Visualizing the dental workforce of OECD countries I

The Organisation for Economic Co-operation and Development host a database with extensive data. In this post we will do some visualizations to compare the number of dentists in each country. Packages used: tidyverse gghighlight kableExtra First we load the data. Now there is a package (OECD) able to extract the datasets, but I will use a local copy: dent_oecd <- read_csv("https://docs.google.com/spreadsheets/d/e/2PACX-1vStv7Pr69DtRKv6Nw6gVBep8hbT3pEeO6B1vNwxK_1DUHgpoTgbuRpZ4SvgtHFQnBZJVGeeQVyRuXZl/pub?gid=1330297229&single=true&output=csv") ## Parsed with column specification: ## cols( ## VAR = col_character(), ## Variable = col_character(), ## UNIT = col_character(), ## Measure = col_character(), ## COU = col_character(), ## Country = col_character(), ## YEA = col_integer(), ## Year = col_integer(), ## Value = col_double(), ## `Flag Codes` = col_character(), ## Flags = col_character() ## ) Always is preferable to take a look the data and its structure: [Read More]