911 67.70995 confirmed     0
#> 10 2020-01-31          Afghanistan 33.93911 67.70995 confirmed     0

coronavirus_long %>% 
  head(10)
#>          date     country      type cases
#> 1  2020-01-22 Afghanistan confirmed     0
#> 2  2020-01-23 Afghanistan confirmed     0
#> 3  2020-01-24 Afghanistan confirmed     0
#> 4  2020-01-25 Afghanistan confirmed     0
#> 5  2020-01-26 Afghanistan confirmed     0
#> 6  2020-01-27 Afghanistan confirmed     0
#> 7  2020-01-28 Afghanistan confirmed     0
#> 8  2020-01-29 Afghanistan confirmed     0
#> 9  2020-01-30 Afghanistan confirmed     0
#> 10 2020-01-31 Afghanistan confirmed     0

coronavirus_wide %>% 
  head(10)
#> # A tibble: 10 x 5
#>    date       country     confirmed death     recovered
#>    <date>     <chr>       <list>    <list>    <list>   
#>  1 2020-01-22 Afghanistan <int [1]> <int [1]> <int [1]>
#>  2 2020-01-23 Afghanistan <int [1]> <int [1]> <int [1]>
#>  3 2020-01-24 Afghanistan <int [1]> <int [1]> <int [1]>
#>  4 2020-01-25 Afghanistan <int [1]> <int [1]> <int [1]>
#>  5 2020-01-26 Afghanistan <int [1]> <int [1]> <int [1]>
#>  6 2020-01-27 Afghanistan <int [1]> <int [1]> <int [1]>
#>  7 2020-01-28 Afghanistan <int [1]> <int [1]> <int [1]>
#>  8 2020-01-29 Afghanistan <int [1]> <int [1]> <int [1]>
#>  9 2020-01-30 Afghanistan <int [1]> <int [1]> <int [1]>
#> 10 2020-01-31 Afghanistan <int [1]> <int [1]> <int [1]>

Launch the shiny app within this package

• You could use the launch_dt() function to see the datatable of COVID-19 daily cases data of Chile or Bolivia. Please note that don’t put anything in the (), otherwise there will be an error. You could switch the country you want to explore in the shiny app after run this function.

• You could use the launch_confirm_period() function to see the line plot of confirmed cases data of Chile and Bolivia, and compare the data gap between the two countries within your selected time period. Please note that don’t put anything in the (), otherwise there will be an error. You could select your interested time period in the shiny app after run this function.

• By running the launch_app() function, you could see both the timetable and plot.

Explore more…

There’s another function: n_countries() in this package. This would provide some space for the users to explore the dataset by themselves. For example, maybe you would like to know how many countries reported newly confirmed cases on a certain date.

etc5523-2020/r-package-assessment-1029YanMa documentation built on Jan. 1, 2021, 1:09 a.m.