Visited Countries in R: A Global Map Adventure

Visited Countries in R: A Global Map Adventure

Introduction:

If you enjoy traveling and using R, you may be interested in creating a world map to mark the countries you have visited. This article provides step-by-step instructions on how to achieve this using R and the highcharter, dplyr, and maps packages. The process involves loading the necessary packages, accessing the iso3166 dataset, defining the countries you have visited, and creating the map. The article also includes additional code to generate an alphabetical list of visited countries and count the total number of countries visited. Follow along with the provided R code to customize the map according to your preferences. We hope this article helps you create a visually appealing world map showcasing your travel adventures using R. If you have any questions or suggestions, please feel free to leave a comment for further discussion.

Full Article: Visited Countries in R: A Global Map Adventure

How to Draw a World Map of Visited Countries in R

If you are an avid traveler and you use R, you might be interested in drawing a world map of the countries you have visited. This article will guide you through the process of creating a world map with your visited countries highlighted using the R programming language.

Required Packages:

Before we begin, make sure you have the following packages installed on your machine:

– highcharter
– dplyr
– maps

These packages can be installed using the command:
“`
install.packages(“package_name”)
“`
where “package_name” is the name of the package.

Preparing the Dataset:

To start, we will use the dataset called “iso3166” from the “maps” package. Rename the variable “a3” to “iso-a3”. This dataset contains information about countries and their ISO codes.

After renaming the variable, save the dataset as “dat”. The first six rows of the dataset should now look like this:

“`
a2 iso-a3 ISOname mapname sovereignty
1 AW ABW Aruba Aruba Netherlands
2 AF AFG Afghanistan Afghanistan
3 AO AGO Angola Angola Angola
4 AI AIA Anguilla Anguilla Anguilla
5 AX ALA Aland Islands Finland:Aland Islands Finland
6 AL ALB Albania Albania Albania
“`

Creating a Vector of Visited Countries:

Next, we will create a vector called “countries_visited” that contains the ISO codes of the countries you have visited. This vector should be in the same format as the “iso-a3” column in the dataset.

For example:

“`
countries_visited <- c("AUS", "BEL", "CAN", "CZE", "DNK", "FIN", "FRA", "DEU", "GRC", "HUN", "IRL", "ITA", "LVA", "LUX", "MCO", "MMR", "NLD", "NZL", "NOR", "PRT", "ROU", "SGP", "ESP", "SWE", "CHE", "TWN", "THA", "GBR", "USA") ``` Adding a "visited" Column to the Dataset: Now, we will create a new variable called "visited" in the dataset. This variable will be set to 1 if the country is in the list of visited countries and 0 otherwise. ``` dat$visited <- ifelse(dat$`iso-a3` %in% countries_visited, 1, 0) ``` Drawing the World Map: Finally, we are ready to draw the world map using the "hcmap()" command from the "highcharter" package. The following code will draw the map with the visited countries highlighted: ``` hcmap( map = "custom/world-highres3", data = dat, joinBy = "iso-a3", value = "visited", showInLegend = FALSE, nullColor = "#DADADA", download_map_data = TRUE ) %>%
hc_mapNavigation(enabled = FALSE) %>%
hc_legend(“none”) %>%
hc_title(text = “World Map”)
“`

This code specifies the high-resolution world map, the dataset to use, the column to join the dataset with, the values to use for coloring, and other visual settings. Customize the arguments to fit your needs.

Displaying the Visited Countries List:

To display a list of all the visited countries in alphabetical order, you can use the following code:

“`
visited_countries <- subset(dat, dat$visited == 1) sort(visited_countries$ISOname) ``` Counting the Number of Visited Countries: To count the number of countries you have visited, you can use the following code: ``` paste("Total:", sum(dat$visited), "countries.") ``` This will display the total number of visited countries. Conclusion: In conclusion, this article has provided a step-by-step guide on how to draw a world map with your visited countries highlighted in R. By following the instructions and customizing the code, you can create a personalized world map that showcases the countries you have explored. Happy traveling and mapping!

Thank you for reading. If you have any questions or suggestions related to this topic, please leave a comment so that others can benefit from the discussion.

Summary: Visited Countries in R: A Global Map Adventure

In this article, we will learn how to draw a world map of the countries we have visited using R programming language. We will be using the “highcharter”, “dplyr”, and “maps” packages. After loading the required packages, we will use the “iso3166” dataset from the “maps” package to get the ISO codes of the countries. We will save the visited countries in a vector and create a new variable “visited” to represent whether a country has been visited or not. Finally, we will use the “hcmap()” command from “highcharter” package to draw the world map with the visited countries highlighted. In conclusion, this article provides a step-by-step guide to visualize the countries visited on a world map using R.

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