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CTPP Data API Hackathon: Registration Deadline Extended!

by Colby Brown

Dear CTPP Community, The registration deadline for participation in the first ever CTPP Data API Hackathon has been extended to November 19! Check out the following links for more information about this fun and exciting opportunity to get recognized and promoted by AASHTO for your coding achievements: CTPP Hackathon Home Page<https://manhan.co/CTPP-Hackathon.html> Registration Link<https://docs.google.com/forms/d/e/1FAIpQLSfzkqXD7wbnlK2pkl7zd9Xp3o0BFNFAp15…> Slack group (for updates, support, team-building etc.)<https://ctpphackathon.slack.com/join/shared_invite/zt-1ho6lx35j-5Ff_Bc5X64t…> In addition to seeing what transportation modelers and engineers can develop with the new API, we're interested in participation from folks outside our field as well, so please do forward this announcement to any Data for Good or civic hacking groups whose members might be interested. Thank you, Colby Brown CEO and Principal [cid:78a2b950-de02-4e2e-a593-e16714476188]<http://manhan.co> https://manhan.co colby(a)manhangroup.com

2 years, 11 months

Upcoming CTPP Training: Getting to Know CTPP Data on Wednesday, November 16 at 2:00 pm Eastern

by Elzinga, Kyla

[https://files.constantcontact.com/ccfdce84701/6fbaaa3b-507d-401a-955f-0d632…] [https://files.constantcontact.com/ccfdce84701/dbea4755-7fcb-4bd8-9ae3-67fd3…] Join an Interactive CTPP Training on November 16! Getting to Know CTPP Data Wednesday, November 16th, 2022 - 2:00PM to 4:00PM ET The monthly CTPP training continues with the next session: Getting to Know CTPP Data. This two-hour training session will provide an overview of the custom data tabulations in the CTPP and cover topics such as ACS data collection, important information to know about what's included - and not - in the CTPP, and how CTPP compares with other data sources. You'll learn about how the data is collected, how to interpret the data, significance testing, the margin of error, and more! Click here to register today!<https://events-na10.adobeconnect.com/content/connect/c1/1511944328/en/event…> Course Format: * Overview of ACS data collection and what to know about ACS data * What is included - and not - in CTPP data * Comparison with other data sources REQUIREMENTS: * The Adobe Connect Application (download available here<https://helpx.adobe.com/adobe-connect/connect-downloads-updates.html>) * Upon registration, more background information will be provided that you should review on the ACS Questionnaire Registration is limited, so please reserve a seat only if you plan to attend live. This is part of a recurring monthly series on the third Wednesday of every month. Stay tuned for more information on the next training on December 21. Visit https://ctpp.transportation.org/upcoming-events/ to stay up-to-date on future trainings and events. You are receiving this message because you registered for a previous CTPP monthly training.

2 years, 11 months

CTPP Data API Hackathon: Registration Now Open!

by Colby Brown

In partnership with AASHTO and Macrosys, LLC, Manhan is organizing a "hackathon" allowing anyone interested to create and show off apps using a public Beta test version of the CTPP Data API, currently under development. Submitted applications will be ranked and judged by a panel of transportation data analysis and visualization experts, and winning participants will receive public recognition by AASHTO. For more information about this unique opportunity and to register, please visit: https://manhan.co/CTPP-Hackathon.html Thank you, Colby Brown CEO and Principal [cid:ee45bb8d-650a-4be3-8790-71bc4ed0ff13]<http://manhan.co> https://manhan.co +1 (413) 282-8629<http://voice.google.com/calls?a=nc,%2B14132828629> Twitter<https://twitter.com/colbymbrown> | LinkedIn<https://www.linkedin.com/in/colbymbrown/> | Calendly<https://calendly.com/manhangroup/45min>

2 years, 11 months

Fwd: 2021 American ACS 1Year PUMS and ACS 1-Year Supplemental Estimates released

by Ed Christopher

This maybe of interest to some. Ed Christopher 708-269-5237 Begin forwarded message: > From: American Community Survey Data Users Group <noreply(a)prb.org> > Date: October 20, 2022 at 9:41:39 AM EDT > To: Ed Christopher <edc(a)berwyned.com> > Subject: U.S. Census Bureau Releases New 2021 American Community Survey (ACS) 1-Year PUMS and ACS 1-Year Supplemental Estimates > > > Update from American Community Survey Data Users Group > > Mary Ana McKay > 2021 ACS 1-Year Public Use Microdata Sample (PUMS) Files > > We are pleased to announce the release of the 2021 American Community Survey (ACS) 1-year Public Use Microdata Sample (PUMS) files. The PUMS files show the full range of population and housing unit responses collected on individual ACS questionnaires for a subsample of ACS housing units and group quarters persons (approximately one percent of the United States population), with disclosure protection enabled so that individuals or housing units cannot be identified. > > The PUMS files allow data users to conduct a custom analysis. Working with PUMS data generally involves downloading large datasets onto a local computer and analyzing the data using statistical software such as R, SPSS, Stata, or SAS. > > PUMS data are currently accessible via the ACS website, and the FTP site, and the microdata analysis tool on data.census.gov. Data.census.gov is particularly useful for researchers who need quick statistics with PUMS. > > For more information about the PUMS files, visit the links below: > > Creating Custom Tables Using the American Community Survey Public Use Microdata Sample: Review this previously recorded webinar to learn more about creating custom tables using the PUMS files > PUMS Documentation: Need to find out more about using the PUMS? Our technical documentation includes a User Guide, Data Dictionary, Code and Subject Lists, and other documents to assist users in accessing and using PUMS data > PUMS Handbook: This guide provides an overview of the ACS PUMS files and how they can be used to access data about America’s communities. > 2021 ACS 1-Year Supplemental Estimates > > We are also pleased to announce the release of the 2021 ACS 1-year Supplemental Estimates. > > Supplemental Estimates are simplified versions of popular ACS tables for geographic areas with at least 20,000 people, compared to the 65,000 population minimum for the standard ACS 1-year estimates. > > Visit the Census Bureau's data.census.gov or use the Census API to start exploring these estimates. > > For more information on ACS Supplemental Estimates, visit the links below: > > When to use 1-year, 1-year Supplemental, and 5-year estimates: Need help determining which dataset to use? Our “When to use” table provides information on currency, sample size, reliability, and precision for all ACS datasets. > Geographic areas with published data: Review the chart outlining the number of areas receiving data by geographic level for the 1-year Supplemental Estimates. > 1-year Supplemental Estimates table shells: View the layout of tables without the estimates or margins of error filled in. Table shells also contain the line number, description of the data, and table ID. > View online > > > You received this notification because you subscribed to the forum. To stop receiving updates from only this thread, go here. > > Flag this post as spam/abuse. > >

2 years, 11 months

Upcoming CTPP Training: Software Advanced on Wednesday, October 19 at 2:00 pm Eastern

by Elzinga, Kyla

[https://files.constantcontact.com/ccfdce84701/6fbaaa3b-507d-401a-955f-0d632…] [https://files.constantcontact.com/ccfdce84701/dbea4755-7fcb-4bd8-9ae3-67fd3…] Join an Interactive CTPP Training on October 19! CTPP Data Access Software Advanced Wednesday, October 19th, 2022 - 2:00PM to 4:00PM ET As a follow-up to the CTPP Data Access Software Basics course, the CTPP program is offering a two-hour training session that will dive even deeper into the capabilities of the CTPP data access software. In this interactive course, you will have the opportunity to work with your classmates to answer in-depth questions using the CTPP data and software. You'll learn how to display data as charts and maps, plot flow data, and more! Click here to register today!<https://adobe.ly/3M18XFM> Course Format: * Brief introduction to the CTPP * Demonstration of advanced software functions * Interactive group exercise REQUIREMENTS: * The Adobe Connect Application (download available here<https://helpx.adobe.com/adobe-connect/connect-downloads-updates.html>) * Attendance of the CTPP Data Access Software Basics training OR familiarity with the basic software functions. Registration is limited, so please reserve a seat only if you plan to attend live. This is part of a recurring monthly series on the third Wednesday of every month. Stay tuned for more information on the next training on November 16. Visit https://ctpp.transportation.org/upcoming-events/ to stay up-to-date on future trainings and events.

3 years

Re: Trends in Transit Commuting, 2019-2021

by Charles Purvis

Wendell: You’re correct. The OMB added Stanislaus (Modesto MSA) and Merced Counties to the “San Jose-San Francisco-Oakland CSA” originally in their OMB Bulletin No. 18-04 (9/14/2018). So, the older ACS data, up until 2018, used the older CSA definitions; the 2019-2021 data uses the new CSA definitions reflected in the OMB 18-04 and OMB 20-01. Maybe there’s a crosswalk that shows changes in the MSAs, CSAs, MiSA, over the years? How different are the geographic areas as defined in OMB 18-04 vs OMB 20-01? Too bad they kept the same names as before. That’s confusing. Although the “San Jose-San Francisco-Oakland-Modesto-Merced CSA” is a bit awkward. Total Population, San Jose-San Francisco-Oakland CSA: 2017 = 8,837,789 (12 county) 2018 = 8,841,475 (12 county) 2019 = 9,665,887 (14 county) 2020 = 9,619,738 (14 county) 2021 = 9,545,921 (14 county) The CSA data I posted in my e-mail and tweets is accurate, but is reflective of the new 14-County SF Bay Area. Grrrr. The Census Bureau really needs to have an “MPO Geographic Summary Level”!!! I need to update my 9/18/2017 blog post “The ABCs of Defining Metropolis” It’s about defining the Bay Area, 1950-2017. https://censusmaven.wordpress.com/2017/09/18/the-abcs-of-defining-metropoli… <https://censusmaven.wordpress.com/2017/09/18/the-abcs-of-defining-metropoli…> Anybody remember SMSAs? (memo to self: maybe check the land area of the CSA when looking at multiple years, say, 2006 to 2021. If the land area changes between years, maybe the region “has grown” in terms of new counties added?) Chuck > On Sep 20, 2022, at 1:48 PM, Demographia Stl <demographia(a)gmail.com> wrote: > > Charles... > > I believe that Stanislaus and Merced counties are also in the San Jose-SF CSA. Please see https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf <https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf>. > > Best, > Wendell Cox > > On Tue, Sep 20, 2022 at 3:27 PM Charles Purvis <clpurvis(a)att.net <mailto:clpurvis@att.net>> wrote: > I’m pasting together my set of tweets from yesterday and today. Editing and embellishing as I go along. Lots of information here; and a lot more work to do. > > TRENDS IN TRANSIT COMMUTING, 2019-2021 > > I'm pivoting focus from work-at-home to transit commuting #ACSData <https://twitter.com/hashtag/ACSData?src=hashtag_click> > > Including 2020 Experimental Data for a change. > > Work-at-home commuters tripled between 2019 and 2021. > > Transit commuting declined by 51 percent between 2019 and 2021. > > (Bicycling-to-work and walking to work are published/available for 2019 and 2021, but not for 2020. I may want to update this table using PUMS data for 2020-Experimental Weights) > > <Table A transit.png> > > The 51 percent decrease in transit commuters, from the #ACS <https://twitter.com/hashtag/ACS?src=hashtag_click> tracks well with ridership data complied by > @APTA_Transit <https://twitter.com/APTA_Transit> > > 2019-2021 APTA is showing a 53% drop in riders, 2019-2020, and a 4% rebound, 2020-2021. > > APTA is also showing a 36.4% increase in Q2 ridership '22 vs '21. Good! > > The #ACSData <https://twitter.com/hashtag/ACSData?src=hashtag_click> transit commuters for 2020 might actually be too high? > > (My general recollection is that work commutes comprise 40 percent of a region’s transit boardings. So, perhaps, we’ve seen an even more massive decrease in non-work transit usage, 2019 to 2020; and an even more massive recovery in non-work transit usage, 2020-2021 and into 2022!) > > Still, however the 51 percent decrease in transit commuters, 2019 to 2021, is staggering. > > Next years release of the 2022 #ACS <https://twitter.com/hashtag/ACS?src=hashtag_click> should hopefully follow the ridership recovery trends shown by > @APTA_Transit <https://twitter.com/APTA_Transit> > > <Table B transit.png> > > State-level results: New York has the highest number of transit commuters, 2019 and 2021. > > 88% of the nation's transit commuters reside in these 15 states. > > Washington State shows the steepest decline, 71% drop > > (Why rank by number of transit commuters in 2021? This is because the market size really matters here. Large transit markets is where we have the highest investment in public transportation. Follow the numbers on transit commuters!) > > <Table C transit.png> > > Transit Commuting by County-of-Residence > > Four largest transit commute markets are the Boroughs of NYC. > > Steepest declines in San Francisco County, CA and King County, WA (-74%) > > Other counties showing steep decreases: District of Columbia (-69 percent) and Cook County, Illinois (-61 percent). > > > <Table D transit.png> > > Transit Commuting by Place-of-Residence > > New York City has 36% of nation's transit commuters in 2021. > > Steepest declines are in Seattle (-76%) and San Francisco (-74%). > > Yonkers showed least decrease (-19%), 2019 to 2021. > > <Table E transit.png> > > Trends in US Transit Commuting, 2019-2021, continued. > > Combined Statistical Areas (CSA) or "Mega-Region” > > The 31-county New York region had 47% of nation's transit commuters in 2021. > > CORRECTION: The 23-county NY region is for the MSA. The CSA comprises 31 counties!! > https://en.wikipedia.org/wiki/New_York_statistical_areas <https://en.wikipedia.org/wiki/New_York_statistical_areas> > > The 12-county San Jose mega-region had a 75% decrease in transit commuting. San Jose is the largest city by total population in the Bay Area, followed by #2 San Francisco and #3 Oakland. The Bay Area neighbor counties included in the CSA are Santa Cruz, San Benito (Hollister) and San Joaquin (Stockton). They’re a part of the Bay Area due to their high share (>15 %) of commuters working in the central Bay Area. > > <Table F transit.png> > > Metropolitan Statistical Areas are either stand alone metro areas, or parts of larger CSAs. > > The five-county San Francisco-Oakland-Berkeley MSA showed a 76% drop in transit commuters. The MSA includes: San Francisco, San Mateo, Marin, Alameda and Contra Costa Counties. > > The Sea-Tac metro area is showing a 72 percent decrease in transit commuting, 2019-2021. > > <Table G transit.png> > > Transit commuting by Congressional District. > > 13 of the 15 districts with largest transit commutes are in New York City. > > Rounding out top 15 are districts in Boston and Philadelphia. > > <Table H transit.png> > Urbanized Areas ranked by transit commuters in 2021. > > Just the urban portion of metro areas, omitting rural areas within the metro. > > The New York UA has 46 percent of the nation's transit commuters in 2021. / / End of thread > > 335, <Table I transit.png> > > ################################# > > Ranking PUMAs by Number of Resident Transit Commuters, 2021. > > I did check out the 2,378 PUMAs in the US. Of the top 50 PUMAs in the US (based on transit commuters, 2021), 45 are in NEW YORK CITY. Two are in Hudson County, NJ (#33, #42); one is in Westchester County, NY (Yonkers, #46); and two are in Chicago (#47, #50). It’s so very clear that New York dominates the United States public transportation market! > > That’s all for today. > > My r scripts for pulling this data is shared, here: > > https://github.com/chuckpurvis/r_scripts/blob/main/ACS_Transit_Focus_2019_2… <https://github.com/chuckpurvis/r_scripts/blob/main/ACS_Transit_Focus_2019_2…> > https://github.com/chuckpurvis/r_scripts/blob/main/ACS_Transit_Focus_contd_… <https://github.com/chuckpurvis/r_scripts/blob/main/ACS_Transit_Focus_contd_…> > > Feel free to adapt, correct, use these scripts. > > Any additional work on charting this information, say, with the R package, ggplot2, would be very welcome! > > Follow me on twitter: @charleypurvis > > Chuck Purvis > Hayward, California > ################################################################################### > > > > > > > _______________________________________________ > CTPP mailing list -- ctpp(a)listserv.transportation.org <mailto:ctpp@listserv.transportation.org> > To unsubscribe send an email to ctpp-leave(a)listserv.transportation.org <mailto:ctpp-leave@listserv.transportation.org> > > > -- > -- > Wendell Cox +1.618 632 8507 > Demographia | Wendell Cox Consultancy - St. Louis Missouri-Illinois CSA > Founding Senior Fellow, Urban Reform Institute <https://urbanreforminstitute.org/> (Houston) > Senior Fellow, Frontier Centre for Public Policy <https://fcpp.org/> (Winnipeg) > Contributing Editor newgeography.com <http://www.newgeography.com/> > www.demographia.com <http://www.demographia.com/> (principal website) > Demographia International Housing Affordability <http://demographia.com/dhi.pdf> > Demographia <http://demographia.com/worldua.pdf>World Urban Areas <http://demographia.com/db-worldua.pdf> > Urban Reform Institute Standard of Living Index <https://secureservercdn.net/198.71.188.149/be6.064.myftpupload.com/wp-conte…> > _______________________________________________ > CTPP mailing list -- ctpp(a)listserv.transportation.org > To unsubscribe send an email to ctpp-leave(a)listserv.transportation.org

3 years

Re: Trends in Transit Commuting, 2019-2021

by Edward Sullivan

Hello, Not a crosswalk, but the historical delineation files/tables are here: https://www.census.gov/geographies/reference-files/time-series/demo/metro-m… [https://www.census.gov/content/dam/Census/public/brand/census-logo-sharing-…]<https://www.census.gov/geographies/reference-files/time-series/demo/metro-m…> Delineation Files - Census.gov<https://www.census.gov/geographies/reference-files/time-series/demo/metro-m…> Metropolitan, micropolitan, and related statistical area delineation files are available here. www.census.gov and here: https://www.census.gov/geographies/reference-files/time-series/demo/metro-m… [https://www.census.gov/content/dam/Census/public/brand/census-logo-sharing-…]<https://www.census.gov/geographies/reference-files/time-series/demo/metro-m…> Historical Delineation Files - Census.gov<https://www.census.gov/geographies/reference-files/time-series/demo/metro-m…> Metropolitan, micropolitan, and related statistical area historical delineation files are available here. www.census.gov and there's a bit of a crosswalk here: Edward A. Sullivan, III Senior Technical Associate Email: egads(a)epsys.com<mailto:egads@epsys.com> Economic & Planning Systems (EPS) 1330 Broadway, Suite 450 Oakland, CA 94612 T 510-841-9190 http://www.epsys.com<http://www.epsys.com/> ________________________________ From: Charles Purvis <clpurvis(a)att.net> Sent: Tuesday, September 20, 2022 3:54 PM To: The Census Transportation Products Program Community of Practice/Users discussion and news list <ctpp(a)listserv.transportation.org> Subject: [CTPP News] Re: Trends in Transit Commuting, 2019-2021 Wendell: You’re correct. The OMB added Stanislaus (Modesto MSA) and Merced Counties to the “San Jose-San Francisco-Oakland CSA” originally in their OMB Bulletin No. 18-04 (9/14/2018). So, the older ACS data, up until 2018, used the older CSA definitions; the 2019-2021 data uses the new CSA definitions reflected in the OMB 18-04 and OMB 20-01. Maybe there’s a crosswalk that shows changes in the MSAs, CSAs, MiSA, over the years? How different are the geographic areas as defined in OMB 18-04 vs OMB 20-01? Too bad they kept the same names as before. That’s confusing. Although the “San Jose-San Francisco-Oakland-Modesto-Merced CSA” is a bit awkward. Total Population, San Jose-San Francisco-Oakland CSA: 2017 = 8,837,789 (12 county) 2018 = 8,841,475 (12 county) 2019 = 9,665,887 (14 county) 2020 = 9,619,738 (14 county) 2021 = 9,545,921 (14 county) The CSA data I posted in my e-mail and tweets is accurate, but is reflective of the new 14-County SF Bay Area. Grrrr. The Census Bureau really needs to have an “MPO Geographic Summary Level”!!! I need to update my 9/18/2017 blog post “The ABCs of Defining Metropolis” It’s about defining the Bay Area, 1950-2017. https://censusmaven.wordpress.com/2017/09/18/the-abcs-of-defining-metropoli… Anybody remember SMSAs? (memo to self: maybe check the land area of the CSA when looking at multiple years, say, 2006 to 2021. If the land area changes between years, maybe the region “has grown” in terms of new counties added?) Chuck On Sep 20, 2022, at 1:48 PM, Demographia Stl <demographia(a)gmail.com<mailto:demographia@gmail.com>> wrote: Charles... I believe that Stanislaus and Merced counties are also in the San Jose-SF CSA. Please see https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf. Best, Wendell Cox On Tue, Sep 20, 2022 at 3:27 PM Charles Purvis <clpurvis(a)att.net<mailto:clpurvis@att.net>> wrote: I’m pasting together my set of tweets from yesterday and today. Editing and embellishing as I go along. Lots of information here; and a lot more work to do. TRENDS IN TRANSIT COMMUTING, 2019-2021 I'm pivoting focus from work-at-home to transit commuting #ACSData<https://twitter.com/hashtag/ACSData?src=hashtag_click> Including 2020 Experimental Data for a change. Work-at-home commuters tripled between 2019 and 2021. Transit commuting declined by 51 percent between 2019 and 2021. (Bicycling-to-work and walking to work are published/available for 2019 and 2021, but not for 2020. I may want to update this table using PUMS data for 2020-Experimental Weights) <Table A transit.png> The 51 percent decrease in transit commuters, from the #ACS<https://twitter.com/hashtag/ACS?src=hashtag_click> tracks well with ridership data complied by @APTA_Transit<https://twitter.com/APTA_Transit> 2019-2021 APTA is showing a 53% drop in riders, 2019-2020, and a 4% rebound, 2020-2021. APTA is also showing a 36.4% increase in Q2 ridership '22 vs '21. Good! The #ACSData<https://twitter.com/hashtag/ACSData?src=hashtag_click> transit commuters for 2020 might actually be too high? (My general recollection is that work commutes comprise 40 percent of a region’s transit boardings. So, perhaps, we’ve seen an even more massive decrease in non-work transit usage, 2019 to 2020; and an even more massive recovery in non-work transit usage, 2020-2021 and into 2022!) Still, however the 51 percent decrease in transit commuters, 2019 to 2021, is staggering. Next years release of the 2022 #ACS<https://twitter.com/hashtag/ACS?src=hashtag_click> should hopefully follow the ridership recovery trends shown by @APTA_Transit<https://twitter.com/APTA_Transit> <Table B transit.png> State-level results: New York has the highest number of transit commuters, 2019 and 2021. 88% of the nation's transit commuters reside in these 15 states. Washington State shows the steepest decline, 71% drop (Why rank by number of transit commuters in 2021? This is because the market size really matters here. Large transit markets is where we have the highest investment in public transportation. Follow the numbers on transit commuters!) <Table C transit.png> Transit Commuting by County-of-Residence Four largest transit commute markets are the Boroughs of NYC. Steepest declines in San Francisco County, CA and King County, WA (-74%) Other counties showing steep decreases: District of Columbia (-69 percent) and Cook County, Illinois (-61 percent). <Table D transit.png> Transit Commuting by Place-of-Residence New York City has 36% of nation's transit commuters in 2021. Steepest declines are in Seattle (-76%) and San Francisco (-74%). Yonkers showed least decrease (-19%), 2019 to 2021. <Table E transit.png> Trends in US Transit Commuting, 2019-2021, continued. Combined Statistical Areas (CSA) or "Mega-Region” The 31-county New York region had 47% of nation's transit commuters in 2021. CORRECTION: The 23-county NY region is for the MSA. The CSA comprises 31 counties!! https://en.wikipedia.org/wiki/New_York_statistical_areas The 12-county San Jose mega-region had a 75% decrease in transit commuting. San Jose is the largest city by total population in the Bay Area, followed by #2 San Francisco and #3 Oakland. The Bay Area neighbor counties included in the CSA are Santa Cruz, San Benito (Hollister) and San Joaquin (Stockton). They’re a part of the Bay Area due to their high share (>15 %) of commuters working in the central Bay Area. <Table F transit.png> Metropolitan Statistical Areas are either stand alone metro areas, or parts of larger CSAs. The five-county San Francisco-Oakland-Berkeley MSA showed a 76% drop in transit commuters. The MSA includes: San Francisco, San Mateo, Marin, Alameda and Contra Costa Counties. The Sea-Tac metro area is showing a 72 percent decrease in transit commuting, 2019-2021. <Table G transit.png> Transit commuting by Congressional District. 13 of the 15 districts with largest transit commutes are in New York City. Rounding out top 15 are districts in Boston and Philadelphia. <Table H transit.png> Urbanized Areas ranked by transit commuters in 2021. Just the urban portion of metro areas, omitting rural areas within the metro. The New York UA has 46 percent of the nation's transit commuters in 2021. / / End of thread 335, <Table I transit.png> ################################# Ranking PUMAs by Number of Resident Transit Commuters, 2021. I did check out the 2,378 PUMAs in the US. Of the top 50 PUMAs in the US (based on transit commuters, 2021), 45 are in NEW YORK CITY. Two are in Hudson County, NJ (#33, #42); one is in Westchester County, NY (Yonkers, #46); and two are in Chicago (#47, #50). It’s so very clear that New York dominates the United States public transportation market! That’s all for today. My r scripts for pulling this data is shared, here: https://github.com/chuckpurvis/r_scripts/blob/main/ACS_Transit_Focus_2019_2… https://github.com/chuckpurvis/r_scripts/blob/main/ACS_Transit_Focus_contd_… Feel free to adapt, correct, use these scripts. Any additional work on charting this information, say, with the R package, ggplot2, would be very welcome! Follow me on twitter: @charleypurvis Chuck Purvis Hayward, California ################################################################################### _______________________________________________ CTPP mailing list -- ctpp(a)listserv.transportation.org<mailto:ctpp@listserv.transportation.org> To unsubscribe send an email to ctpp-leave(a)listserv.transportation.org<mailto:ctpp-leave@listserv.transportation.org> -- -- Wendell Cox +1.618 632 8507 Demographia | Wendell Cox Consultancy - St. Louis Missouri-Illinois CSA Founding Senior Fellow, Urban Reform Institute<https://urbanreforminstitute.org/> (Houston) Senior Fellow, Frontier Centre for Public Policy<https://fcpp.org/> (Winnipeg) Contributing Editor newgeography.com<http://www.newgeography.com/> www.demographia.com<http://www.demographia.com/> (principal website) Demographia International Housing Affordability<http://demographia.com/dhi.pdf> Demographia <http://demographia.com/worldua.pdf> World Urban Areas<http://demographia.com/db-worldua.pdf> Urban Reform Institute Standard of Living Index<https://secureservercdn.net/198.71.188.149/be6.064.myftpupload.com/wp-conte…> _______________________________________________ CTPP mailing list -- ctpp(a)listserv.transportation.org<mailto:ctpp@listserv.transportation.org> To unsubscribe send an email to ctpp-leave(a)listserv.transportation.org<mailto:ctpp-leave@listserv.transportation.org>

3 years

Re: Working at Home in America: 2019 vs 2021:

by Charles Purvis

Hey Ed: My guess with Redmond, WA and Dublin, CA is that they both popped the magical 65,000 total population barrier in 2021. Of course, my detailed spreadsheets found enough weirdness to question everything. Pearland, Texas. Population = 131,448 (2019) and 120,694 (2021). Table DP03 shows workers by mean of commute for 2019 but not for 2021. My R script results match what I can find on data.census.gov <http://data.census.gov/>. Why the population decline? I’m suspicious. Meridian, Idaho. Population = 114,161 (2019) and 125,959 (2021). Again, table DP03 shows workers by means of commute for 2019 but not for 2021. Again, matches data.census.gov <http://data.census.gov/>. The Villages, Florida. Population 85,377 (2019) and 80,691 (2021). No data on workers by means of transportation to work for either year. This makes sense (?) since The Villages is the largest age 55+ community in the USA. VERY few commuters to be expected. But what happened with total population? A decline? Question: Is the 2021 ACS taking into account data on total population, population by age/sex from the now available Census 2020?? I don’t know. Both the US and States pull both 1 and 52 (states + DC + PR) in my R script for both 2019 and 2021. That’s a relief. County = 840 in 2019; 841 in 2021… The joined dataset is 852 counties. A little more messy. Place = 634 places in 2019; 634 places in 2021; but the joined dataset is 650 places. Some places pop-in; some places are popping-out. Good grief. PUMA = 2,364 in 2019; 2,364 in 2021; and joined together, still, 2,364. We get the most number of geographic areas in the single-year ACS using PUMAs. And it’s wall-to-wall, shore-to-shining-shore coverage. This is really good to know and to share. I think we have 2,487 PUMAs based on Census 2020, but I need some verification/ backup from Census Bureau or State Data Centers to check over my analyses. I may want to do a test run at the county and place level, for a single year, say 2021, for commuting data in tables DP03, B08006, and C08006. DP03 has data on workers by 6 means of transportation; B08006 has data on workers by 13 means of transportation; C08006 has data on workers by 8 means of transportation. I think the fewer categories, the less suppression? I went to the White Sox / Athletics game this past Sunday. Dave Stewart’s number retired. Rickey, Dennis, Carney, McGwire, Reggie, Wally Haas, and LaRussa were all there. A’s win the game, too. Fun day in Oakland. Chuck > On Sep 15, 2022, at 5:25 PM, Ed Christopher <edc(a)berwyned.com> wrote: > > Thanks Chuck. Its always interesting to see the different summaries that people are putting together. Being a small area guy I am sort of wondering what the suppression rule is that is "NAing" the Bethesda and Dublin data in 2019. > > On 9/15/2022 4:31 PM, Charles Purvis wrote: >> I’m assembling some of my tweets from today’s efforts. If you’re on twitter, follow my at @charleypurvis >> >> New #ACSdata on workers working at home. Top ten states + US. Using #tidycensus . What REALLY surprised me is that the US work-at-home share increased from 5.72% in 2019 to 15.82% in 2020 (experimental weights) and FURTHER INCREASED to 17.86 in 2021! Wow. Use Table DP03 for data >> >> <table1_athome.png> >> >> Table 2. Ranking of US Counties #ACSData . DC and neighbor counties; San Francisco; Seattle; NYC; and Atlanta. #tidycensus . These increases are staggering / newsworthy. Had to verify using data.census.gov <http://data.census.gov/> to be sure! >> >> <table2_athome.png> >> >> >> Table 3. Work at home by Place (City) of Residence. DC, San Francisco and Seattle suburbs. Redmond and Dublin are super-fast growing burbs. #ACSData #tidycensus . Data matches @kyle_e_walker tweet from this morning. Lots of stories to tell. >> >> <table3_athome.png> >> >> Now focusing on Working-at-Home in the nine-county San Francisco Bay Area. #ACSData #tidycensus . Work at home share increased from 6.5% (2019) to 32.8% (2021) in Bay Area. Wow. A low of 12.8% in Solano to a high of 45.6% in San Francisco County. @MTCBATA >> >> <table4_athome.png> >> >> Number of workers working at home almost quintupled (five-fold increase) in the Bay Area, 2019 to 2021. #ACSData #tidycensus . From doubling plus in Sonoma County to a staggering septupling (seven-fold increase) in Santa Clara County (Silicon Valley) @MTCBATA Pretty wow. >> >> <Table5_athome.png> >> >> The tables are just screenshots of excel tables that I prepared this morning/early afternoon. >> >> That’s all for now. >> >> Chuck >> >> >> >> >> >> >> >> _______________________________________________ >> CTPP mailing list -- ctpp(a)listserv.transportation.org <mailto:ctpp@listserv.transportation.org> >> To unsubscribe send an email to ctpp-leave(a)listserv.transportation.org <mailto:ctpp-leave@listserv.transportation.org> > > -- > Ed Christopher > 708-269-5237 > _______________________________________________ > CTPP mailing list -- ctpp(a)listserv.transportation.org > To unsubscribe send an email to ctpp-leave(a)listserv.transportation.org

3 years

Southern California Association of Governments analysis of 2021 ACS

by Charles Purvis

OK. This report from the Southern California Association of Governments is absolutely awesome. I’m certain that they (either/both SCAG staff or Professor Dowell Myers at USC) had access to the embargoed data. I saw a SCAG tweet from about 1130 am this morning! Wow! https://scag.ca.gov/sites/main/files/file-attachments/091522-acs-2021-1-yea… <https://scag.ca.gov/sites/main/files/file-attachments/091522-acs-2021-1-yea…> The SCAG/USC analysis focuses on single-year ACS estimates for 2006, 2012, 2019 and 2021. Great job!

3 years

ACS 2021 Single Year Estimates -- working at home data

by Charles Purvis

Well, the single year 2021 estimates from the American Community Survey were released today! Honking and hollerin' Here’s a message I posted on the ACS Data Community (Population Research Board) discussion board: It’s been a busy day with the new single year 2021 estimates released!! I was using a tidycensus R script to pull relevant data on workers working at home, total workers, and total population. Usually I go to table B08006 to get data on workers by means of transportation to work. Kyle Walker, creator of tidycensus, posted a tweet this morning about the top ten or so places by work-at-home share... He used the DP03 table (specifically, table cell DP03_0024P) (Percent working at home). My initial run pulling data from table B08006 missed a few places that Kyle mentioned in his tweet. (Dublin, California, for example) . This is because the DP03 table is almost a "super-collapsed" version of B08006... Even more collapsed than C08006. There is much less likely to be place-level suppression in a DP table compared to the standard "B" (basic) or "C" (collapsed) tables. Not sure if this holds comparing DP to S tables. Ya learn something new every day. My R-script from today's adventures is on my github for all to enjoy (and hopefully correct if I screwed up!) https://github.com/chuckpurvis/r_scripts/blob/main/ACS_WorkatHome_Focus_201… <https://github.com/chuckpurvis/r_scripts/blob/main/ACS_WorkatHome_Focus_201…> Chuck

3 years

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