knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) library(echarts4r) e_common( font_family = "Raleway" )
e_geo
family is similar to e_geo_3d
e_map
, e_map_3d
or e_globe
.
quakes |> e_charts(long) |> e_geo( roam = TRUE, boundingCoords = list( c(185, - 10), c(165, -40) ) ) |> e_scatter( lat, mag, coord_system = "geo" ) |> e_visual_map(mag, scale = e_scale)
flights <- read.csv( paste0("https://raw.githubusercontent.com/plotly/datasets/", "master/2011_february_aa_flight_paths.csv") ) flights |> e_charts() |> e_geo() |> e_lines( start_lon, start_lat, end_lon, end_lat, name = "flights", lineStyle = list(normal = list(curveness = 0.3)) )
quakes |> e_charts(long) |> e_geo( boundingCoords = list( c(190, -10), c(180, -40) ) ) |> e_heatmap( lat, mag, coord_system = "geo", blurSize = 5, pointSize = 3 ) |> e_visual_map(mag)
The companion package echarts4r.maps comes with 215 maps.
You can install the package with:
install.packages("remotes") remotes::install_github('JohnCoene/echarts4r.maps')
View the full list of maps with echarts4r.maps::em_bank()
.
library(echarts4r.maps) flights <- read.csv( paste0("https://raw.githubusercontent.com/plotly/datasets/", "master/2011_february_aa_flight_paths.csv") ) flights |> e_charts() |> em_map("USA") |> e_geo("USA") |> e_lines( start_lon, start_lat, end_lon, end_lat, name = "flights", lineStyle = list(normal = list(curveness = 0.3)) )
You can also use your own geoJSON with e_map_register
.
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