worldhdi

The goal of worldhdi is to present Human Development Index Data from 1990-2022 in a tidy format. The data is sourced from the United Nations Development

Installation

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

# install.packages("devtools")
devtools::install_github("openwashdata/worldhdi")

## Run the following code in console if you don't have the packages
## install.packages(c("dplyr", "knitr", "readr", "stringr", "gt", "kableExtra"))
library(dplyr)
library(knitr)
library(readr)
library(stringr)
library(gt)
library(kableExtra)
library(tidyverse)
library(lubridate)

Alternatively, you can download the individual datasets as a CSV or XLSX file from the table below.

dataset	CSV	XLSX
worldhdi	Download CSV	Download XLSX

Data

The package provides access to tidy human development index (HDI) for 193 countries from 1990-2022. The data is sourced from the United Nations Development Programme (UNDP)

library(worldhdi)

worldhdi

The dataset worldhdi contains data about human development index (HDI) for 193 countries from 1990-2022. It has 210 observations and 17 variables

worldhdi |> 
  head(3) |> 
  gt::gt() |>
  gt::as_raw_html()

hdi_rank	country	hdi_1990	hdi_2000	hdi_2010	hdi_2015	hdi_2019	hdi_2020	hdi_2021	hdi_2022	rank_change_2015_2022	avg_growth_1990_2000	avg_growth_2000_2010	avg_growth_2010_2022	avg_growth_1990_2022	tier_hdi	iso3c
1	Switzerland	0.850	0.885	0.940	0.952	0.960	0.957	0.965	0.967	0	0.4043282	0.6047435	0.2362672	0.4038199	Very High	CHE
2	Norway	0.845	0.914	0.938	0.952	0.961	0.963	0.964	0.966	-1	0.7880282	0.2595300	0.2454164	0.4190857	Very High	NOR
3	Iceland	0.834	0.895	0.927	0.948	0.958	0.955	0.957	0.959	0	0.7084005	0.3519162	0.2832129	0.4373840	Very High	ISL

For an overview of the variable names, see the following table.

variable_name	variable_type	description
hdi_rank	double	World Rank in Human Development Index as of 2022
country	double	Official name of the country
hdi_1990	double	HDI in 1990
hdi_2000	double	HDI in 2000
hdi_2010	double	HDI in 2010
hdi_2015	double	HDI in 2015
hdi_2019	double	HDI in 2019
hdi_2020	double	HDI in 2020
hdi_2021	double	HDI in 2021
hdi_2022	double	HDI in 2022
rank_change_2015_2022	double	Change in rank from 2015 to 2022
avg_growth_1990_2000	double	Average annual growth in country’s HDI between 1990-2000
avg_growth_2000_2010	double	Average annual growth in country’s HDI between 2000-2010
avg_growth_2010_2022	double	Average annual growth in country’s HDI between 2010-2022
avg_growth_1990_2022	double	Average annual growth in country’s HDI between 1990-2022
tier_hdi	character	HDI Tier as defined by UNDP {Very high \[0.8-1.0), High \[0.7 - 0.8), Medium \[0.55-0.7), Low (\<0.55)}
iso3c	character	ISO3 code for the country

Example

library(worldhdi)
library(ggplot2)
library(rnaturalearthdata)
library(rnaturalearth)

# 2022 HDI worldwide 
world <- ne_countries(scale = "medium", returnclass = "sf")

world_map_data <- world |> left_join(worldhdi, by = c("iso_a3" = "iso3c"))

hdi_colors <- c("#d73027", "#fc8d59", "#fee08b", "#fdae61", "#fdd49e", "#feedde", 
                "#d9ef8b", "#a6d96a", "#66bd63", "#1a9850", "#00441b", "#003300", "#001a00", 
                "#e0e0e0") 

ggplot(data = world_map_data) +
  geom_sf(aes(fill = cut(hdi_2022, 
                         breaks = c(-Inf, 0.399, 0.449, 0.499, 0.549, 0.599, 0.649, 0.699, 
                                    0.749, 0.799, 0.849, 0.899, 0.950, Inf), 
                         labels = c("≤ 0.399", "0.400–0.449", "0.450–0.499", "0.500–0.549", 
                                    "0.550–0.599", "0.600–0.649", "0.650–0.699", 
                                    "0.700–0.749", "0.750–0.799", "0.800–0.849", 
                                    "0.850–0.899", "0.900–0.950", "≥ 0.950")))) +
  scale_fill_manual(values = hdi_colors, na.value = "gray90", name = "HDI 2022 Brackets") +
  theme_minimal() +
  labs(title = "World HDI (2022)") +
  theme(axis.text = element_blank(),
        axis.ticks = element_blank(),
        panel.grid = element_blank())

Which countries saw the biggest increases in HDI over this period?

worldhdi |> 
  filter(!is.na(avg_growth_1990_2022)) |> 
  arrange(desc(avg_growth_1990_2022)) |> 
  select(country, avg_growth_1990_2022) |>
  head(10) |> 
  gt::gt() |>
  gt::as_raw_html()

country	avg_growth_1990_2022
Mozambique	2.074138
Niger	1.955641
Myanmar	1.899160
Guinea	1.754069
Mali	1.740998
Rwanda	1.695317
Malawi	1.670162
Bangladesh	1.632927
Uganda	1.618777
China	1.547965

Trends in HDI by region

# Use the rows where country is Organisation for Economic Co-operation and Development,
# Arab States, East Asia and the Pacific, Europe and Central Asia, Latin America and the Caribbean, World and plot the hdi trends using hdi_1990, hdi_2000, hdi_2010, hdi_2015, hdi_2022

worldhdi |>
  filter(country %in% c("Organisation for Economic Co-operation and Development", 
                        "Arab States", "East Asia and the Pacific", 
                        "Europe and Central Asia", "Latin America and the Caribbean", "World", "Sub-Saharan Africa", "South Asia")) |>
  pivot_longer(cols = starts_with("hdi"), 
               names_to = "year", 
               values_to = "hdi") |>
  mutate(year = gsub("hdi_", "", year),  # Remove "hdi_" prefix
         year = ymd(paste0(year, "-01-01")),  # Convert to date format
         country = ifelse(country == "Organisation for Economic Co-operation and Development", "OECD", country)) |>
  ggplot(aes(x = year, y = hdi, group = country, color = country)) +
  geom_line() +
  geom_point() +
  scale_x_date(date_labels = "%Y", date_breaks = "10 years") +  # Format x-axis as date and show every 10 years
  labs(title = "Trends in HDI by Region", y = "HDI", x = "Year", color = "Country") +  # Set legend title
  theme_minimal()

License

Data are available as CC-BY.

Citation

Please cite this package using:

citation("worldhdi")
#> To cite package 'worldhdi' in publications use:
#> 
#>   Dubey Y (2024). "worldhdi: Human Development Index Worldwide
#>   1990-2022." doi:10.5281/zenodo.14006110
#>   <https://doi.org/10.5281/zenodo.14006110>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Misc{dubey,
#>     title = {worldhdi: Human Development Index Worldwide 1990-2022},
#>     author = {Yash Dubey},
#>     doi = {10.5281/zenodo.14006110},
#>     abstract = {This package provides details about Human Development Index across the world from 1990 to 2022. 193 countries are included in the dataset. It also includes data aggregated by regions.},
#>     year = {2024},
#>     version = {0.1.0},
#>   }