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--- title: "Flex Dashboard" output: flexdashboard::flex_dashboard: orientation: rows --- ```{r setup, include=FALSE} library(plotly) library(maps) knitr::opts_chunk$set(message = FALSE) ``` Rows {data-height:600} ------------------------------------------------------------------------------ ### Chart A ```{r} # This example modifies code from Hadley Wickham -- https://gist.github.com/hadley/233134 # It also uses data from Nathan Yau's flowingdata site -- http://flowingdata.com/ unemp <- read.csv("http://datasets.flowingdata.com/unemployment09.csv") names(unemp) <- c("id", "state_fips", "county_fips", "name", "year", "?", "?", "?", "rate") unemp$county <- tolower(gsub(" County, [A-Z]{2}", "", unemp$name)) unemp$state <- gsub("^.*([A-Z]{2}).*$", "\\1", unemp$name) county_df <- map_data("county") names(county_df) <- c("long", "lat", "group", "order", "state_name", "county") county_df$state <- state.abb[match(county_df$state_name, tolower(state.name))] county_df$state_name <- NULL state_df <- map_data("state") choropleth <- merge(county_df, unemp, by = c("state", "county")) choropleth <- choropleth[order(choropleth$order), ] choropleth$rate_d <- cut(choropleth$rate, breaks = c(seq(0, 10, by = 2), 35)) # provide a custom tooltip to plotly with the county name and actual rate choropleth$text <- with(choropleth, paste0("County: ", name, "<br>Rate: ", rate)) p <- ggplot(choropleth, aes(long, lat, group = group)) + geom_polygon(aes(fill = rate_d, text = text), colour = alpha("white", 1/2), size = 0.2) + geom_polygon(data = state_df, colour = "white", fill = NA) + scale_fill_brewer(palette = "PuRd") + theme_void() # just show the text aesthetic in the tooltip ggplotly(p, tooltip = "text") ``` ### Chart B ```{r} crimes <- data.frame(state = tolower(rownames(USArrests)), USArrests) crimesm <- tidyr::gather(crimes, variable, value, -state) states_map <- map_data("state") g <- ggplot(crimesm, aes(map_id = state)) + geom_map(aes(fill = value), map = states_map) + expand_limits(x = states_map$long, y = states_map$lat) + facet_wrap( ~ variable) + theme_void() ggplotly(g) ``` Rows {data-height:400} ------------------------------------------------------------------------------ ### Chart C ```{r} m <- ggplot(faithful, aes(x = eruptions, y = waiting)) + stat_density_2d() + xlim(0.5, 6) + ylim(40, 110) ggplotly(m) ``` ### Chart D ```{r} m <- ggplot(faithful, aes(x = eruptions, y = waiting)) + stat_density_2d(aes(fill = ..level..), geom = "polygon") + xlim(0.5, 6) + ylim(40, 110) ggplotly(m) ``` ### Chart E ```{r} m <- ggplot(faithful, aes(x = eruptions, y = waiting)) + geom_hex() ggplotly(m) ```