Get Started

Your first map

# Fake data
st <- c("AR", "NY", "CA", "IL", "CO", "MT", "TX", "OK", "AL", "NM", "NV", "NC", "OH", "PA")
states <- data.frame(from = st, to = sample(st, 14))

states %>%
    datamaps(scope = "usa", height = "400", width = "100%") %>% # intiate map
    add_arcs_name(from, to) %>% # add arcs layers 
    add_labels() # add state labels

Examples

data.frame(
  state = state.abb,
  area = state.area
) %>% 
  datamaps(scope = "usa", height = "400", width = "100%") %>%
  add_choropleth(state, area)

Combine types.

library(datamaps)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

sesh <- read.csv("https://raw.githubusercontent.com/JohnCoene/projects/master/htmlwidgets/echarts/data/sessions.csv")

# datamaps uses iso3c format
sesh$iso3c <- countrycode::countrycode(sesh$Country, "country.name", "iso3c")
#> Warning in countrycode::countrycode(sesh$Country, "country.name", "iso3c"): Some values were not matched unambiguously: , (not set)
sesh <- sesh[!is.na(sesh$iso3c),] # remove NA
sesh$continent <- countrycode::countrycode(sesh$iso3c, "iso3c", "continent") # find continents

# sum Sessions by continent
continents <- sesh %>% 
  group_by(continent) %>% 
  summarise(Sessions = sum(Sessions)) %>% 
  mutate(long = c(3.917313, -99.133209, 106.660172, 16.363449),
         lat = c(7.401962, 19.432608, 10.762622, 48.210033))

sesh %>% 
  datamaps(default = "lightgray", height = "400", width = "100%") %>% # initiate map
  add_choropleth(iso3c, Sessions, colors = RColorBrewer::brewer.pal(5, "YlOrRd")) %>% # add chorpleth layer
  add_data(continents) %>% # add continent dataset
  add_bubbles(long, lat, log(Sessions) * 5, continent, continent, colors = RColorBrewer::brewer.pal(4, "Set1")) # add continent bubbles

Set different projections and add graticule.

data <- data.frame(name = c("USA", "CAN", "BRA", "ARG", "MEX", "CUB", "BOL"),
                   color = round(runif(7, 1, 10)))

data %>%
  datamaps(projection = "orthographic", height = "400", width = "100%") %>%
  add_choropleth(name, color, colors = c("skyblue", "yellow", "orangered")) %>% 
  add_graticule() 

All of it (nearly).

coords <- data.frame(city = c("London", "New York", "Beijing", "Sydney"),
                     lon = c(-0.1167218, -73.98002, 116.3883, 151.18518),
                     lat = c(51.49999, 40.74998, 39.92889, -33.92001),
                     values = c(11, 23, 29 , 42))

data <- data.frame(name = c("USA", "FRA", "CHN", "RUS", "COG", "DZA",
                            "BRA", "AFG"),
    color = round(runif(8, 1, 10)))

edges <- data.frame(origin = c("USA", "FRA", "BGD", "ETH", "KHM", "GRD",
                               "FJI", "GNB", "AUT", "YEM"),
    target = c("BRA", "USA", "URY", "ZAF", "SAU", "SVK", "RWA", "SWE",
               "TUV", "ZWE"),
    strokeColor = rep(c("gray", "black"), 5))

data %>%
    datamaps(default = "lightgray", height = "400", width = "100%") %>%
    add_choropleth(name, color) %>%
    add_data(coords) %>%
    add_bubbles(lon, lat, values, values, city, colors = c("skyblue", "darkblue")) %>%
    add_data(edges) %>%
    add_arcs_name(origin, target, strokeColor)

Custom map

topo <- paste0(
  "https://rawgit.com/Anujarya300/bubble_maps/",
  "master/data/geography-data/india.topo.json"
)

data <- data.frame(state = c("JH", "MH"), value = c(55, 28))
  
data %>% 
  datamaps(scope = "india", height = "600", width = "100%") %>% 
  add_choropleth(state, value) %>% 
  config_geo(data.url = topo) %>% 
  set_projection(htmlwidgets::JS('
  function (element) {
    var projection = d3.geo.mercator()
    .center([78.9629, 23.5937])
    .scale(1000);
    var path = d3.geo.path().projection(projection);
    return { path: path, projection: projection };
  }
  ')
  )

Plugins

SVG icons

coords <- data.frame(
  city = c("London", "New York", "Beijing", "Sydney"),
  lon = c(-0.1167218, -73.98002, 116.3883, 151.18518),
  lat = c(51.49999, 40.74998, 39.92889, -33.92001)
)

coords %>% 
  datamaps() %>% 
  add_icons(lon, lat)

Custom markers

icon_url <- paste0(
  "https://pbs.twimg.com/profile_images/",
  "927645314630193158/ufoYTbbi_400x400.jpg"
)

coords %>% 
  datamaps() %>% 
  markers_options(
    icon = list(
      url = icon_url,
      width = 20, height = 20
     ),
     fillOpacity = 1
  ) %>% 
  add_markers(lon, lat)