coronavirus_spatial: coronavirus_spatial

In dmglandon/coronavirus_test: The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Dataset

Description

Create a geospatial version of the coronavirus data set for easier visualization and spatial analysis. Uses rnaturalearth for the the spatial info and generates sf objects using st_join to match up datasets.

Usage

coronavirus_spatial(
  return_shape = c("point", "polygon"),
  returncols = c("all", "simple", "reduced"),
  ...
)

Arguments

return_shape	Should the sf object returned be points for cases or polygons of countries? Defaults to 'point'.
returncols	What coluns do you want returned. Defaults to 'all', giving all columns from the original 'coronavirus' dataset as well as those returned by ne_countries. 'simple' returned those from 'coronavirus' as well as some larger scale geographic information. 'reduced' returns the info from 'simple' as well as information on population, income, and a number of ISO codes.
...	Other arguments to ne_countries

Value

An 'sf' object with either country borders as polygons or cases as points

Source

Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus website

The rnaturalearth

Examples

## Not run: 
library(ggplot2)
library(dplyr)
library(rnaturalearth)

worldmap <- ne_countries(returnclass = "sf")


coronavirus_points <- coronavirus_spatial() %>%
                       filter(date == "2020-03-08") %>%
                       filter(type == "confirmed")

coronavirus_polys <- coronavirus_spatial(return_shape = "polygon")%>%
                       filter(date == "2020-03-08")%>%
                       filter(type == "confirmed")

ggplot(worldmap) +
  geom_sf() +
  geom_sf(data = coronavirus_polys, aes(fill = log10(cases+1))) +
  geom_sf(data = coronavirus_points) +
  scale_fill_viridis_c() +
  theme_void()


## End(Not run)

dmglandon/coronavirus_test documentation built on March 23, 2020, 12:44 a.m.