Untitled

library(rjson)

library(highcharter)

## Highcharts (www.highcharts.com) is a Highsoft software product which is

## not free for commercial and Governmental use

library(jsonlite)

## 
## Attaching package: 'jsonlite'

## The following objects are masked from 'package:rjson':
## 
##     fromJSON, toJSON

library(tigris)

## 
## Attaching package: 'tigris'

## The following object is masked from 'package:graphics':
## 
##     plot

library(ggplot2)
library(purrr)

## 
## Attaching package: 'purrr'

## The following object is masked from 'package:jsonlite':
## 
##     flatten

library(tidyr)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:purrr':
## 
##     contains, order_by

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(sp)
library(rgeos)

## rgeos version: 0.3-22, (SVN revision 544)
##  GEOS runtime version: 3.5.0-CAPI-1.9.0 r4084 
##  Linking to sp version: 1.2-4 
##  Polygon checking: TRUE

library(rgdal)

## rgdal: version: 1.2-5, (SVN revision 648)
##  Geospatial Data Abstraction Library extensions to R successfully loaded
##  Loaded GDAL runtime: GDAL 2.0.1, released 2015/09/15
##  Path to GDAL shared files: C:/Users/green/Documents/R/win-library/3.3/rgdal/gdal
##  Loaded PROJ.4 runtime: Rel. 4.9.2, 08 September 2015, [PJ_VERSION: 492]
##  Path to PROJ.4 shared files: C:/Users/green/Documents/R/win-library/3.3/rgdal/proj
##  Linking to sp version: 1.2-4

library(maptools)

## Checking rgeos availability: TRUE

library(ggthemes)
library(viridis)

URL <- "http://graphics8.nytimes.com/newsgraphics/2016/01/15/drug-deaths/c23ba79c9c9599a103a8d60e2329be1a9b7d6994/data.json"
fil <- "epidemic.json"
if (!file.exists(fil)) download.file(URL, fil)

data <- fromJSON("epidemic.json")

drugs <- gather(data, year, value, -fips)
drugs$year <- sub("^y", "", drugs$year)
drugs <- filter(drugs, year != "2012")

qcty <- quietly(counties)

us <- qcty(setdiff(state.abb, c("AK", "HI")), cb=TRUE)$result
us <- suppressWarnings(SpatialPolygonsDataFrame(gBuffer(gSimplify(us, 0.1, TRUE), byid=TRUE, width=0), us@data))

us_map <- fortify(us, region="GEOID")

gg <- ggplot()
gg <- gg + geom_map(data=us_map, map=us_map,
                    aes(x=long, y=lat, map_id=id),
                    color="#2b2b2b", size=0, fill=NA)

## Warning: Ignoring unknown aesthetics: x, y

gg <- gg + geom_map(data=drugs, map=us_map,
                    aes(fill=value, map_id=fips), 
                    color=NA, size=0)
gg <- gg + scale_fill_viridis(name="Overdose deaths per 100,000", 
                              option="magma")
gg <- gg + facet_wrap(~year, ncol=3)
gg <- gg + coord_map("polyconic")
gg <- gg + theme_map()
gg <- gg + theme(strip.background=element_blank())
gg <- gg + theme(strip.text=element_text(hjust=0))
gg <- gg + theme(legend.position="top")
gg

URL <- "http://graphics8.nytimes.com/newsgraphics/2016/01/15/drug-deaths/c23ba79c9c9599a103a8d60e2329be1a9b7d6994/data.json"

data("uscountygeojson")
data("unemployment")

data <-  fromJSON(URL) %>% 
  tbl_df() %>% 
  gather(year, value, -fips) %>% 
  mutate(year = sub("^y", "", year),
         value = ifelse(is.na(value), 0, value))

head(data)

## # A tibble: 6 × 3
##    fips  year value
##   <chr> <chr> <dbl>
## 1 01001  2002     1
## 2 01003  2002     2
## 3 01005  2002     0
## 4 01007  2002     1
## 5 01009  2002     2
## 6 01011  2002     0

ds <- data %>% 
  group_by(fips) %>% 
  do(item = list(
    fips = first(.$fips),
    sequence = .$value,
    value = first(.$value))) %>% 
  .$item

hc <- highchart(type = "map") %>% 
  hc_add_series(data = ds,
                name = "drug deaths per 100,000",
                mapData = uscountygeojson,
                joinBy = "fips",
                borderWidth = 0.01) %>% 
  hc_colorAxis(stops = color_stops()) %>%  
  hc_title(text = "How the Epidemic of Drug Overdose Deaths Ripples") %>% 
  hc_legend(layout = "vertical", reversed = TRUE,
            floating = TRUE, align = "right") %>% 
  hc_add_theme(hc_theme_smpl()) %>% 
  hc_motion(
    enabled = TRUE,
    axisLabel = "year",
    labels = sort(unique(data$year)),
    series = 0,
    updateIterval = 50,
    magnet = list(
      round = "floor",
      step = 0.1
    )
  )

hc