countyhealth18: Countyhealthrankings.org 2018 dataset *** WORK IN PROGRESS

In ejanalysis/countyhealthrankings: Data on Health Indicators by US County, from countyhealthrankings.org

Countyhealthrankings.org 2018 dataset *** WORK IN PROGRESS

Description

This data set provides a variety of health indicators for each US county.

Usage

data('countyhealth18')

Format

A data.frame with >3000 rows (Counties) and >300 columns (variables)

Source

2014 - 2019 datasets from http://www.countyhealthrankings.org/explore-health-rankings/rankings-data-documentation
e.g.,

utils::browseURL('http://www.countyhealthrankings.org/rankings/data')
or

fname <- 'analytic_data2019_0.csv'
utils::download.file(url = paste('http://www.countyhealthrankings.org/sites/default/files/', fname, sep = ”), destfile = fname)
### maybe better to use readr::read_csv() since it is better at guessing preferred format of each column
countyhealth19 <- utils::read.csv(fname, stringsAsFactors = FALSE)
require(readr)
countyhealth19 <- readr::read_csv(fname, skip = 1, col_types = paste('ccccc', paste(rep('d',534-5), collapse = ”), sep = ”))
countyhealth19 <- as.data.frame(countyhealth19)
colfullnames19 <- readr::read_csv(fname, n_max = 1, col_names = FALSE)
colfullnames19 <- as.vector(unlist(colfullnames19)) # simpler
countyhealth19[1:5, 1:9]
save(countyhealth19, file = 'countyhealth19.RData')
save(colfullnames19, file = 'colfullnames19.RData')

2014/2015 data obtained 3/27/2015 and slightly modified to provide
5 digit FIPS as character field, and ST field as copy of State field.
The 2016 data was obtained 3/17/2016 and was not modified
The 2017 data was obtained 3/28/2018
The 2018 data was obtained 3/28/2018
The 2019 data was obtained 4/22/2019
Also see: http://www.countyhealthrankings.org/about-us

ejanalysis/countyhealthrankings documentation built on March 25, 2022, 9:15 a.m.