{"id":3141,"date":"2014-11-27T10:17:49","date_gmt":"2014-11-27T15:17:49","guid":{"rendered":"http:\/\/rud.is\/b\/?p=3141"},"modified":"2018-03-07T16:44:05","modified_gmt":"2018-03-07T21:44:05","slug":"power-outage-impact-choropleths-in-5-steps-in-r-featuring-rvest-rstudio-projects","status":"publish","type":"post","link":"https:\/\/rud.is\/b\/2014\/11\/27\/power-outage-impact-choropleths-in-5-steps-in-r-featuring-rvest-rstudio-projects\/","title":{"rendered":"Power Outage Impact Choropleths In 5 Steps in R (featuring rvest & RStudio “Projects”)"},"content":{"rendered":"

I and @awpiii were trading news about the power outages in Maine & New Hampshire last night and he tweeted the link to the @PSNH [Outage Map](http:\/\/www.psnh.com\/outage\/). As if the Bing Maps tiles weren’t bad enough, the use of a categorical color scale instead of a sequential one[[1](http:\/\/earthobservatory.nasa.gov\/blogs\/elegantfigures\/2011\/05\/20\/qualitative-vs-sequential-color-scales\/)]<\/sup> caused sufficient angst that I whipped up an alternate version in R between making pies and bread for Thanksgiving (even with power being out for us).<\/p>\n

PSNH provides a text version<\/a> of outages (by town) that ends up being a pretty clean HTML table, and a quick Google search led me to a fairly efficient town-level [shapefile](http:\/\/www.mass.gov\/anf\/research-and-tech\/it-serv-and-support\/application-serv\/office-of-geographic-information-massgis\/datalayers\/adjacent-states-town-boundaries.html) for New Hampshire. With these data files at the ready, it was time to make a better map.<\/p>\n

**Step 0 – Environment Setup**<\/p>\n

So, I lied. There are six steps. “5” just works way better in attention-grabbing list headlines. The first one is setting up the project and loading all the libraries we’ll need. I use RStudio for most of my R coding and their IDE has the concept of a “project” which has it’s own working directory, workspace, history, and source documents separate from any other RStudio windows you have open. They are a great way to organize your analyses and experiments. I have my own “new project” [script](http:\/\/rud.is\/dl\/newprj.sh) that sets up additional directory structures, configures the `Rproj` file with my preferences and initializes a git repository for the project.<\/p>\n

I also use the setup step to load up a ggplot2 map theme I keep in a gist.<\/p>\n

library(sp)\r\nlibrary(rgdal)\r\nlibrary(dplyr)\r\nlibrary(rvest)\r\nlibrary(stringi)\r\nlibrary(scales)\r\nlibrary(RColorBrewer)\r\nlibrary(ggplot2)\r\n\r\n# for theme_map\r\ndevtools::source_gist(\"https:\/\/gist.github.com\/hrbrmstr\/33baa3a79c5cfef0f6df\")<\/pre>\n
**Step 1 – Read in the map**<\/p>\n
This is literally a one-liner:<\/p>\n
nh <- readOGR(\"data\/nhtowns\/NHTOWNS_POLY.shp\", \"NHTOWNS_POLY\")<\/pre>\n
My projects all have a `data` directory and thats where I normally store shapefiles. I used `ogrinfo -al NHTOWNS_POLY.shp` at the command line to determine the layer name.<\/p>\n
**Step 2 - Read in the outage data**<\/p>\n
The `rvest` package is nothing short of amazing. It makes very quick work of web scraping and—despite some newlines in the mix—this qualifies as a one-liner in my book:<\/p>\n
outage <- html(\"http:\/\/www.psnh.com\/outagelist\/\") %>%\r\n  html_nodes(\"table\") %>%\r\n  html_table() %>%\r\n  .[[1]]<\/pre>\n
That bit of code grabs the whole page, extracts all the HTML tables (there is just one in this example), turns it into a list of data frames and then returns the first one.<\/p>\n
**Step 3 - Data wrangling**<\/p>\n
While this step is definitely not as succinct as the two previous ones, it's pretty straightforward:<\/p>\n
outage <- outage[complete.cases(outage),]\r\ncolnames(outage) <- c(\"id\", \"total_customers\", \"without_power\", \"percentage_out\")\r\noutage$id <- stri_trans_totitle(outage$id)\r\noutage$out <- cut(outage$without_power,\r\n    breaks=c(0, 25, 100, 500, 1000, 5000, 10000, 20000, 40000),\r\n    labels=c(\"1 - 25\", \"26 - 100\", \"101 - 500\", \"501 - 1,000\",\r\n             \"1,001 - 5,000\", \"5,001- 10,000\", \"10,001 - 20,000\",\r\n             \"20,001 - 40,000\"))<\/pre>\n
We filter out the `NA`'s (this expunges the \"total\" row), rename the columns, convert the town name to the same case used in the shapefile (NOTE: I could have just `toupper`ed all the town names, but I really like this function from the `stringi` package) and then use `cut` to make an 8-level factor out of the customer outage count (to match the PSNH map legend).<\/p>\n
**Step 4 - Preparing the map for plotting with `ggplot`**<\/p>\n
This is another one-liner:<\/p>\n
nh_map <- fortify(nh, region=\"NAME\")<\/pre>\n
and makes it possible to use the town names when specifying the polygon regions we want to fill with our spiffy color scheme.<\/p>\n
**Step 5 - Plotting the map**<\/p>\n
It is totally possible to do this in one line, but many kittens will lose their lives if you do. I like this way of structuring the creation of a `ggplot` graphic since it makes it very easy to comment out or add various layers or customizations without worrying about stray `+` signs.<\/p>\n
gg <- ggplot(data=nh_map, aes(map_id=id))\r\ngg <- gg + geom_map(map=nh_map, aes(x=long, y=lat),\r\n                    color=\"#0e0e0e\", fill=\"white\", size=0.2)\r\ngg <- gg + geom_map(data=outage, map=nh_map, aes(fill=out),\r\n                    color=\"#0e0e0e\", size=0.2)\r\ngg <- gg + scale_fill_brewer(type=\"seq\", palette=\"RdPu\",\r\n                             name=\"Number of\\ncustomer outages\\nin each town\")\r\ngg <- gg + coord_equal()\r\ngg <- gg + labs(title=sprintf(\"%s Total PSNH Customers Without Power\",\r\n                              comma(sum(outage$without_power))))\r\ngg <- gg + theme_map()\r\ngg <- gg + theme(legend.position=\"right\")\r\ngg<\/pre>\n
That sequence starts the base `ggplot` object creation, sets up the base map colors and then overlays the town outage colors. We use the `RdPu` [Color Brewer](http:\/\/colorbrewer2.org\/) sequential palette and give the legend the same title as the PSNH counterpart.<\/p>\n
The shapefile is already projected (Lambert Conformal Conic—take a look at it with `ogrinfo -al`), so we can get away with using `coord_equal` vs re-projecting it, and we do a tally of outages to stick in the title. My base `theme_map` is designed for Maine, hence the extra `theme` call to move the legend.<\/p>\n
**The Finished Product**<\/p>\n
Crisp SVG polygons, no cluttered Bing Maps tiles and a proper color palette.<\/p>\n
![img](http:\/\/rud.is\/dl\/psnh.svg)<\/center><\/p>\n
All the code is [up on github](https:\/\/github.com\/hrbrmstr\/psnh).<\/p>\n","protected":false},"excerpt":{"rendered":"
I and @awpiii were trading news about the power outages in Maine & New Hampshire last night and he tweeted the link to the @PSNH [Outage Map](http:\/\/www.psnh.com\/outage\/). As if the Bing Maps tiles weren’t bad enough, the use of a categorical color scale instead of a sequential one[[1](http:\/\/earthobservatory.nasa.gov\/blogs\/elegantfigures\/2011\/05\/20\/qualitative-vs-sequential-color-scales\/)] caused sufficient angst that I whipped up […]<\/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":true,"_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":[24,678,673,674,720,706,91],"tags":[810],"class_list":["post-3141","post","type-post","status-publish","format-standard","hentry","category-charts-graphs","category-data-visualization","category-datavis-2","category-dataviz","category-gis","category-maps","category-r","tag-post"],"yoast_head":"\nPower Outage Impact Choropleths In 5 Steps in R (featuring rvest & RStudio "Projects") - 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\/2014\/11\/27\/power-outage-impact-choropleths-in-5-steps-in-r-featuring-rvest-rstudio-projects\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Power Outage Impact Choropleths In 5 Steps in R (featuring rvest & RStudio "Projects") - rud.is\" \/>\n<meta property=\"og:description\" content=\"I and @awpiii were trading news about the power outages in Maine & New Hampshire last night and he tweeted the link to the @PSNH [Outage Map](http:\/\/www.psnh.com\/outage\/). 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Central Maine Power provides an\u2026","rel":"","context":"In "Charts & Graphs"","block_context":{"text":"Charts & Graphs","link":"https:\/\/rud.is\/b\/category\/charts-graphs\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2013\/11\/Plot_Zoom.png?fit=530%2C680&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2013\/11\/Plot_Zoom.png?fit=530%2C680&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2013\/11\/Plot_Zoom.png?fit=530%2C680&ssl=1&resize=525%2C300 1.5x"},"classes":[]},{"id":2816,"url":"https:\/\/rud.is\/b\/2013\/11\/28\/one-more-timemapping-maine-power-outages-with-d3\/","url_meta":{"origin":3141,"position":1},"title":"One More Time\u2026Mapping Maine Power Outages with D3","author":"hrbrmstr","date":"2013-11-28","format":false,"excerpt":"It started with a local R version and migrated to a Shiny version and is now in full D3 glory. Some down time gave me the opportunity to start a basic D3 version of the outage map, but it needs a bit of work as it relies on a page\u2026","rel":"","context":"In "d3"","block_context":{"text":"d3","link":"https:\/\/rud.is\/b\/category\/d3\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2013\/11\/Central_Maine_Power_Live_Outage_Map-2.png?fit=757%2C649&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2013\/11\/Central_Maine_Power_Live_Outage_Map-2.png?fit=757%2C649&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2013\/11\/Central_Maine_Power_Live_Outage_Map-2.png?fit=757%2C649&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2013\/11\/Central_Maine_Power_Live_Outage_Map-2.png?fit=757%2C649&ssl=1&resize=700%2C400 2x"},"classes":[]},{"id":2846,"url":"https:\/\/rud.is\/b\/2013\/12\/27\/points-polygons-and-power-outages\/","url_meta":{"origin":3141,"position":2},"title":"Points, Polygons and Power Outages","author":"hrbrmstr","date":"2013-12-27","format":false,"excerpt":"Most of my free coding time has been spent tweaking a D3-based live power outage tracker for Central Maine Power customers (there's also a woefully less-featured Shiny app for it, too). There is some R associated with the D3 vis, but it's limited to a cron job that's makes the\u2026","rel":"","context":"In "Data Visualization"","block_context":{"text":"Data Visualization","link":"https:\/\/rud.is\/b\/category\/data-visualization\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":2803,"url":"https:\/\/rud.is\/b\/2013\/11\/27\/mapping-power-outages-in-maine-dynamically-with-shinyr\/","url_meta":{"origin":3141,"position":3},"title":"Mapping Power Outages in Maine Dynamically with Shiny\/R","author":"hrbrmstr","date":"2013-11-27","format":false,"excerpt":"I decided to forego the D3 map mentioned in the previous post in favor of a Shiny one since I had 90% of the mapping code written. I binned the ranges into three groups, changed the color over to something more pleasant (with RColorBrewer), added an interactive table for the\u2026","rel":"","context":"In "data driven security"","block_context":{"text":"data driven security","link":"https:\/\/rud.is\/b\/category\/data-driven-security\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2013\/11\/162.243.111.4_3838_outages_.png?fit=470%2C735&ssl=1&resize=350%2C200","width":350,"height":200},"classes":[]},{"id":6930,"url":"https:\/\/rud.is\/b\/2017\/11\/02\/yet-another-power-outages-post-full-tidyverse-edition\/","url_meta":{"origin":3141,"position":4},"title":"Yet-Another-Power Outages Post : Full Tidyverse Edition","author":"hrbrmstr","date":"2017-11-02","format":false,"excerpt":"This past weekend, violent windstorms raged through New England. We \u2014 along with over 500,000 other Mainers \u2014 went \"dark\" in the wee hours of Monday morning and (this post was published on Thursday AM) we still have no utility-provided power nor high-speed internet access. The children have turned iFeral,\u2026","rel":"","context":"In "R"","block_context":{"text":"R","link":"https:\/\/rud.is\/b\/category\/r\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2017\/11\/plot_zoom_png.png?fit=1200%2C628&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2017\/11\/plot_zoom_png.png?fit=1200%2C628&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2017\/11\/plot_zoom_png.png?fit=1200%2C628&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2017\/11\/plot_zoom_png.png?fit=1200%2C628&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2017\/11\/plot_zoom_png.png?fit=1200%2C628&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":6917,"url":"https:\/\/rud.is\/b\/2017\/10\/30\/gg_tweeting-power-outages\/","url_meta":{"origin":3141,"position":5},"title":"gg_tweet’ing Power Outages","author":"hrbrmstr","date":"2017-10-30","format":false,"excerpt":"As many folks know, I live in semi-rural Maine and we were hit pretty hard with a wind+rain storm Sunday to Monday. The hrbrmstr compound had no power (besides a generator) and no stable\/high-bandwidth internet (Verizon LTE was heavily congested) since 0500 Monday and still does not as I write\u2026","rel":"","context":"In "ggplot"","block_context":{"text":"ggplot","link":"https:\/\/rud.is\/b\/category\/ggplot\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/posts\/3141","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/comments?post=3141"}],"version-history":[{"count":0,"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/posts\/3141\/revisions"}],"wp:attachment":[{"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/media?parent=3141"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/categories?post=3141"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/tags?post=3141"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}