library(apexcharter) library(dplyr) # Bar --------------------------------------------------------------------- data("mpg", package = "ggplot2") count(mpg, class) %>% mutate(pct = n/sum(n)) %>% apex(mapping = aes(class, pct), type = "column") %>% ax_colors("#617a89")%>% ax_yaxis( title = list(text = "Weight (tons)"), labels = list( formatter = JS( "function(value) {return Math.round(value * 100) + '%';}" ) ), tickAmount = 6 ) %>% ax_xaxis( title = list(text = "Fuel efficiency (mpg)") ) %>% ax_tooltip( y = list( title = list( formatter = JS("function() {return 'Percentage';}") ) ) ) %>% ax_labs( title = "Seminal ggplot2 column chart example with percents", subtitle = "Example taken from {hrbrthemes} readme" ) %>% ax_title( style = list(fontSize = "22px") ) %>% ax_subtitle( style = list(fontSize = "16px", color = "#BDBDBD") ) # Line -------------------------------------------------------------------- data("unhcr_ts") unhcr_ts %>% filter(population_type == "Refugees (incl. refugee-like situations)") %>% mutate(date = as.Date(paste0(year, "-01-01"))) %>% apex(aes(date, n, group = continent_origin), type = "line") %>% ax_legend(position = "bottom") %>% ax_stroke(width = 2) %>% ax_colors("#440154", "#414487", "#2A788E", "#22A884", "#7AD151", "#FDE725") %>% ax_yaxis( labels = list( formatter = JS("function(val) {return (val/1e6).toFixed(0);}") ), title = list(text = "Number of refugees (in million)") ) %>% ax_xaxis(labels = list(format = "yyyy")) %>% ax_tooltip( x = list(format = "yyyy"), y = list( formatter = JS( # thousand separator in javascript "function(value) {return value.toString().replace(/\\B(?=(\\d{3})+(?!\\d))/g, \",\");}" ) ) ) %>% ax_annotations( points = list( list( x = JS("new Date('1994').getTime()"), y = 6935296, label = list(text = "Great Lakes refugee crisis", offsetY = 0), marker = list(size = 6) ) ) ) %>% ax_labs( title = "Continent of origin for refugees population", subtitle = "Data from the UN Refugee Agency" ) %>% ax_title( style = list(fontSize = "22px") ) %>% ax_subtitle( style = list(fontSize = "16px", color = "#BDBDBD") ) # Scatter ----------------------------------------------------------------- data("gapminder", package = "gapminder") gapminder %>% filter(year == 2007) %>% mutate( gdpPercap = log(gdpPercap), pop = sqrt(pop / pi) / 1500 ) %>% apex(mapping = aes(gdpPercap, lifeExp, z = pop, group = continent, label = country), type = "scatter") %>% ax_chart(zoom = list( enabled = TRUE, type = "xy" )) %>% ax_yaxis( decimalsInFloat = 0, axisBorder = list(show = TRUE), axisTicks = list(show = TRUE), title = list(text = "life expectancy at birth (in years)") ) %>% ax_xaxis( tickAmount = 8, labels = list( formatter = JS("function(val) {return val.toFixed(2);}") ), tooltip = list(enabled = FALSE), title = list(text = "GDP per capita (log-scale)") ) %>% ax_grid(xaxis = list(lines = list(show = TRUE))) %>% ax_legend(position = "right", offsetY = 70) %>% ax_markers(hover = list(sizeOffset = 0, size = 25)) %>% ax_tooltip(custom = JS(paste( "function({ series, seriesIndex, dataPointIndex, w }) {", "console.log(w); return (", "'
' +", "'
' +", "w.config.series[seriesIndex].data[dataPointIndex].label", "+ '
' +", "'
' +", "'
' +", "'' +", "'Population: ' +", "'' +", "'' +", "Math.round(Math.pow(w.config.series[seriesIndex].data[dataPointIndex].z * 1500, 2) * Math.PI). toString().replace(/\\B(?=(\\d{3})+(?!\\d))/g, \",\") +", "'' +", "'
' +", "'' +", "'GDP per capita: ' +", "'' +", "'' +", "Math.round(Math.exp(w.config.series[seriesIndex].data[dataPointIndex].x)) +", "'' +", "'
' +", "'' +", "'Life expectancy: ' +", "'' +", "'' +", "w.config.series[seriesIndex].data[dataPointIndex].y +", "'' +", "'
' +", "'
' +", "'
'", ");", "}", sep = "\n" ))) %>% ax_labs( title = "Life expectancy, GDP and population", subtitle = "gapminder dataset from {gapminder}" ) %>% ax_title( style = list(fontSize = "22px") ) %>% ax_subtitle( style = list(fontSize = "16px", color = "#BDBDBD") ) # Heatmap ----------------------------------------------------------------- data("vaccines", package = "highcharter") apex(vaccines, aes(year, state, fill = count), type = "heatmap") %>% ax_chart(animations = list(enabled = FALSE)) %>% ax_dataLabels(enabled = FALSE) %>% ax_stroke(width = 0) %>% ax_plotOptions( heatmap = heatmap_opts( radius = 0, enableShades = FALSE, colorScale = list( ranges = list( list( from = 0, to = 0.001, name = "Missing", color = "#FFF" ), list( from = 0.001, to = 4, name = "low", # color = "#000004" color = "#FDE725" ), list( from = 4, to = 70, name = "mid-low", # color = "#781C6D", color = "#35B779" ), list( from = 70, to = 290, name = "mid-high", # color = "#ED6925", color = "#31688E" ), list( from = 290, to = 3000, name = "high", # color = "#FCFFA4", color = "#440154" ) ) ) ) ) %>% ax_legend( formatter = JS( "function(seriesName, opts) { if (seriesName == 'Missing') return null; else return seriesName; }" ) ) %>% ax_yaxis( labels = list( style = list(fontSize = "8px"), offsetY = -20 ) ) %>% ax_annotations( xaxis = list( list( x = 1963, x2 = 1963.1, strokeDashArray = 0, opacity = 1, borderColor = "firebrick", fillColor = "firebrick", label = list( borderColor = "firebrick", style = list(color = "#FFF", background = "firebrick"), text = "Vaccine Intoduced", orientation = "horizontal", position = "bottom", offsetY = 10 ) ) ) ) %>% ax_labs( title = "Infectious Diseases and Vaccines", subtitle = "vaccines dataset from {highcharter}" ) %>% ax_title( style = list(fontSize = "22px") ) %>% ax_subtitle( style = list(fontSize = "16px", color = "#BDBDBD") )