My submission to Tableau’s annual data viz competition is a call to action for Angelenos to get involved in Neighborhood Councils. This post will cover why and how I put it together.
1. Choosing a topic.
I am now about halfway through Jane Jacobs’ seminal book on urban planning, The Death and Life of Great American Cities, and it has been extremely thought-provoking. (In fact, as Tableau gets more into spatial analytics and urban systems, it might be a good addition to the viz book club).
Her chapter on neighborhood self-government was especially poignant, and I was pleased to connect the dots that it’s exactly the intention behind LA’s neighborhood council system. So, even though I had spent ~3 days looking through all sorts census data, I decided to ditch all of that (for now) and instead make something simple to showcase what neighborhood councils are and why/how Angelenos should get involved.
2. Collecting the data.
- I downloaded the Neighborhood Council shapefile from the LA City GeoHub here. In addition to the geometry, the dataset contains the date the council was certified by the city and what planning area/service region it is a part of.
- The information on when and where the councils meet came from the EmpowerLA website. For the sake of practicing and because this information is likely to change over time, I used R to scrape the data directly from the site. More details will need to go in a separate post, but the code is pretty short so here it is in case it’s helpful:
#webscraping in R using the rvest package
url <- “http://empowerla.org/councils/"#each observation is now saved in a table since it's a table in the html
tbl1 <- url %>%
html_nodes(xpath = ‘//*[@id=”post-417"]/div/div/div/div/div/div/table’) %>%
html_table()#converting to a data frame
NC_meetings <- tbl1[] #use two brackets to extract elements from a list
3. Crafting the story and layout
This step always takes a lot of research, thinking, and whiteboarding. In fact, although the contest ends today and my viz is a ‘final draft,’ I will surely continue iterating on and repurposing the story for new audiences and mediums.
As one example for where to take your viz story, I’ve been simultaneously editing the Wikipedia entry on Neighborhood Councils. My wikipedia soapbox will also need to be a separate post.
4. Building the visualization.
If you are disciplined on step 3, then this step is a piece of cake for the most part. Yes, there were times when I had 10 tabs open between google and the Tableau community forum and blog posts on tips to wining Iron Viz, but that is how you learn and grow.
The greatest challenge here is that the final wording, formatting, and title can make or break your viz. I am not 100% happy with these three aspects of mine, but the contest doesn’t officially end until midnight tonight so if you have any suggestions, please do share! Good luck everyone :)