Problem in plotting a map graph using highcharter - r

Question

I am having troubles trying to write R code for a choroplet using the highcharter package. I am trying to replicate the code in the following link on lines 84-112: https://www.kaggle.com/gloriousc/global-terrorism-in-1970-2016/code.
I have been encountering 2 errors:
When running line 95, error says that there is no object called "countrycode_data". I looked on the internet in order to find out what countrycode_data is and I discovered that it is a dataset of the containing country code to associate to country names in datasets. Countrycode_data, from what I understood, it should have been contained in the "countrycode" package that I had installed but I didn't manage to find out how to access this dataset. In order to overcome this problem i downloaded this dataset from the internet and managed to go on with the code.
When running the choroplet code starting on line 103, I encountered the following error: "Error: %in%(x = tail(joinBy, 1), table = names(df)) is not TRUE". I actually have no idea about what this error could mean, so I'm here asking for help.
I managed to overcome the 1st error problem even though I am not sure that it is the correct way.
I am going to leave the entire code right here:
knitr::opts_chunk$set(echo=TRUE, error=FALSE)
library(dplyr) #manipulate table
library(ggplot2) #visualization
library(highcharter) #making map
library("viridisLite") #Default Color Maps
library(countrycode) #list of country code
library(treemap) #make a treemap chart
library(reshape2) #melt function
library(plotly) #pie chart
library(tm) #text mining
library(SnowballC) #stemming text
library(wordcloud) #make a text chart
library(RColorBrewer) #make a color pallette
library(DT) #make datatable
#input the data
terror <- read.csv("../input/globalterrorismdb_0617dist.csv")
Terrorist Incidents Map
#count terrorism incidents per country as a dataframe
countries <- terror %>%
group_by(country_txt) %>%
summarise(Total = round(n()))
#Making a terrorism map
#Credit to umeshnarayanappa
names(countries) <- c("country.name", "total") #change the column name
countries$iso3 <- countrycode_data[match(countries$country.name, countrycode_data$country.name.en), "iso3c"] #add iso3 column from country_code
data(worldgeojson, package = "highcharter")
dshmstops <- data.frame(q = c(0, exp(1:5)/exp(5)),
c = substring(viridis(5 + 1, option = "D"), 0, 7)) %>% #from viridisLite, make a color
list_parse2() #from highchart package, parse df to list
highchart() %>% #from highchart package
hc_add_series_map(worldgeojson, countries, value = "total", joinBy = "iso3") %>%
hc_colorAxis(stops = dshmstops) %>%
hc_legend(enabled = TRUE) %>%
hc_add_theme(hc_theme_db()) %>%
hc_mapNavigation(enabled = TRUE) %>%
hc_title(text = "Global Terrorism in 1970-2016", style = list(fontSize = "25px")) %>%
hc_add_theme(hc_theme_google()) %>%
hc_credits(enabled = TRUE, text = "Sources: National Consortium for the Study of Terrorism and Responses to Terrorism (START)", style = list(fontSize = "10px"))
I want to specify that, even though I ctrl+c ctrl+v the lines, they are not working for me.
Thank you for reading everything and also, I hope, for your help.

Answer 1

I tried to replicate the example. I hope the following is enough for you to work by yourself and replicate the example. It seems that countrycode_data is on the psData package. This package requires the rJava package, which is not on my machine now. As you were looking for a workaround, I found my own way; I scrape country data including iso3. (You can probably use the ISOcodes package too.) You need to check if country names in the two datasets are identical or not, which is a common challenge. You usually see some mismatches. I do not have time to correct all, but I showed you how to revise some country names in recode(). The bottom line is that you want to add iso3 to countries. So you need to make sure that you have identical country names as much as possible. (Obviously, some countries do not exist any more. You cannot really do anything about them.) The author used match() in his code, but I rather used left_join() to do the same. After this, I think you are ready to follow the rest of the code. Note that hc_add_series_map() is also doing a join process. worldgeojson has a property called iso3. countries must have a column called iso3. Otherwise, you will get the same error message again.
library(tidyverse)
library(data.table)
library(rvest)
library(highcharter)
library(viridisLite)
# I used fread(). This is much faster.
terror <- fread("globalterrorismdb_0919dist.csv")
# I wrote my own code which does the same job.
count(terror, country_txt) %>%
setNames(nm = c("country.name", "total")) -> countries
# Get iso3 data
map_dfc(.x = c("official", "shortname", "iso3"),
.f = function(x) {read_html("http://www.fao.org/countryprofiles/iso3list/en/") %>%
html_nodes(paste("td.", x, sep = "")) %>%
html_text() %>%
gsub(pattern = "\\n(\\s+)?", replacement = "")}) %>%
setNames(nm = c("official", "shortname", "iso3")) -> iso3
# Revise some country names.
mutate(iso3, shortname = trimws(sub(x = shortname, pattern = "\\(.*\\)",
replacement = "")),
shortname = recode(.x = shortname,
`Bosnia and Herzegovina` = "Bosnia-Herzegovina",
`Brunei Darussalam` = "Brunei",
Czechia = "Czech Republic",
Congo = "Republic of the Congo",
`Côte d'Ivoire` = "Ivory Coast",
`Russian Federation` = "Russia",
`United Kingdom of Great Britain and Northern Ireland` = "United Kingdom",
`United States of America`= "United States"
)) -> iso3
# Join the two data sets
left_join(countries, iso3, by = c("country.name" = "shortname")) -> countries
data(worldgeojson, package = "highcharter")
dshmstops <- data.frame(q = c(0, exp(1:5)/exp(5)),
c = substring(viridis(5 + 1, option = "D"), 0, 7)) %>% #from viridisLite, make a color
list_parse2()
highchart() %>% #from highchart package
hc_add_series_map(worldgeojson, df = countries,
value = "total", joinBy = "iso3") %>%
hc_colorAxis(stops = dshmstops) %>%
hc_legend(enabled = TRUE) %>%
hc_add_theme(hc_theme_db()) %>%
hc_mapNavigation(enabled = TRUE) %>%
hc_title(text = "Global Terrorism in 1970-2016", style = list(fontSize = "25px")) %>%
hc_add_theme(hc_theme_google()) %>%
hc_credits(enabled = TRUE,
text = "Sources: National Consortium for the Study of Terrorism and Responses to Terrorism (START)",
style = list(fontSize = "10px"))