{"id":3413,"date":"2015-05-15T07:18:28","date_gmt":"2015-05-15T12:18:28","guid":{"rendered":"http:\/\/rud.is\/b\/?p=3413"},"modified":"2018-07-09T06:55:08","modified_gmt":"2018-07-09T11:55:08","slug":"u-s-drought-monitoring-with-hexbin-state-maps-in-r","status":"publish","type":"post","link":"https:\/\/rud.is\/b\/2015\/05\/15\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\/","title":{"rendered":"U.S. Drought Monitoring With Hexbin State Maps in R"},"content":{"rendered":"<p>On the news, today, of the <a href=\"\">early stages of drought hitting the U.S. northeast states<\/a> I decided to springboard off of <a href=\"https:\/\/rud.is\/b\/2015\/05\/14\/geojson-hexagonal-statebins-in-r\/\">yesterday&#8217;s post<\/a> and show a more practical use of hexbin state maps than the built-in (and still purpose unknown to me) &#8220;bees&#8221; data.<\/p>\n<p>The <a href=\"http:\/\/droughtmonitor.unl.edu\/MapsAndData\/GISData.aspx\">U.S. Drought Monitor site<\/a> supplies more than just a pretty county-level map. There&#8217;s plenty of <a href=\"http:\/\/droughtmonitor.unl.edu\/MapsAndData\/GISData.aspx\">data<\/a> and you can dynamically retrieve just data tables for the whole U.S., U.S. states and U.S. counties. Since we&#8217;re working with state hexbins, we just need the state-level data. Drought levels for all five stages are reported per-state, so we can take all this data and created a faceted\/small-multiples map based on it.<\/p>\n<p>This builds quite a bit on the previous work, so you&#8217;ll see some familiar code. Most of the new code is actually making the map look nice (the great part about this is that once you have the idiom down, it&#8217;s just a matter of running the script each day vs a billion mouse clicks). The other bit of new code is the data-retrieval component:<\/p>\n<pre><code class=\"language-r\">library(readr)\nlibrary(tidyr)\nlibrary(dplyr)\n\nintensity <- c(D0=\"Abnormally Dry\", D1=\"Moderate Drought\", D2=\"Severe Drought\", \n               D3=\"Extreme Drought\", D4=\"Exceptional Drought\")\n\ntoday <- format(Sys.Date(), \"%Y%m%d\")\n\nread_csv(sprintf(\"http:\/\/droughtmonitor.unl.edu\/USDMStatistics.ashx\/?mode=table&#038;aoi=state&#038;date=%s\", today)) %>% \n  gather(drought_level, value, D0, D1, D2, D3, D4) %>% \n  mutate(intensity=factor(intensity[drought_level], \n                          levels=as.character(intensity), ordered=TRUE)) -> drought<\/code><\/pre>\n<p>This:<\/p>\n<ul>\n<li>sets up a fast way to add the prettier description of the drought levels (besides D0, D1, etc)<\/li>\n<li>dynamically uses today&#8217;s date as the parameter for the URL we read with <code>read_csv<\/code> (from the <code>readr<\/code> package)<\/li>\n<li>covert the data from wide to long<\/li>\n<li>adds the intensity description<\/li>\n<\/ul>\n<p>The <code>ggplot<\/code> code will facet on the intensity level to make the overall map:<\/p>\n<pre><code class=\"language-r\">library(rgdal)\nlibrary(rgeos)\nlibrary(ggplot2)\nlibrary(readr)\nlibrary(tidyr)\nlibrary(dplyr)\nlibrary(grid)\n\n# get map from https:\/\/gist.github.com\/hrbrmstr\/51f961198f65509ad863#file-us_states_hexgrid-geojson\n\nus <- readOGR(\"us_states_hexgrid.geojson\", \"OGRGeoJSON\")\n\ncenters <- cbind.data.frame(data.frame(gCentroid(us, byid=TRUE), id=us@data$iso3166_2))\n\nus_map <- fortify(us, region=\"iso3166_2\")\n\nintensity <- c(D0=\"Abnormally Dry\", D1=\"Moderate Drought\", D2=\"Severe Drought\",\n               D3=\"Extreme Drought\", D4=\"Exceptional Drought\")\n\ntoday <- format(Sys.Date(), \"%Y%m%d\")\n\nread_csv(sprintf(\"http:\/\/droughtmonitor.unl.edu\/USDMStatistics.ashx\/?mode=table&#038;aoi=state&#038;date=%s\", today)) %>%\n  gather(drought_level, value, D0, D1, D2, D3, D4) %>%\n  mutate(intensity=factor(intensity[drought_level],\n                          levels=as.character(intensity), ordered=TRUE)) -> drought\n\ngg <- ggplot()\ngg <- gg + geom_map(data=us_map, map=us_map,\n                    aes(x=long, y=lat, map_id=id),\n                    color=\"white\", size=0.5)\ngg <- gg + geom_map(data=drought, map=us_map,\n                    aes(fill=value, map_id=State))\ngg <- gg + geom_map(data=drought, map=us_map,\n                    aes(map_id=State),\n                    fill=\"#ffffff\", alpha=0, color=\"white\",\n                    show_guide=FALSE)\ngg <- gg + geom_text(data=centers, aes(label=id, x=x, y=y), color=\"white\", size=4)\ngg <- gg + scale_fill_distiller(name=\"State\\nDrought\\nCoverage\", palette=\"RdPu\", na.value=\"#7f7f7f\",\n                                labels=sprintf(\"%d%%\", c(0, 25, 50, 75, 100)))\ngg <- gg + coord_map()\ngg <- gg + facet_wrap(~intensity, ncol=2)\ngg <- gg + labs(x=NULL, y=NULL, title=sprintf(\"U.S. Drought Conditions as of %s\\n\", Sys.Date()))\ngg <- gg + theme_bw()\ngg <- gg + theme(plot.title=element_text(face=\"bold\", hjust=0, size=24))\ngg <- gg + theme(panel.border=element_blank())\ngg <- gg + theme(panel.margin=unit(3, \"lines\"))\ngg <- gg + theme(panel.grid=element_blank())\ngg <- gg + theme(axis.ticks=element_blank())\ngg <- gg + theme(axis.text=element_blank())\ngg <- gg + theme(strip.background=element_blank())\ngg <- gg + theme(strip.text=element_text(face=\"bold\", hjust=0, size=14))\ngg <- gg + theme(legend.position=c(0.75, 0.15))\ngg <- gg + theme(legend.direction=\"horizontal\")\ngg <- gg + theme(legend.title.align=1)\n\npng(sprintf(\"%s.png\", today), width=800, height=800)\nprint(gg)\ndev.off()<\/code><\/pre>\n<p><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" data-attachment-id=\"3416\" data-permalink=\"https:\/\/rud.is\/b\/2015\/05\/15\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\/20150515-2\/\" data-orig-file=\"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2015\/05\/201505151.png?fit=800%2C800&amp;ssl=1\" data-orig-size=\"800,800\" data-comments-opened=\"1\" data-image-meta=\"{&quot;aperture&quot;:&quot;0&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;0&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;0&quot;,&quot;iso&quot;:&quot;0&quot;,&quot;shutter_speed&quot;:&quot;0&quot;,&quot;title&quot;:&quot;&quot;,&quot;orientation&quot;:&quot;0&quot;}\" data-image-title=\"20150515\" data-image-description=\"\" data-image-caption=\"\" data-large-file=\"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2015\/05\/201505151.png?fit=510%2C510&amp;ssl=1\" src=\"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2015\/05\/201505151.png?resize=510%2C510&#038;ssl=1\" alt=\"20150515\" width=\"510\" height=\"510\" class=\"aligncenter size-full wp-image-3416\" \/><\/p>\n<p>Now, you can easily animate these over time to show the progression\/regression of the drought conditions. If you're sure your audience can work with SVG files, you can use those for very crisp\/sharp maps (and even feed it to D3 or path editing tools). If you have an example of how you're using hexbin choropleths, drop a note in the comments. The code from above is also <a href=\"https:\/\/gist.github.com\/hrbrmstr\/51f961198f65509ad863\">on github<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>On the news, today, of the early stages of drought hitting the U.S. northeast states I decided to springboard off of yesterday&#8217;s post and show a more practical use of hexbin state maps than the built-in (and still purpose unknown to me) &#8220;bees&#8221; data. The U.S. Drought Monitor site supplies more than just a pretty [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"activitypub_content_warning":"","activitypub_content_visibility":"","activitypub_max_image_attachments":3,"activitypub_interaction_policy_quote":"anyone","activitypub_status":"","footnotes":""},"categories":[721,678,673,674,706,91],"tags":[810],"class_list":["post-3413","post","type-post","status-publish","format-standard","hentry","category-cartography","category-data-visualization","category-datavis-2","category-dataviz","category-maps","category-r","tag-post"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>U.S. Drought Monitoring With Hexbin State Maps in R - rud.is<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/rud.is\/b\/2015\/05\/15\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"U.S. Drought Monitoring With Hexbin State Maps in R - rud.is\" \/>\n<meta property=\"og:description\" content=\"On the news, today, of the early stages of drought hitting the U.S. northeast states I decided to springboard off of yesterday&#8217;s post and show a more practical use of hexbin state maps than the built-in (and still purpose unknown to me) &#8220;bees&#8221; data. The U.S. Drought Monitor site supplies more than just a pretty [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/rud.is\/b\/2015\/05\/15\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\/\" \/>\n<meta property=\"og:site_name\" content=\"rud.is\" \/>\n<meta property=\"article:published_time\" content=\"2015-05-15T12:18:28+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2018-07-09T11:55:08+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/rud.is\/b\/wp-content\/uploads\/2015\/05\/201505151.png\" \/>\n<meta name=\"author\" content=\"hrbrmstr\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"hrbrmstr\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/rud.is\\\/b\\\/2015\\\/05\\\/15\\\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/rud.is\\\/b\\\/2015\\\/05\\\/15\\\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\\\/\"},\"author\":{\"name\":\"hrbrmstr\",\"@id\":\"https:\\\/\\\/rud.is\\\/b\\\/#\\\/schema\\\/person\\\/d7cb7487ab0527447f7fda5c423ff886\"},\"headline\":\"U.S. Drought Monitoring With Hexbin State Maps in R\",\"datePublished\":\"2015-05-15T12:18:28+00:00\",\"dateModified\":\"2018-07-09T11:55:08+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/rud.is\\\/b\\\/2015\\\/05\\\/15\\\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\\\/\"},\"wordCount\":333,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\\\/\\\/rud.is\\\/b\\\/#\\\/schema\\\/person\\\/d7cb7487ab0527447f7fda5c423ff886\"},\"image\":{\"@id\":\"https:\\\/\\\/rud.is\\\/b\\\/2015\\\/05\\\/15\\\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/rud.is\\\/b\\\/wp-content\\\/uploads\\\/2015\\\/05\\\/201505151.png\",\"keywords\":[\"post\"],\"articleSection\":[\"cartography\",\"Data Visualization\",\"DataVis\",\"DataViz\",\"maps\",\"R\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\\\/\\\/rud.is\\\/b\\\/2015\\\/05\\\/15\\\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\\\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/rud.is\\\/b\\\/2015\\\/05\\\/15\\\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\\\/\",\"url\":\"https:\\\/\\\/rud.is\\\/b\\\/2015\\\/05\\\/15\\\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\\\/\",\"name\":\"U.S. Drought Monitoring With Hexbin State Maps in R - rud.is\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/rud.is\\\/b\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/rud.is\\\/b\\\/2015\\\/05\\\/15\\\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/rud.is\\\/b\\\/2015\\\/05\\\/15\\\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/rud.is\\\/b\\\/wp-content\\\/uploads\\\/2015\\\/05\\\/201505151.png\",\"datePublished\":\"2015-05-15T12:18:28+00:00\",\"dateModified\":\"2018-07-09T11:55:08+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/rud.is\\\/b\\\/2015\\\/05\\\/15\\\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/rud.is\\\/b\\\/2015\\\/05\\\/15\\\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/rud.is\\\/b\\\/2015\\\/05\\\/15\\\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\\\/#primaryimage\",\"url\":\"https:\\\/\\\/i0.wp.com\\\/rud.is\\\/b\\\/wp-content\\\/uploads\\\/2015\\\/05\\\/201505151.png?fit=800%2C800&ssl=1\",\"contentUrl\":\"https:\\\/\\\/i0.wp.com\\\/rud.is\\\/b\\\/wp-content\\\/uploads\\\/2015\\\/05\\\/201505151.png?fit=800%2C800&ssl=1\",\"width\":800,\"height\":800},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/rud.is\\\/b\\\/2015\\\/05\\\/15\\\/u-s-drought-monitoring-with-hexbin-state-maps-in-r\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/rud.is\\\/b\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"U.S. Drought Monitoring With Hexbin State Maps in R\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/rud.is\\\/b\\\/#website\",\"url\":\"https:\\\/\\\/rud.is\\\/b\\\/\",\"name\":\"rud.is\",\"description\":\"&quot;In God we trust. 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