In RobWiederstein/retirementData: US Retirement Location Data

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/",
  out.width = "100%"
)

library(retirementData)
library(kableExtra)

Retirement Locator

Introduction

The goal of the retirementData package was to consolidate some diverse and relevant factors on where to locate for retirement. The data is located in the retirementData package but displayed on a separate dashboard here. Within the package, the main dataset is retirementLoc. Its variables are:

library(retirementData)
names(retirementLoc) |> 
  matrix(ncol = 3, byrow = T) |>
  kableExtra::kbl() |>
  kable_styling(bootstrap_options = "striped", full_width = T, position = 'center')

Installation

You can install the development and experimental version of retirementData from its repository with:

# Or the development version from GitHub:
# install.packages("devtools")
install_github("RobWiederstein/retirementData")

Load Data

Once the development package is installed, it can be loaded via:

data("retirementData")

Common Questions

The data can provide some practical guidance as to candidate locations by identifying high growth counties, reasonable housing costs, air quality and life expectancy. For example, the code below might be used to answer where housing costs are reasonable:

library(retirementData)
retirementLoc |>
        dplyr::arrange(years_to_payoff) |>
        dplyr::select(state, county, pop_2020, years_to_payoff) |>
        dplyr::slice(1:5)

Code of Conduct

Please note that the retirementData project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

RobWiederstein/retirementData documentation built on Dec. 18, 2021, 10:53 a.m.