Lesson5

WORLD MAP

Let’s use our libraries(tidyverse, countrycode) and read our dateset

require(tidyverse)

## Loading required package: tidyverse

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.2
## ✔ ggplot2   4.0.0     ✔ tibble    3.3.0
## ✔ lubridate 1.9.4     ✔ tidyr     1.3.1
## ✔ purrr     1.1.0     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

require(countrycode)

## Loading required package: countrycode

hr <- read.csv("../Datasets/hr_status_icerd.csv")
view(hr)

hr_gl <- hr%>% #nolint
    add_row(iso2="GL", member="GreenLand", state.party = 1, year.ratification.or.accession= 1971, signatory=0, no.action=0,status="state party") #nolint
hr = hr_gl #nolint
view(hr)

Now we start to create our map.

First step creating our dataframe

wmap <- map_data("world")
head(wmap)

##        long      lat group order region subregion
## 1 -69.89912 12.45200     1     1  Aruba      <NA>
## 2 -69.89571 12.42300     1     2  Aruba      <NA>
## 3 -69.94219 12.43853     1     3  Aruba      <NA>
## 4 -70.00415 12.50049     1     4  Aruba      <NA>
## 5 -70.06612 12.54697     1     5  Aruba      <NA>
## 6 -70.05088 12.59707     1     6  Aruba      <NA>

2nd step:

worldplot <- ggplot() +
  geom_polygon(data = wmap, aes(x = long, y = lat, group = group)) +
  coord_fixed(1.3)

worldplot

Congrats! you’ve created your map.