Hello to the CTPP listserv. Thought I would share something I started several months ago. I somehow got distracted - - baseball or beer or squirrels or something! My ex-colleague mentioned a year or so ago the R-package “CTPPr” produced by Westat staff. Thought I would give it a test drive. It works great for its intended use: table specific downloads of Part 1, 2, 3 data for entire states (or multiple states). Ideally I would flesh out these examples, using the census mapping options in R, as well as combining it with other census R-packages such as TIGRIS and TIDYCENSUS. Here’s my “getting started” R script for extracting CTPP 2006/10 and 2012/16 data using the CTPPr package. Cheers, Chuck Purvis, Hayward, California (formerly with the Metropolitan Transportation Commission, San Francisco, California). ############################################################ # CTPPr_GettingStarted_1.r # Getting started with the Westat R Package "CTPPr" # CTPPr is authored by: Anthony Fucci, Alexander Cates # and Marcelo Simas of Westat # Note that there isn't an option to select only certain # tracts, places, TADs, TAZs, WITHIN a state... only the # ENTIRE state! User may prefer to use the Beyond2020 # software for extracting only some parts within a state! # # Examples Developed by Chuck Purvis, Hayward, California # -- March 21-25, 2021 -- ########################################################### # Install CTPPr onto local computer.. Just need to do once! # I'm just not sure about etiquette for updating packages! install.packages('devtools') devtools::install_github('Westat-Transportation/CTPPr') # Activate/load the CTPPr library for this script. library("CTPPr") # optional libraries to load, depending on how I expand the examples! library('dplyr') library("tidyverse") library("magrittr") # Produce a VIEWER table of ALL CTPP Tables # It defaults to the CTPP 2012-16 data. Not sure about 2006-10.... ctpp_tables() # Demonstrate various examples of the download_ctpp function.... # without geography= or state=, the function defaults to US States, # 50 US States + District of Columbia + Puerto Rico! # Package authors strongly recommend using BOTH geography= and # state= or you will crash the AASHTO servers or worse. # The default datset is the 2012-2016 CTPP. # CTPPr can also be used to pull 2006-2010 CTPP data. # But TABLE NUMBERING can be different between the two databases, # so be really careful! # Note that a simple one-cell table will retrieve three variables: # 1. Geography Variable Name (RESIDENCE, WORKPLACE, or both!) # 2. Estimate # 3. Standard Error (the Authors have divided the MOE by 1.645 to yield SE) # Table A101100 is Total Population! A one-cell table! # "A" -- based on the entire ACS microdata # "1" -- residence-based geographies # "01" -- data universe is "total population" # "100" -- This is Table #100. # These three examples pull US States. totalpop_1216 <- download_ctpp(A101100) totalpop_1216a <- download_ctpp(A101100,dataset='2016') totalpop_0610 <- download_ctpp(A101100,dataset='2010') # This example, weirdly, provides County data for California! Califpop_1216 <- download_ctpp(A101100,dataset='2016', geography='State', state="California") # Example: Counties within California Calpop_1216a <- download_ctpp(A101100,dataset='2016', geography='County', state="California") # Example: Places within California CalPlacePop_1216a <- download_ctpp(A101100,dataset='2016', geography='Place', state="California") # Example: All Census Tracts within California with the Tract Name CalTractPop_1216a <- download_ctpp(A101100,dataset='2016', geography='Tract', state="California", output="Name") # Example: Tracts within California, Using the FIPS Code instead of Name CalTractPop_1216b <- download_ctpp(A101100,dataset='2016', geography='Tract', state="California", output = 'FIPS Code') # Example: Tracts within California, Split FIPS Code # probably need some follow-on examples to split the FIPS code # into 3 separate variables: state, county, tract. CalTractPop_1216c <- download_ctpp(A101100,dataset='2016', geography='Tract', state="California", output = 'Split FIPS Code') # Example: PUMAs within California # And then add a new variable, Coefficient of Variation (SE/Estimate) CalPUMAPop_1216 <- download_ctpp(A101100,dataset='2016', geography='PUMA', state="California", output = 'Name') CalPUMAPop_1216$CV = CalPUMAPop_1216$SE / CalPUMAPop_1216$Estimate # Example: PUMAs within California, FIPS Code CalPUMAPop_1216a <- download_ctpp(A101100,dataset='2016', geography='PUMA', state="California", output = 'FIPS Code') # Example: PUMAs within California, FIPS Code and Name!! CalPUMAPop_1216b <- download_ctpp(A101100,dataset='2016', geography='PUMA', state="California", output = 'FIPS and Name') # Example: PUMAs within California, Split FIPS Code CalPUMAPop_1216c <- download_ctpp(A101100,dataset='2016', geography='PUMA', state="California", output = 'Split FIPS Code') # Example: Metropolitan Statistical Areas within California # Note: CTPPr documentation doesn't mention the State>MSA sum level. # but it works... at least for California MSA_Pop_1216a <- download_ctpp(A101100,dataset='2016', geography='MSA', state="California", output = 'Name') # Example: Principal Cities within Each MSA in California. # Note that MSAs may have multiple Principal Cities!!! MSACity_Pop_1216 <- download_ctpp(A101100,dataset='2016', geography='City', state="California", output = 'Name') # for whatever reason, pulling urbanized areas isn't working. UA_Pop_1216 <- download_ctpp(A101100,dataset='2016', geography='UA', # state="California", output = 'Name') # Other residence and workplace geography include: # OUSA (workplace tables only); TAD; and TAZ, and MCD(12 MCD states) # Pull a two way table: Population by Hispanic (3) by Race (5) # This yields 15 records (3*5) for each County # Two Additional columns are included in this particular data frame: # -- "Hispanic Origin 3" # -- "Race of Person 5" Calif_County_Race_Hisp_1216 <- download_ctpp(A101204,dataset = '2016', output = "FIPS Code", geography = 'County', state = "California") # Pull a REALLY big two-way table: Workers by Occupation (25) # by Industry (15)... # This yields 21,750 observations for the 58 county California, # Columns include: RESIDENCE, "Occupation 25", "Industry 15", # Estimate, and SE. Calif_County_Workers_Occ_Ind_1216 <- download_ctpp(A102214,dataset = '2016', output = "FIPS Code", geography = 'County', state = "California") # The following doesn't work, even though it's listed in the view # of available tables. Be careful!! # I don't think "C" tables are really available .... Calif_County_Workers_Occ_Ind_1216aaa <- download_ctpp(A102214C,dataset = '2016', output = "FIPS Code", geography = 'County', state = "California") ################################################################## # Workplace Tables! (Part 2 Tables) # Total Workers at Work by County of Work # Output columns in the data frame are: WORKPLACE, Estimate, and SE # "A" -- data is from the entire ACS microdata, not just the 5% in PUMS # "2" -- these are tabulated at the work-end (or workplace) # "02" -- the data universe is "total workers at work" # "100" -- this is table #100 Calif_COW_TotWorkers <- download_ctpp(A202100,dataset = '2016', output = "Name", geography = 'County', state = "California") ################################################################## # Worker Flow Tables (Part 3 Tables) # Total Worker Flows, County-to-County, Intra-State California # Intra State California is 58 by 58 counties, for 3,364 records! # 58 * 58 = 3364.... lots of records with zero commuters!! # Output columns include: RESIDENCE, WORKPLACE, Estimate, SE Calif_Co2Co_TotWork <- download_ctpp(id="A302100", dataset = '2016', output = "FIPS and Name", geography = 'County->County', state = "California") # Pull County-to-County workers for four Western US States # This yields 15,876 records, but a lot of the records have 0 workers! Calif_Neighbors_Co2Co_TotWork <- download_ctpp(id="A302100", dataset = '2016', output = "FIPS and Name", geography = 'County->County', state = "California,Arizona,Nevada,Oregon") # Perhaps continue the above example to just retain # Intra-state records, and inter-state into/out of California.... # End of Getting Started Part 1.