Loading libraries

To create the interactive map I used the following libraries. Note that the library fontawesome is installed using devtools from github.

#devtools::install_github("rstudio/fontawesome")
library(leaflet)
library(htmltools)
library(fontawesome)
library(htmlwidgets)

Creating the data frame.

I created a work data frame containing details of the latitude and longitude of locations where I’ve worked. I added a column link where I included html links to different parts of my website. The format is: "<b><a href='https://LINK.com'>Link Name</a></b>"

head(work)
##                    location
## 1         Valparaíso, Chile
## 2          Curitiba, Brasil
## 3 Sable Island, Nova Scotia
## 4       Greifswald, Germany
## 5          Arusha, Tanzania
## 6            Kigali, Rwanda
##                                                    institute
## 1                              Instituto de Fomento Pesquero
## 2                             Universidade Federal do Paraná
## 3                                       Dalhousie University
## 4                                Friedrich Loeffler Institut
## 5 Nelson Mandela African Institute of Science and Technology
## 6                    National Institute of Statistics Rwanda
##                    work      lat      lon
## 1 Chilean Pink Cusk Eel -33.0472 -71.6127
## 2            Fox rabies -25.4290 -49.2671
## 3            Grey seals  43.9337 -59.9149
## 4            Fox rabies  54.0865  13.3923
## 5              Teaching  -3.3995  36.7968
## 6              Teaching  -1.9415  30.0574
##                                                                                          link
## 1            <b><a href='http://lauriebaker.rbind.io/#projects'>Chilean Pink-cusk eel</a></b>
## 2 <b><a href='http://lauriebaker.rbind.io/project/internal-project/'>Outfoxing Rabies</a></b>
## 3          <b><a href='http://lauriebaker.rbind.io/#projects'>Grey Seals as Bioprobes</a></b>
## 4 <b><a href='http://lauriebaker.rbind.io/project/internal-project/'>Outfoxing Rabies</a></b>
## 5                        <b><a href='http://lauriebaker.rbind.io/courses/'>R Training</a></b>
## 6                        <b><a href='http://lauriebaker.rbind.io/courses/'>R Training</a></b>
##       icon
## 1     fish
## 2  disease
## 3      gps
## 4  disease
## 5 training
## 6 training

Creating the labels

Next, I created the labels and icons to use on the map. I wanted to include a label including the institute where the work was carried out and also a link to the relevant page on my website. To do this I used the function sprintf() and pointed to the relevant columns in my data institute, link.

There is some additional styling added using <strong> for bold and <br/> to create a break so the the Project information is on the next line.

labels <- sprintf(
  "<strong>%s</strong><br/>Project: %s",
  work$institute, work$link
) %>% lapply(htmltools::HTML)

Creating the icons using awesomeIconList

I wanted to distinguish the different types of projects on the map (using symbols for my projects relating to dish, fish , and gps satellite tracking) and also I wanted to highlight the R training sessions I’ve run. I used different icons from the fontawesome package and used the argument markerColor to distinguish between training sessions and projects.

If you prefer to use the standard marker color you can skip the argument for markerColor as shown for iconset1.

iconset1 <- awesomeIconList(
   fish = makeAwesomeIcon(text = fa("fish")),
   gps = makeAwesomeIcon(text = fa("satellite")),
   disease = makeAwesomeIcon(text = fa("syringe")),
   training = makeAwesomeIcon(text = fa("r-project"))
)

iconset2 <- awesomeIconList(
   fish = makeAwesomeIcon(text = fa("fish"), markerColor = "green"),
   gps = makeAwesomeIcon(text = fa("satellite"), markerColor = "green"),
   disease = makeAwesomeIcon(text = fa("syringe"), markerColor = "green"),
   training = makeAwesomeIcon(text = fa("r-project"), markerColor = "purple")
)

Creating the leaflet map

For the leaflet map I first specified my dataset leaflet(work) and then added the Stamen.Watercolor and Stame.TerrainLabels provider tiles using addProvideTiles.

To explore the different options available you can type providers$ + TAB and scroll through the different layers. The next layer to be added is the markers using addAwesomeMarkers their location is set by the lon and lat columns of the dataset work.

The correct icon is added by specifying the column icon within iconset2[icon]. These match the icons defined so that when the icon is “fish” this is effectively iconset2["fish"] the marker defined as fish is used.

Lastly I specify the popup as my predefined labels, which take the institute and link specified in my dataset.

(work_map <- leaflet(work) %>% 
              addProviderTiles(providers$OpenStreetMap) %>%
              addAwesomeMarkers(~lon, ~lat, icon = ~iconset2[icon], popup = ~labels))

widget_path <- file.path("../../../static/leaflet")

dir.create(widget_path)

saveWidget(work_map, file.path(widget_path,"work_map.html"))