The goal of this tutorial is to do the following: Collect addresses (via Google Forms) Download to R (via googlesheets) Geocode them (via geocode) Plot them (using leaflet) Get driving distance between them (via gmapsdistance) Cluster them (kmeans) Making the leaflet plot fancy 1. Collect Perhaps in a future post I’ll explore googleformr. For now, I create forms the old-school way.
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The goal of this tutorial is to do the following: Collect addresses (via Google Forms) Download to R (via googlesheets) Geocode them (via geocode) Plot them (using leaflet) Get driving distance between them (via gmapsdistance) Cluster them (kmeans) Making the leaflet plot fancy 1. Collect Perhaps in a future post I’ll explore googleformr. For now, I create forms the old-school way.
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In another post, I describe how I use this data that I’ve scraped, but I wanted to provide a more in-depth tutorial for those interested in how I got the data. Note, this data belongs to Truecar, so all uses herein are for personal and academic reasons only. Get the data In order to do any good analaysis, you first need data. I prefer to have more data than less, where possible.
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This blog will outline what I see as differences between Hugo and Jekyll, some benefits and drawbacks of using Netlify vs. GitHub pages to host, and how to launch the Hugo Tranquilpeak theme from scratch. Why Hugo? One of my first posts was about blogging with Jekyll hosted on GitHub. About six months after writing that post, I hit a few bugs trying to debug it and got frustrated because I had already forgotten all of what I binge-learned earlier.
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If you don’t know how to use the shell/terminal/command line, you should. Why? Here’s a sampling of I’ve done in the last month: I used R to generate 30,000 plots using ggplot(). I used the shell and ffmpeg to animate those plots as a movie. I’ve used the shell from VBA to send an Excel column of data into Stata, execute a summary statistic command, and then import the results back into Excel.
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Author's picture

Bryan Whiting

father, innovator, data scientist

Data Scientist

Washington, D.C.