Skip to content

Commit

Permalink
made recomended changes
Browse files Browse the repository at this point in the history
  • Loading branch information
@joseph-palmer
joseph-palmer committed Jun 10, 2021
1 parent a7fbe00 commit 9e5d2a9
Show file tree
Hide file tree
Showing 5 changed files with 69 additions and 43 deletions.
9 changes: 5 additions & 4 deletions README.Rmd
View file
Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,8 @@ knitr::opts_chunk$set(

[![MIT license](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/epiforecasts/covidregionaldata/blob/master/LICENSE.md/) [![GitHub contributors](https://img.shields.io/github/contributors/epiforecasts/covidregionaldata)](https://github.com/epiforecasts/covidregionaldata/graphs/contributors) [![PRs Welcome](https://img.shields.io/badge/PRs-welcome-yellow.svg)](https://makeapullrequest.com/) [![GitHub commits](https://img.shields.io/github/commits-since/epiforecasts/covidregionaldata/v0.9.1.svg?color=orange)](https://github.com/epiforecasts/covidregionaldata/commit/master/) [![DOI](https://zenodo.org/badge/271601189.svg)](https://zenodo.org/badge/latestdoi/271601189) [![status](https://joss.theoj.org/papers/dd6f7acdae3b7136a3ac373ce9a0655c/status.svg)](https://joss.theoj.org/papers/dd6f7acdae3b7136a3ac373ce9a0655c)

An interface to subnational and national level COVID-19 data. For all countries supported, this includes a daily time-series of cases. Wherever available we also provide data on deaths, hospitalisations, and tests. National level data is also supported using a range of data sources as well as line list data and links to intervention data sets. This package is designed for people who wan't access to standardised Covid-19 data from 'official' sources.
Interface to subnational and national level COVID-19 data sourced from both official sources, such as Public Health England in the UK, and from other Covid-19 data collections, including the World Health Organisation (WHO), European Centre for Disease Prevention and Control (ECDC), John Hopkins University (JHU), Google Open Data and others. Covid-19 data is cleaned and processed from their raw format in an open and transparent way, allowing users to scrutinise and extend our methods. For all countries supported, this includes a daily time-series of cases. Wherever available data is provided on deaths, hospitalisations, and tests. National level data is also supported using a range of data sources as well as line list data and links to intervention data sets.
This package is designed for people who wan't access to standardised Covid-19 data from 'official' sources.

## Installation

Expand All @@ -29,7 +30,7 @@ install.packages("covidregionaldata")

Install the stable development version of the package with:

```{r, eval = TRUE}
```{r, eval = FALSE}
install.packages("covidregionaldata", repos = "https://epiforecasts.r-universe.dev")
```

Expand Down Expand Up @@ -149,7 +150,7 @@ citation("covidregionaldata")

[![Development](https://img.shields.io/badge/Wiki-lightblue.svg?style=flat)](https://github.com/epiforecasts/covidregionaldata/wiki/)

This package is the result of hard work from a number of contributors (see contributors list in the DESCRIPTION). We would particularly like to thank the [CMMID COVID-19 working group
](https://cmmid.github.io/groups/ncov-group.html) for inciteful comments, feedback and advice in designing this package.
This package is the result of hard work from a number of contributors (see contributors list in the DESCRIPTION). We would like to thank the [CMMID COVID-19 working group
](https://cmmid.github.io/groups/ncov-group.html) for inciteful comments and feedback.

We welcome contributions and new contributors! We particularly appreciate help adding new data sources for countries at sub-national level, or work on priority problems in the [issues](https://github.com/epiforecasts/covidregionaldata/issues). Please check and add to the issues, and/or add a [pull request](https://github.com/epiforecasts/covidregionaldata/pulls). For more details, start with the [contributing guide](https://github.com/epiforecasts/covidregionaldata/wiki/Contributing). For details of the steps required to add support for a dataset see the [adding data guide](https://github.com/epiforecasts/covidregionaldata/wiki/Adding-Data).
99 changes: 62 additions & 37 deletions README.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -22,9 +22,15 @@ commits](https://img.shields.io/github/commits-since/epiforecasts/covidregionald
[![DOI](https://zenodo.org/badge/271601189.svg)](https://zenodo.org/badge/latestdoi/271601189)
[![status](https://joss.theoj.org/papers/dd6f7acdae3b7136a3ac373ce9a0655c/status.svg)](https://joss.theoj.org/papers/dd6f7acdae3b7136a3ac373ce9a0655c)

An interface to subnational and national level COVID-19 data. For all
Interface to subnational and national level COVID-19 data sourced from
both official sources, such as Public Health England in the UK, and from
other Covid-19 data collections, including the World Health Organisation
(WHO), European Centre for Disease Prevention and Control (ECDC), John
Hopkins University (JHU), Google Open Data and others. Covid-19 data is
cleaned and processed from their raw format in an open and transparent
way, allowing users to scrutinise and extend our methods. For all
countries supported, this includes a daily time-series of cases.
Wherever available we also provide data on deaths, hospitalisations, and
Wherever available data is provided on deaths, hospitalisations, and
tests. National level data is also supported using a range of data
sources as well as line list data and links to intervention data sets.
This package is designed for people who wan’t access to standardised
Expand All @@ -42,8 +48,6 @@ Install the stable development version of the package with:

``` r
install.packages("covidregionaldata", repos = "https://epiforecasts.r-universe.dev")
#> Installing package into '/home/joe/R/x86_64-pc-linux-gnu-library/3.6'
#> (as 'lib' is unspecified)
```

Install the unstable development version of the package with:
Expand Down Expand Up @@ -74,7 +78,7 @@ the temporary directory by default),

``` r
start_using_memoise()
#> Using a cache at: /tmp/RtmppJ4l0P
#> Using a cache at: /tmp/RtmpLzqu5D
```

To stop using `memoise` use,
Expand All @@ -99,23 +103,34 @@ the Google COVID-19 open data project), use:
``` r
nots <- get_national_data()
#> Downloading data from https://covid19.who.int/WHO-COVID-19-global-data.csv
#> Rows: 124,313
#> Columns: 8
#> Delimiter: ","
#> chr [3]: Country_code, Country, WHO_region
#> dbl [4]: New_cases, Cumulative_cases, New_deaths, Cumulative_deaths
#> date [1]: Date_reported
#>
#> Use `spec()` to retrieve the guessed column specification
#> Pass a specification to the `col_types` argument to quiet this message
#> Cleaning data
#> Processing data
nots
#> # A tibble: 124,188 x 15
#> date un_region who_region country iso_code cases_new cases_total deaths_new deaths_total recovered_new recovered_total hosp_new hosp_total tested_new tested_total
#> <date> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2020-01-03 Asia EMRO Afghanistan AF 0 0 0 0 NA NA NA NA NA NA
#> 2 2020-01-03 Europe EURO Albania AL 0 0 0 0 NA NA NA NA NA NA
#> 3 2020-01-03 Africa AFRO Algeria DZ 0 0 0 0 NA NA NA NA NA NA
#> 4 2020-01-03 Oceania WPRO American Samoa AS 0 0 0 0 NA NA NA NA NA NA
#> 5 2020-01-03 Europe EURO Andorra AD 0 0 0 0 NA NA NA NA NA NA
#> 6 2020-01-03 Africa AFRO Angola AO 0 0 0 0 NA NA NA NA NA NA
#> 7 2020-01-03 Americas AMRO Anguilla AI 0 0 0 0 NA NA NA NA NA NA
#> 8 2020-01-03 Americas AMRO Antigua & Barbuda AG 0 0 0 0 NA NA NA NA NA NA
#> 9 2020-01-03 Americas AMRO Argentina AR 0 0 0 0 NA NA NA NA NA NA
#> 10 2020-01-03 Asia EURO Armenia AM 0 0 0 0 NA NA NA NA NA NA
#> # … with 124,178 more rows
#> # A tibble: 124,424 x 15
#> date un_region who_region country iso_code cases_new cases_total
#> <date> <chr> <chr> <chr> <chr> <dbl> <dbl>
#> 1 2020-01-03 Asia EMRO Afghanistan AF 0 0
#> 2 2020-01-03 Europe EURO Albania AL 0 0
#> 3 2020-01-03 Africa AFRO Algeria DZ 0 0
#> 4 2020-01-03 Oceania WPRO American Samoa AS 0 0
#> 5 2020-01-03 Europe EURO Andorra AD 0 0
#> 6 2020-01-03 Africa AFRO Angola AO 0 0
#> 7 2020-01-03 Americas AMRO Anguilla AI 0 0
#> 8 2020-01-03 Americas AMRO Antigua & Bar… AG 0 0
#> 9 2020-01-03 Americas AMRO Argentina AR 0 0
#> 10 2020-01-03 Asia EURO Armenia AM 0 0
#> # … with 124,414 more rows, and 8 more variables: deaths_new <dbl>,
#> # deaths_total <dbl>, recovered_new <dbl>, recovered_total <dbl>,
#> # hosp_new <dbl>, hosp_total <dbl>, tested_new <dbl>, tested_total <dbl>
```

This can also be filtered for a country of interest,
Expand Down Expand Up @@ -155,20 +170,28 @@ for example by level 1 region in the UK, use:
uk_nots <- get_regional_data(country = "UK", verbose = FALSE)
uk_nots
#> # A tibble: 6,461 x 26
#> date region region_code cases_new cases_total deaths_new deaths_total recovered_new recovered_total hosp_new hosp_total tested_new tested_total areaType cumCasesByPublish… cumCasesBySpecim… newCasesByPublis…
#> <date> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
#> 1 2020-01-30 East Mid… E12000004 NA NA NA NA NA NA NA NA NA NA <NA> NA NA NA
#> 2 2020-01-30 East of … E12000006 NA NA NA NA NA NA NA NA NA NA <NA> NA NA NA
#> 3 2020-01-30 England E92000001 2 2 NA NA NA NA NA NA NA NA nation NA 2 NA
#> 4 2020-01-30 London E12000007 NA NA NA NA NA NA NA NA NA NA <NA> NA NA NA
#> 5 2020-01-30 North Ea… E12000001 NA NA NA NA NA NA NA NA NA NA <NA> NA NA NA
#> 6 2020-01-30 North We… E12000002 NA NA NA NA NA NA NA NA NA NA <NA> NA NA NA
#> 7 2020-01-30 Northern… N92000002 NA NA NA NA NA NA NA NA NA NA <NA> NA NA NA
#> 8 2020-01-30 Scotland S92000003 NA NA NA NA NA NA NA NA NA NA <NA> NA NA NA
#> 9 2020-01-30 South Ea… E12000008 NA NA NA NA NA NA NA NA NA NA <NA> NA NA NA
#> 10 2020-01-30 South We… E12000009 NA NA NA NA NA NA NA NA NA NA <NA> NA NA NA
#> # … with 6,451 more rows, and 9 more variables: newCasesBySpecimenDate <dbl>, cumDeaths28DaysByDeathDate <dbl>, cumDeaths28DaysByPublishDate <dbl>, newDeaths28DaysByDeathDate <dbl>, newDeaths28DaysByPublishDate <dbl>,
#> # newPillarFourTestsByPublishDate <lgl>, newPillarOneTestsByPublishDate <dbl>, newPillarThreeTestsByPublishDate <dbl>, newPillarTwoTestsByPublishDate <dbl>
#> date region region_code cases_new cases_total deaths_new deaths_total
#> <date> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 2020-01-30 East Mi… E12000004 NA NA NA NA
#> 2 2020-01-30 East of… E12000006 NA NA NA NA
#> 3 2020-01-30 England E92000001 2 2 NA NA
#> 4 2020-01-30 London E12000007 NA NA NA NA
#> 5 2020-01-30 North E… E12000001 NA NA NA NA
#> 6 2020-01-30 North W… E12000002 NA NA NA NA
#> 7 2020-01-30 Norther… N92000002 NA NA NA NA
#> 8 2020-01-30 Scotland S92000003 NA NA NA NA
#> 9 2020-01-30 South E… E12000008 NA NA NA NA
#> 10 2020-01-30 South W… E12000009 NA NA NA NA
#> # … with 6,451 more rows, and 19 more variables: recovered_new <dbl>,
#> # recovered_total <dbl>, hosp_new <dbl>, hosp_total <dbl>, tested_new <dbl>,
#> # tested_total <dbl>, areaType <chr>, cumCasesByPublishDate <dbl>,
#> # cumCasesBySpecimenDate <dbl>, newCasesByPublishDate <dbl>,
#> # newCasesBySpecimenDate <dbl>, cumDeaths28DaysByDeathDate <dbl>,
#> # cumDeaths28DaysByPublishDate <dbl>, newDeaths28DaysByDeathDate <dbl>,
#> # newDeaths28DaysByPublishDate <dbl>, newPillarFourTestsByPublishDate <lgl>,
#> # newPillarOneTestsByPublishDate <dbl>,
#> # newPillarThreeTestsByPublishDate <dbl>,
#> # newPillarTwoTestsByPublishDate <dbl>
```

Now we have the data we can create plots, for example the time-series of
Expand Down Expand Up @@ -209,7 +232,9 @@ using the following,
#>
#> To cite covidregionaldata in publications use:
#>
#> Sam Abbott, Katharine Sherratt, Joe Palmer, Richard Martin-Nielsen, Jonnie Bevan, Hamish Gibbs, and Sebastian Funk (2020). covidregionaldata: Subnational Data for the COVID-19 Outbreak, DOI:
#> Sam Abbott, Katharine Sherratt, Joe Palmer, Richard Martin-Nielsen,
#> Jonnie Bevan, Hamish Gibbs, and Sebastian Funk (2020).
#> covidregionaldata: Subnational Data for the COVID-19 Outbreak, DOI:
#> 10.5281/zenodo.3957539
#>
#> A BibTeX entry for LaTeX users is
Expand All @@ -230,10 +255,10 @@ using the following,
[![Development](https://img.shields.io/badge/Wiki-lightblue.svg?style=flat)](https://github.com/epiforecasts/covidregionaldata/wiki/)

This package is the result of hard work from a number of contributors
(see contributors list in the DESCRIPTION). We would particularly like
to thank the [CMMID COVID-19 working
(see contributors list in the DESCRIPTION). We would like to thank the
[CMMID COVID-19 working
group](https://cmmid.github.io/groups/ncov-group.html) for inciteful
comments, feedback and advice in designing this package.
comments and feedback.

We welcome contributions and new contributors\! We particularly
appreciate help adding new data sources for countries at sub-national
Expand Down
Loading

0 comments on commit 9e5d2a9

Please sign in to comment.