Cubit's Blog

Photo by Brandon Griggs on Unsplash

So you need apartment statistics.

I often get requests for apartment data from folks who are:
1. researching where to locate a business that provides services to apartment dwellers like a washateria or car wash; or
2. researching where to buy or build a new apartment facility (and the bank has asked them to include the number of apartment units in an area in their business plan).

What you might not know is that the US Census Bureau reports apartment statistics — which means you don’t HAVE to pay a ton of money to a real estate data company to get an estimate of the number of apartment units in a particular area.

How to get Apartment Statistics from the US Census

If you’d rather spend your time doing more interesting things than learning how to use the American Fact Finder 2 — you can always pay me to pull this data for you using the custom data request form. But just in case you are curious, a glutton for punishment or a college student doing research, here’s how:

1. Head over to the American Fact Finder 2 – Advanced Search.

2. In the Geographies tab on the left, select your geographic area of interest (i.e. New York city, NY or Cook County, Illinois).

3. Then type in these magic words into the search box: “Units in Structure”

4. Then look for the Units in Structure table in the list.

5. Depending on the size of your geographic area & the margin of error that you are comfortable with, you’ll need to choose between the American Community Survey (ACS) 1 year, 3 year or 5 year data. As of today, the ACS 1 year 2011 data are the most current data available. Take a look at the margins of error in the different ACS products to see what table will be the best fit for your purposes.

Fun fact! Now that you know how to pull data via the American Fact Finder 2, there are other statistics that you can get about apartments — not just Units in Structure data.

---

Understanding Your Apartment Statistics

Now you have your apartment data from the Census — but what do the row headings “1, attached”, “1, detached”, “2” actually mean? Here are the Census’ definitions per the American Community Survey definitions.

• 1-Unit, Detached – This is a 1-unit structure detached from any other house, that is, with open space on all four sides. Such structures are considered detached even if they have an adjoining shed or garage. A one-family house that contains a business is considered detached as long as the building has open space on all four sides. Mobile homes to which one or more permanent rooms have been added or built also are included.
• 1-Unit, Attached – This is a 1-unit structure that has one or more walls extending from ground to roof separating it from adjoining structures. In row houses (sometimes called 7 townhouses), double houses, or houses attached to nonresidential structures, each house is a separate, attached structure if the dividing or common wall goes from ground to roof.
• 2 or More Apartments – These are units in structures containing 2 or more housing units, further categorized as units in structures with 2, 3 or 4, 5 to 9, 10 to 19, 20 to 49, and 50 or more apartments.
• Boat, RV, Van, Etc. – This category is for any living quarters occupied as a housing unit that does not fit the previous categories. Examples that fit this category are houseboats, railroad cars, campers, and vans. Recreational vehicles, boats, vans, tents, railroad cars, and the like are included only if they are occupied as someone’s current place of residence.
• Mobile Home – Both occupied and vacant mobile homes to which no permanent rooms have been added are counted in this category. Mobile homes used only for business purposes or for extra sleeping space and mobile homes for sale on a dealer’s lot, at the factory, or in storage are not counted in the housing inventory.

---

US Cities with the Most Apartment Units

Just for fun, here are the 40 US cities with the largest number of apartment units according to the American Community Survey 2011 data. No real surprises here. The cities with the largest populations have the most apartment units as do tourist and college towns.

	Geography	Apartment Units
1	New York, NY	2,829,021
2	Chicago, IL	849,096
3	Los Angeles, CA	781,045
4	Houston, TX	442,551
5	Dallas, TX	256,739
6	San Francisco, CA	256,289
7	San Diego, CA	228,212
8	Boston, MA	224,289
9	Philadelphia, PA	219,932
10	Phoenix, AZ	190,495
11	Washington, DC	183,906
12	Austin, TX	175,766
13	San Antonio, TX	173,339
14	Columbus, OH	160,684
15	Seattle, WA	157,533
16	Milwaukee, WI	143,193
17	Denver, CO	135,336
18	Miami, FL	121,343
19	Atlanta, GA	121,086
20	Indianapolis, IN	120,819
21	Charlotte, NC	111,772
22	Jacksonville, FL	110,341
23	Portland, OR	105,165
24	San Jose, CA	104,905
25	Nashville-Davidson, TN	103,981
26	Memphis, TN	100,851
27	Cleveland, OH	98,037
28	Baltimore, MD	96,381
29	Cincinnati, OH	96,051
30	Minneapolis, MN	94,733
31	Detroit, MI	93,888
32	San Juan, PR	93,132
33	St. Louis, MO	93,101
34	Urban Honolulu CDP, HI	92,137
35	Jersey, NJ	92,098
36	Las Vegas, NV	90,887
37	Long Beach, CA	90,168
38	Oakland, CA	90,024
39	Fort Worth, TX	86,814
40	Buffalo, NY	85,595

U.S. Census Bureau. 2011 American Community Survey: B25024 UNITS IN STRUCTURE. Retrieved February 26, 2013 from http://factfinder2.census.gov 

---

If you need help pulling apartment statistics for your area, let me know what data you need by filling out the custom data request form, and I’ll email you back with a quote.

Photo by Justin Eisner on Unsplash

Occasionally, I pull school district population data for clients as a custom data request. Here are 2 tools & 1 technique for pulling demographic data for school districts.

Background

While the US Census Bureau does help collect school district population data, I can’t find school district data on the Census Bureau’s website. For example while I can select “all school districts in New York” in the American Fact Finder 2, I can’t actually pull any demographic or population data for the school districts. The Census Bureau’s website says that they have a project called the Education Demographic and Geographic Estimates project which “produces a variety of geodemographic data for the National Center for Education Statistics.” Ah! Now we are getting somewhere.

Let’s head over to the National Center for Education Statistics website. They have a cool tool called the School District Demographics Systems (SDDS).

Tool 1: NCES’ School District Demographic Systems

• Good for basic demographics & heat maps
• Bad for detailed demographics & pulling the most current demographic data available

Positive: SDDS is Easy to Use

Make your selections in the green box to right, and the map will change accordingly. For example, here’s a map of the Under 18 Hispanic persons for all Texas Unified School Districts.

If you want the actual data that’s displayed on the map, click on the Data Table button. Then click the Save to File button. Pretty nifty, huh?

You can get the following data points:

• Total Students
• Total Population
• Total Occupied Housing Units
• Owner Occupied Housing Units
• Renter Occupied Housing Units
• Average Household Size
• Average Family Size
• Percentage – Householder/Male
• Percentage – Householder/Female
• White Alone
• Black or African American alone
• Asian Alone
• Hispanic or Latino
• American Indian and Alaska Native
• Native Hawaiian and Other Pacific Islander
• OtherMulti-Race
• Total Population Under 18
• Sex by Age Breakdown
• Total Teachers
• Total Librarians / Media Specialists
• Total Revenue

Positive: SDDS Displays Individual Schools & School Boundaries

To see individual schools, select schools in the greenbox to the right. Zoom in to get more detailed data about individual schools. In the map below, you can see schools by type for schools in Harris County, Texas. In addition to school district boundaries, you can also get see individual school boundaries by clicking on Map Layers & changing the selections there.

Positive: Export Spatial Data for School Districts with the SDDS

If you want to build custom maps or do spatial analyses, you can also export the spatial data. Click on the Map Tools button, and then click on Get Spatial data. Select the data which best meets your needs – Census, ACS or SAIPE. If you don’t already know what dataset to use, you’ll probably need a little help from a demographic data nerd or spend a couple of hours digging on the Census Bureau’s website. The differences between these datasets are way more complicated than can be summarized in this blog post. Or you could just download all of the datasets & then pick between then later on.

Negative: Very Limited Data Points are available with the SDDS

So we’ve seen that the SDDS is an awesome and easy to use tool for pulling school district population data–kudos to the builders of this tool–but there’s a potential problem. What if you need data points for school districts that aren’t included in the list above? Here are just a few examples of data points that folks working with school district data want & can’t get from the SDDS (even though these data points below are published by the Census Bureau):

• median household income
• median home value
• household type & family type
• poverty data
• unemployment rates
• industry & occupation data
• transportation statistics
• educational attainment
• languages spoken at home

Enter a 2nd NCES data tool.

Tool 2: NCES’  Demographic Profile Webmap

• Good for more detailed demographic data & heat maps
• Bad for getting the most current demographic data available

The Demographic Profile Webmap is another awesome tool that works like the SDDS tool with the added benefit of providing us with even more demographic data. Oh boy! The only problem is that as of today the Demographic Profile Webmap provides us the ACS 2006 -2010 data. The most current ACS 5 year dataset that is available today is 2007-2011. Hopefully, this app will be updated in the near future. But as of now, you can’t get the most current data from this tool.

Technique 3: GIS Analysis

Let’s say you want the most current data available for the number of people who speak Spanish in a school district. Here’s a very simplified outline of how to do this analysis (warning: if you don’t have a basic understanding of GIS, the following outline might be gibberish).

How to Estimate Data Points for School Districts that are not included in SDDS

1. Download the school spatial boundaries. If you want school district boundaries, you can download them either from the SDDS (see above) or the Census Bureau’s website. If you want individual school boundaries, try the SDDS, but for the most current boundary data, you’ll probably need to contact either the school district or the state education agency.
2. Download the Census boundaries for your area of interest (i.e. state, county, etc.). You can download these boundaries from the Census Bureau’s website. If you aren’t sure what geographic level to use, Census block groups are the smallest level of Census geography with almost all data points. But in the case of language data, we can get much more detailed language data for Census tracts than for block groups. So you may have to do some guess & check to determine the best Census geography to use.
3. Use the school spatial boundaries as “cookie cutters” (aka calculate intersections) to cut out the Census boundaries that are contained within the school boundaries. Let’s pretend that Census Tract A, B & C are all contained within your school district boundary.
4. Then pull the Census language data for Census Tracts A, B & C from the Census Bureau’s website. Now if you are a GIS guru, you could do this step along with step 2 & combine the demographic data with the spatial data. But if you are like me and are more comfortable working with databases than with GIS (GISs? I’m not sure how to pluralize GIS. Or is it like sheep – and GIS is the pural?), you can pull the demographic data at this point & write a quick query to grab only the data points that you need.
5. Finally, sum the counts of Spanish speakers for Census Tract A, B, & C to produce your estimate of Spanish speakers in a school district. So if Tract A has 10 Spanish speakers, Tract B has 5 Spanish speakers & Tract C has 0 Spanish speakers, we can estimate that the school district has 15 Spanish speakers. Summation works well for basic count data, but if you need to estimate “median” values, you’ll probably need to use something like a weighted average calculation.

Hopefully, this post has armed you with enough tools & techniques that you can now pull the school district population data that you need. But if you’d rather not learn the difference between Decennial Census vs ACS data or when it’s better use use Census blocks vs block groups vs tracts, you can always hire me to pull this data for you.

Photo by Blake Wheeler on Unsplash

Occasionally we get asked for ZIP Code-based Census data. We have to say that we don’t have ZIP Code data and neither does the Census. What!? That’s right! But don’t worry, we got your back – the Census publishes ZIP Code Tabulation Areas (ZCTA, pronounced ‘ziktah’).

To quote the Census:

“ZCTAs are generalized area representations of U.S. Postal Service (USPS) ZIP Code service areas. They represent the most frequently occurring five-digit ZIP Code found in a given area. Simply put, each ZCTA is built by aggregating 2010 Census blocks, whose addresses use a given ZIP Code. Each resulting ZCTA is then assigned the most frequently occurring ZIP Code as its ZCTA code.”

In a nutshell: ZCTA 78704 is a representative snapshot of ZIP Code 78704.

ZCTAs Rock! Here’s why:

ZCTAs map to US Census data; ZIP Codes don’t.

About ZIP Codes. We don’t have ZIP code boundaries, because the U.S. Postal Service doesn’t define or publish them. Also, some of ZIP Codes are just routes (a series of connected lines, not polygons).

ZIP Codes change constantly to help the USPS deliver mail more efficiently. That’s what ZIP Codes are designed for: delivery. If you’re planning delivery logistics, use ZIP codes. Some companies offer zip code boundary maps. They estimate (using a variety of methods) polygons based on groups of points, physical landmarks (like bodies of water), and other methods. Most companies have their own private/favorite method of estimating ZIP code boundaries. But because ZIP Codes change so often, boundary maps fall out of sync with US Census demographic data.

US Census Demographic Data + ZCTAs == AWESOME

ZCTAs are polygons fixed to match the census data. By using ZCTAs you get a consistent and accurate representation of a geographic area.

More info about ZCTAs from Census.gov

• http://www.census.gov/geo/ZCTA/zcta.html
• http://www.census.gov/geo/ZCTA/zctafaq.html

Photo by Beatriz Pérez Moya on Unsplash

So this blog post probably won’t be among the most captivating posts I’ve ever written. But it might help someone who is googling around for “how to cite Census data.”

UPDATE: this post was revised on May 8, 2013.

The citations below are in Modern Language Association format — or MLA. And the format of the citation that you’re going to use will depend on HOW you pull the Census data. For example if you use the Census Bureau’s American Fact Finder tool, you’ll use 1 format whereas if you use pull the data from the Census Bureau’s FTP site, you’ll use a different format.

How to Cite American Community Survey Data

1. Cite American Community Survey data pulled via the American Fact Finder (most popular)

United States Census Bureau / American FactFinder. “B11001 : Household Type (Including Living Alone).” 2007 – 2011 American Community Survey. U.S. Census Bureau’s American Community Survey Office, 2011. Web. 1 January 2013 <http://factfinder2.census.gov>.

Note: the date is the date that you pulled the data from the American Fact Finder.

2. Cite American Community Survey data pulled via the Census’ electronic files on the ftp site

United States Census Bureau.“Summary File.”2007 – 2011 American Community Survey. U.S. Census Bureau’s American Community Survey Office, 2013. Web. 1 January 2013 <http://ftp2.census.gov/>.

Note: the date is the date that you download the data from the ftp site.

How to Cite Decennial 2010 Census data

 1. Cite Census 2010 data pulled via the American Fact Finder (most popular)

United States Census Bureau / American FactFinder. “P12 : Sex by Age.” 2010 Census.U.S. Census Bureau, 2010.Web. 1 January 2013 <http://factfinder2.census.gov>.

Note: the date is the date that you pulled the data from the American Fact Finder.

 2. Cite Census 2010 data pulled via the Census’ electronic files on the ftp site

United States Census Bureau. 2010 Census.U.S. Census Bureau. 2010. Web. 1 January 2013 <http://www.census.gov/2010census/data/>.

Note: the date is the date that you download the data from the ftp site.

How to Cite Decennial 2000 Census data

1. Cite Census 2000 data pulled via the American Fact Finder

United States Census Bureau / American FactFinder.“Profile of General Demographic Characteristics: 2000 Census 2000 Summary File 1 (SF 1) 100% Data.” U.S. Census Bureau, 2000.Web. 1 January 2013 <http://factfinder.census.gov>.

Note: the date is the date that you pulled the data from the American Fact Finder.

Double Note: you can’t actually pull Census 2000 data from the the American Fact Finder 2. You used to be able to (or “used to could” for any Texans reading this post) get this data from the old American Fact Finder 1. So I’ll just leave this example here as a hypothetical example.  

 2. Cite Census 2000 data pulled via the Census’ electronic files on the ftp site

United States Census Bureau. 2000 Census.U.S. Census Bureau, 2000.Web. 1 January 2013 <http://www.census.gov/prod/cen2000/>.

Note: the date is the date that you download the data from the ftp site.

Photo by Alex Bertha on Unsplash

I recently got a question from a Cubit user about where to get parcel data. I’ve shared our conversation in hopes that it might answer other peoples’ questions about where to find parcel and real estate data.

The Question: Where Do I Find Parcel Data?

“I’m working on my final project for my masters program & am excited to use Cubit for all the demographic data I’ll need. In the meantime, I need to gather real estate data on recent sales of residential & commercial property in Los Angeles county. The data also needs to include characteristics such as parcel size, structure size, & use. I’ve heard of the MetroScan database, but don’t know how to access it without paying thousands of dollars to CoreLogic. Do you have any ideas on other ways of accessing data like this?”

My Reply — Including the 3 Best Sources for Free Parcel Data

Funny you should ask–we’re actually working on developing a Cubit-like tool for parcel data. But it will include Travis County, Texas parcels only at first. If folks like it, hopefully, we can expand to the rest of the US!

Back to your question, here’s a quick brain dump of free or cheap parcel data tools/sources.

• LoopNet:the standard for commercial property data
• Zillow’s Tool Recent Home Sales
• “parcel size, structure size, and use” That’s where things get tricky. You may know this already, but whenever I need parcel data, I start by contacting 3 government agencies:
  1. the Appraisal District or Tax Assessor,
  2. the Metropolitan Planning Organization or Council of Government and
  3. the City GIS office.

  I’d then use address info provided by Zillow and LoopNet to pull the parcel data from the government agency database.

• Also, in Texas we have a real estate data center as part of Texas A&M that rocks! I wonder if California has a similar resource.

A quick google search turned up that you can buy parcel data from here: http://assessor.lacounty.gov/extranet/Outsidesales/saleintr.aspx
Similar data cost me $85 for all of Travis County, Texas as a reference point. Maybe they’ll give you a student discount? Or offer to share the results of your research with them?
That’s all I can think of. Let me know how it goes!

Are there other good sources of free/cheap parcel data that aren’t included in this blog post? If so, please share in the comments.