README.md
In hmsidwR: Health Metrics and the Spread of Infectious Diseases

hmsidwR - Health Metrics and the Spread of Infectious Diseases

The goal of {hmsidwR} is to provide the set of data used in the Health Metrics and the Spread of Infectious Diseases Machine Learning Applications and Spatial Modeling Analysis book.

install.packages("hmsidwR")

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

# install.packages("devtools")
devtools::install_github("Fgazzelloni/hmsidwR")

This is a basic example which shows you how to solve a common problem:

library(hmsidwR)
library(dplyr)
data(sdi90_19)
head(subset(sdi90_19, location == "Global"))
#> # A tibble: 6 × 3
#>   location  year value
#>   <chr>    <dbl> <dbl>
#> 1 Global    1990 0.511
#> 2 Global    1991 0.516
#> 3 Global    1992 0.521
#> 4 Global    1993 0.525
#> 5 Global    1994 0.529
#> 6 Global    1995 0.534

sdi_avg <- sdi90_19 |>
  group_by(location) |>
  reframe(sdi_avg = round(mean(value), 3))

head(sdi_avg)
#> # A tibble: 6 × 2
#>   location       sdi_avg
#>   <chr>            <dbl>
#> 1 Aceh             0.58 
#> 2 Acre             0.465
#> 3 Afghanistan      0.238
#> 4 Aguascalientes   0.606
#> 5 Aichi            0.846
#> 6 Akita            0.792

sdi90_19 |>
  filter(location %in% c("Global", "Italy", "France", "Germany")) |>
  group_by(location) |>
  reframe(sdi_avg = round(mean(value), 3)) |>
  head()
#> # A tibble: 4 × 2
#>   location sdi_avg
#>   <chr>      <dbl>
#> 1 France     0.79 
#> 2 Germany    0.863
#> 3 Global     0.58 
#> 4 Italy      0.763