https://github.com/javierluraschi/covid

Novel Coronavirus(2019-nCoV) updates from WHO daily reports
https://github.com/javierluraschi/covid

2019-ncov coronavirus corvid corvid-2019 dataset rstats

Last synced: 3 days ago
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Novel Coronavirus(2019-nCoV) updates from WHO daily reports

• Host: GitHub
• URL: https://github.com/javierluraschi/covid
• Owner: javierluraschi
• License: mit
• Created: 2020-02-29T00:21:45.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2020-06-23T20:57:01.000Z (over 4 years ago)
• Last Synced: 2024-12-19T04:51:40.208Z (17 days ago)
• Topics: 2019-ncov, coronavirus, corvid, corvid-2019, dataset, rstats
• Language: R
• Size: 34.8 MB
• Stars: 7
• Watchers: 5
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.Rmd
  • License: LICENSE

Awesome Lists containing this project

README

        
---

title: "COVID Updates"

output:

  github_document:

    fig_width: 9

    fig_height: 4

---

This repo provides hourly updates from the [World Helath Organization](https://www.who.int/) [Coronavirus disease (COVID-2019) situation reports](https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports/) in [CSV](https://github.com/javierluraschi/covid/tree/datasets) and [pins](https://pins.rstudio.com) format.

From R, you can query the list of available datasets as follows:

```{r}

library(pins)

board_register_datatxt("https://raw.githubusercontent.com/javierluraschi/covid/datasets/data.txt", "covid")

pin_find(board = "covid")

```

You can then retrieve specific tables from the daily reports as follows:

```{r}

pin_get("covid-20200227-1", board = "covid")

```

Do notice that this dataset come straight from the PDF files, while the data is kept up-to-date by parsing it as soon as it's released, the headers still need to be cleaned up and some tables joined together.

The CSV files can be found under [covid/tree/datasets](https://github.com/javierluraschi/covid/tree/datasets), a cleaned up dataset can be found in other repos like [ramikrispin/coronavirus-csv](https://github.com/RamiKrispin/coronavirus-csv) and downloaded with pins as follows:

```{r}

covid <- pin("https://raw.githubusercontent.com/RamiKrispin/coronavirus-csv/master/coronavirus_dataset.csv") %>%

  read.csv() %>% tibble::as_tibble() %>% print()

```

```{r}

library(dplyr, warn.conflicts = FALSE)

library(ggplot2)

filter(covid, type == "confirmed") %>%

  group_by(date) %>%

  summarise(confirmed = sum(cases)) %>%

  arrange(date) %>%

  mutate(date = as.Date(date), confirmed = cumsum(confirmed)) %>%

  ggplot(aes(x=date, y=confirmed)) + geom_line() + theme_light()

```