The marketing department at AASHTO is taking a crack at helping us get more on the map. One major benefit to this is that when our next funding cycle rolls around (2023) we will be a bit ahead in the "materials for decision makers" department. To this end, if you have some success story or testimonial regarding the CTPP, I would love to hear about it. It may be tweeted, posted to Facebook or Instagram (if visual), or used in future marketing. If you would rather send them to me, and not the whole list, that would be great: pweinberger(a)aashto.org<mailto:email@example.com>. I've included a couple examples below my signature, to give you ideas.
CTPP Program Manager
"The CTPP program is a vital component for understanding travel in the state of Florida. The data, along with the technical support provided by AASHTO helps Florida understand the nature of the workforce in Florida, how, when, and where they travel for work, and the impacts on congestion and transportation operations. The CTPP data is a cost effective tool for helping Florida DOT achieve its mission of providing for the mobility of people and ensuring economic prosperity by helping provide a data driven solution to transportation problems."
- Florida Department of Transportation
Several major model development projects in the state of Colorado have used CTPP Journey-to-Work data, including development of activity-based models for the Denver region and for the entire state. CTPP is one of the "go-to" sources of travel pattern data that is genuinely independent of the travel survey data commonly used to estimate these models. Unbiased, independent data of this type is very hard to come by, and the CTPP is a critical piece of just about any model development project puzzle.
As promised/threatened, here is my full backstory on the demise of American FactFinder and the rise of tidy census!
Well, I was a bit mystified and ever so slightly chagrined when the US Census Bureau decided to pull the plug on American FactFinder (AFF) on March 30, 2020. “I’ve Grown Accustomed to it’s Face.” As a dutiful citizen census analyst, I thought I’d give the new site http://data.census.gov/ a good look. After a good look, I was really considering just giving up: no more census data and just be a regular retired person. Analyzing census data is a hobby, and analyzing census data with the new data portal is a real chore/ grind/ hassle/ headache.
One major complaint about data.census.gov: you can’t access the older single year American Community Survey data for 2005 through 2009. (You could, in American FactFinder, but alas the AFF no longer exists!) So, if you want single year data for 2005 through 2018 for your large city/county/region, well, sorry Charlie.
I’ve toyed for years of using the “R” package for analyzing census data. I’m an old SAS package programmer, and I was always of the opinion (and custom) to just use SAS (and Excel, and AFF) for my basic analysis of any census data. But SAS is very expensive, and R is free, so, there might be something about “Teaching an Old Dog New Tricks” and to start learning/using R.
The key to analyzing census data in R is the Census Bureau’s API (Application Programming Interface.) I’ve heard about APIs for years (never knew what “API” stood for!), but it seemed like too much to learn when we had American Factfinder to get what we needed and wanted.
I’m not sure when I found out about the R package “tidycensus.” But it sounded worthwhile checking out, and I installed it on my home Mac desktop computer. This was in mid-May. Something for me to do while sheltering-in-place.
I then started to learn about “tidycensus” by watching various YouTube and Census Bureau videos. Tidycensus is a free, add-on R package created in 2017 by Professor Kyle Walker at TCU in Fort Worth, Texas. Along with “tidycensus” there is the “tidyverse” and “tigris” and other packages that I have yet to learn.
These YouTube/Census Bureau videos made learning “tidycensus” a breeze!!! I’m VERY impressed with what we can do with “tidycensus.”
On the other hand, I spent many hours learning how to do even the simplest things using “R”: concatenating (stacking) files; merging files using a join variable; reading and writing “csv” files; subsetting files, etc. I’m getting the hang of using “R” but my overall proficiency is still at a “newbie” level.
So, to wrap up this long introduction, here are various YouTube and Census Bureau webinar videos as a best introduction to tidycensus. I am highly recommending them to all census data analysts!!
Getting Started with R and R Studio by “How to R” (14:37, 9/1/2013)
Kyle Walker: Census Data in R: An Overview (3:54, 2/25/20)
Kyle Walker R Tutorial: Searching for data with tidycensus (3:10, 2/25/20)
Kyle Walker: Basic tidy census functionality (2:30, 2/25/20)
Dr. Kyle Walker is an Associate Professor of Geography at the Texas Christian University in Fort Worth, Texas.
Mary Jo Webster: Using TidyCensus in R, part 1 (26:50, 4/3/20)
Mary Jo Webster: Using TidyCensus in R, part 2 (18:37, 4/3/20)
Ms. Webster is a data journalist at the Star Tribune in Minneapolis, Minnesota.
Amanda Klimek: Using the Census Bureau Application Programming Interface (API) with the American Community Survey (ACS), June 26, 2019, US Census Bureau webinar
Amanda Klimek is a survey statistician with the American Community Survey Office
Here’s the home page for tidycensus:
I’m creating my own set of sample tidycensus r-scripts that I’m looking to share with the community. Let me know if this would help?
Chuck Purvis, Hayward, California
(formerly of the Metropolitan Transportation Commission, San Francisco, California)