Data Analytics & API Applications

Possibly the most well known APIs (Application Programming Interface) are the Google APIs. Among these, the Google Maps API, or its use, might be the most familiar. See about integrating political/statistical geography and Google Maps API. This section reviews different types of APIs.

Data Analytics and APIs
API technology/tools play an important role in accessing and integrating geographic, demographic and economic data. APIs offer two types of benefits. For Web-based applications, APIs provide the ability for on-the-fly access to selected demographic-economic buried in otherwise large datasets that typically otherwise involve downloading and preprocessing. A second important benefit/use is to extract data from those same datasets, reconfigure the structure of the data retrieved by API and create a new dataset structure that lends itself to analytical applications.

ProximityOne Data Analytics sessions review purpose, scope, strengths, advantages & limitations of APIs described in this section. Topics included in the related Web section include:
• Federal Geographic-Demographic-Economic Data Access Using APIs
• REST APIs
• Federal Communications Commission
• Bureau of the Census … much more than Census
• Bureau of Economic Analysis
• Bureau of Labor Statistics
• Data Access & Analytics Applications
There are hundreds more APIs available from Federal agencies and wide-ranging sources.

Using APis and GIS: Visualizing Patterns; Geospatial Analysis
The following graphic has been developed first using API tools to create the underlying datasets. While the source data used in this application could have been downloaded and processed in legacy manner, the API tools provide on-the-fly development of the data in a structure required by the GIS software. These data are then integrated into shapefiles for use with the GIS software. Once the datasets are developed, they can be used in a myriad of application, GIS and otherwise.

Patterns of Male Hispanic Population Age 5 Years by ZIP Code
— Houston, TX Area

• Click graphic for larger view with ZIP Code labels and more detail.
• The graphic shows patterns of the Male Hispanic population 5 years of age as of Census 2010.
• The view illustrates how single year of age by gender by race/origin can be visually analyzed.
• See more about these data and single year of age demographics

Examples and More Detail
See the corresponding Web section on Data Analytics & Using APIs. Many See application examples are shown there.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data.

Creating & Using Address Shapefiles

… there are many online tools that enable you to key in an address and show the location on a map. This section is focused on creating and using address-based point shapefiles in a GIS context. These methods provide similar information, showing the addresses on a map, but also enable a wide range of analytical capabilities. For example, find out how many of your addresses are in one county or census tract. Or, determine the census block or school district for each address.

Visualize Address Locations

The above views illustrates use of Find Address tool, described below, to locate/show addresses listed below. Marker/locations are shown with different markers based on a query. Markers are labeled with the point ID.
1100 Main St, Kansas City, MO 64105
1301 Wyandotte St, Kansas City, MO 64105
1701 W. 39th Street, Kansas City, MO 64111
4101 Main Street, Kansas City, MO 64111
302 Nichols Rd., Kansas City, MO 64112
6100 Broadmoor St, Mission, KS 66202
5800 Antioch Rd, Merriam, KS 66202
11815 E Highway 40, Independence, MO 64055

Use the no-fee ProximityOne User Group version of the CV XE GIS software to enter addresses, show them on a map and automatically save the shapefile for reuse in the existing or other GIS projects.

Entering Addresses
Install CV XE GIS software and enter your User Group userid. Start CV XE GIS and select the Tools>Find Address feature.

After clicking Tools>Find Address, prompt appears showing default address. Enter an address or use the default value; click OK. Optionally continue adding addresses.  End the process by entering null address (no value). The first step is illustrated in the following graphic using an address in the Kansas City, MO area.

Shapefile Automatically Created
The default point shapefile name c:\cvxe\1\$$address1.shp is created as shown in message in the graphic below. In this example, only one address was entered. The address location is shown by the red marker. The shapefile is added to the existing GIS project. See legend panel top left in the graphic.

Using the Results
The next graphic illustrates using the Identify tool to click on point which displays the mini-profile for the selected point/address. Address/point attributes that are automatically created include the point number and address in ‘name’ field. Use other features of the software to modify the marker/point appearance, label the addresses or add other attributes to each address.

Unlike online address-locators and display services, using the GIS operation you can determine which in which census block or other political/statistical areas (congressional district, school district, etc.) the address is located. If your point shapefile contains many addresses there are also geospatial analysis tools that can be used. Use the site analysis feature select a group of addresses, visually on the map, and create/display a profile of aggregated data for the selection of points.

Contextual View of Matched Road/Street Segment
You can also view the address locations in context of the matched street segment. The next graphic shows a zoom-in view. The roads/streets layer has made active (click on layer name in legend panel). The Identify tool is used to create mini-profile of matched street segment as shown in the graphic below.

By using the road segment attributes, the census block code (and higher level geocodes) can be determined/assigned. See more about the road segment attributes.

There are many other tools to create address-based point shapefiles. For example, you might have a file with existing latitude-longitude values/fields. In this case, the Find Address or Find Address-Batch operation is not needed — the latitude-longitude values have already been assigned. Creating a point shapefile by importing records with existing latitude-longitude will be reviewed in an upcoming blog post.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data.

114th Congressional District Demographic Economic Patterns

How do neighborhood demographic-economic characteristics of New York Congressional District 12 compare to adjacent district 7? … or any other congressional district? How to assess needs of congressional district constituents? This section reviews access to and use of thematic and reference maps for each/all 114th Congressional Districts. Interactively rank, view, query and compare demographic-economic characteristics of congressional districts using online tables/tools described in this section.

The CD Gallery provides new map graphics for each 114th Congressional District. Each map graphic shows patterns of economic prosperity by neighborhood in context of the corresponding 114th Congressional District. The most recent American Community Survey (ACS2013) data are used to show neighborhood patterns (based on census tract median household income).

Patterns of Economic Prosperity by Neighborhood
New York 12th Congressional District & vicinity

  • Map view created using CV XE GIS software.
  • View similar thematic pattern maps for each/all congressional districts.

Interactive Demographic Economic Tables
View demographic-economic characteristics of each/all 114th Congressional Districts are included in four interactive tables organized by subject matter group:

  • General Demographics
  • Social Characteristics
  • Economic Characteristics
  • Housing Characteristics

These key approximate 600 subject matter items are based on the American Community Survey (ACS) 1-year estimates.  These data update later in 2015.  

Similar interactive tables are available for these geographies:  Census Tracts , School Districts, Cities, ZIP Codes and State.Metro.County.

Use the interactive tables to view, query, rank, compare characteristics of the population, households and housing for these areas. A scroll section on each page (see links above) lists each of the subject matter items available for each congressional district via the table.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data.

Single Year of Age Demographics

Single year of age (SYOA) demographics are demographic data summarized for the single year of age population (e.g., age 1, age 2, etc.) for a geographic area such as a county, census tract or ZIP code area. This section is part one of three sections and is focused on tools and methods to access, integrate and analyze SYOA data. The second part is focused on integrating these data with other data and use of GIS and geospatial analysis. The third part reviews how these data are used to develop projections and access to/use of projections.  See more details in related Web section. 

Population Age 0 Relative to 1,000 Population by ZIP Code
  — Atlanta Metro

– Crude birth rate approximation: population age 0 relative to 1,000 population
– Darker green: rate 16+; medium green: rate 12-16; light green: less than 12
– Click graphic for larger view, zoom-in, labeled with ZIP codes and rate.
– View developed with CV XE GIS.

Using SYOA Demographics
Except for possibly the single year of age 0, less than one year of age, single year of age demographics are intrinsically not in high demand. The fact that the single year of age demographics can be aggregated to standardized age cohorts and custom age groups is another matter entirely. Analysts and researchers often need current estimates or projections for age-gender-race/origin groups that are not available from pre-planned tabulations.

Uses of these SYOA data include the basics of understanding the size of a specific age group relative to the total population. Or, how the size of a total population age group compares among genders or a specific race/origin. There are a myriad of more focused applications such as estimating voter propensities/outcomes for certain combinations of age by gender by race/origin combinations. What single year of age data are available and how can they be used to meet these needs?

SYOA Data Options
The only Census Bureau-sourced option for SYOA county or sub-county geography data from Census 2010 forward is Census 2010. Age-related data from the American Community Survey (ACS) exist only for age groups (other than a few selected single year tabulations). Age-related data from the Census Bureau model-based annual estimates (county-up) are only available at the 5-year age cohort level. Most SYOA data (covering each age to age 99 and 100 and over) are further broken out only by gender and race/origin. That is, there are no SYOA summary data for other attributes such as foreign born for each/all ages. Census 2010 and ACS Public Use Microdata Sample data can be used to tabulate/estimate SYOA data with extended attributes though 1) such estimates can only be developed for areas 100,000 population or more and 2) the thinness of number of cases generally makes this infeasible.

The National Center for Health Statistics (NCHS/NVSS) provides SYOA data for county geography. These data are controlled to Census Bureau annual model-based estimates (not released by Census). The NCHS “bridge estimates” data are available annually 2010 forward (2013 estimates available as of March 2015). See more information.

ProximityOne provides census tract, ZIP code area and county-up geography SYOA estimates and projections to 2020. See more information about 5-year projections and projections to 2060.

Census 2010 SYOA
The Census-sourced single year of age demographics for sub-county areas are from the Census 2010 Summary File 1 (SF1). The Census 2010 SF1 “PCT012” (PCT: Population Census Tract and higher geography) tables provide single year of age by gender by race/origin population data for U.S. national scope census tract, ZIP code area and higher level geography. See more about the content and structure of the PCT012 tables.

SYOA-based profiles based on the PCT012 data for ZIP Code area 77077 (Houston, TX) are shown below. The tables have been developed using the ProximityOne Modeler2 software (more below).

Table 1. Single Year of Age by Race/Origin; 2010; ZIP Code Area: 77070

Click graphic to view full scroll section.

Table 2. Age by Race/Origin; Age Groups; 2010; ZIP Code Area: 77070

Click graphic for larger view.

Modeler2 Software
The Modeler2 software has been developed by ProximityOne to create demographic-economic estimates and projections at the sub-county geographic levels including census tracts and ZIP code areas. Annual estimates and projections are developed for 2010 through 2020 by single year of age, and for age groups, by census tract and ZIP code area.

The Modeler2 software can also be used to develop Census 2010-based SYOA profiles such as those shown above. While the Census 2010 PCT012 tables provide the basic data needed to develop these profiles, there is a lot that lies between the data existing and the development/availability of consumable data. As shown in the description of the PCT012 tables, the data are organized in Census 2010 SF1 as a set of tables that need to be separately accessed … and then transformed to a usable format. The Modeler2 software provides two options to access and use the basic PCT012 data: via a locally stored all U.S. dataset or via the Census API (a feature integrated into the Modeler2 software).

Members of the ProximityOne User Group can download and use Modeler2 Level 1 and create SYOA profiles for any county in the U.S. See the User Group section for more information about installation and use.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data.

Hispanic Population by Specific Origin by ZIP Code

.. the Hispanic population is diverse … here we share information about data and tools that can be used to examine the Hispanic population by specific origin by ZIP code. The Hispanic or Latino population group is comprised of many specific origin subgroups. The specific origin subgroups are often associated with different regions of the world. Many specific origin subgroups tend to cluster by location within the U.S. both as a result of the geography of emigration (e.g., Mexico to Texas) and association with where same subgroup emigrants have settled (e.g., Cuba to New York). This section provides insights into how the Hispanic specific origin subgroups are distributed across the U.S. by ZIP Code Area. Tools are provided to analyze geographic and subgroup patterns of interest. For more details and to access interactive table see related Web section.

Mexican Population as Percent of Total Hispanic Population
— Los Angeles metro area by ZIP Code

Click for larger view.
Labels show Hispanic population as a percent of total population.
Color patterns show Mexican population as percent of Hispanic population.
View created using CV XE GIS.

Census 2010 identifies approximately 70 Hispanic specific origin subgroups (see list). The table presented below shows the U.S. Census 2010 Hispanic population for a summary of these specific origin subgroups organized into 28 more aggregated groups. The Census 2010 population by ZIP Code for these same 28 subgroups is presented in an interactive table below in this section.

See related sections:
• Hispanic Population by Specific Origin by County
• ZIP Code Geographic, Demographic, Economic Data Resources

Hispanic Population by Specific Origin: Census 2010
This graphic below is a partial view of a table showing Census 2010 Hispanic population by specific origin. See full table in related Web section.

Visual Pattern Analysis with GIS Tools — scroll section
The following graphic shows the Mexican population as a percent of total Hispanic population by ZIP Code area in the Houston, Texas/Harris County (bold black boundary) area. See color/interval patterns in legend at left of map. ZIP codes are labeled with Hispanic population as a percent of total population.

Click for larger view; larger view shows mini-profile of ZIP Code 77077.
View created using CV XE GIS.

Interactive Table
— Hispanic Population by Specific Origin by ZIP Code Area
View, rank, compare, query patterns of the Hispanic population by specific origin by ZIP code area using the interactive table. The following graphic shows a view of the interactive table illustrating Texas ZIP codes sorted in descending order on the Mexican population column.

Click graphic for larger view.

Scope of Specific Origin Data in Interactive Table
The following graphic shows a partial view of the Hispanic specific origin population items that are included in the interactive table. This example shows data for the Houston area ZIP code 77077. See the complete list of items in the related Web section.

Click graphic for larger view.

Link these Census 2010 demographics for ZIP code areas with American Community Survey demographics to view/analyze a broader array of demographic-economic subject matter. See ZIP Code Geographic, Demographic, Economic Data Resources.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data.

Local Area Labor Force Characteristics

.. on the one hand, there are many choices for accessing and using local area labor force characteristics data; on the other, the available options often fall short of meeting the needs.  This section provides a guide to accessing, integrating and using selected local area labor force characteristics data for wide-ranging analysis and decision-making applications. A “local area” as used here refers mainly to city/place, county and sub-county geography (census tract and ZIP Code area). See related Web section.

ACS 2013 Employment Situation by ZIP Code Area
  — Using GIS Tools for Visual & Geospatial Analysis
The American Community Survey (ACS) 5-year estimates have evolved into a primary resource for examining labor force characteristics. One important limitation is the time lag between data availability and reference date. The ACS 2013 data (released December 2014) are for the 5-year period 2009-2013 and centric to mid-2011; in mid-2015 these estimates are 4 years old.

However, these data can provide powerful insights. The following graphic shows the percent unemployed by ZIP Code area in the Houston, Texas/Harris County (bold black boundary) area. The ACS 2013 5-year estimates of the unemployment rate, included in the interactive table below, are shown as a thematic map. It is easy to see which areas/ZIP codes are experiencing higher/lower unemployment rates.

Click for larger view; larger view shows mini-profile of ZIP Code 77077.
See more ZIP Code demographic-economic data resources.
View created using CV XE GIS.

This section updates in mid-March (watch in calendar) with new data access information relating to data resources summarized below. The present version of this section is focused on:
1) upcoming updates to the Bureau of Labor Statistics Local Area Unemployment
Statistics program and how this affects labor force data availability and use and
2) an interactive table providing access to ZIP Code area labor force
characteristics based on the American Community Survey 2013 5-year data.

Overview
Statistical programs that provide local area labor force data include:
• American Community Survey
  — annual updates, place of residence based
  — geography: block group, ZIP Code area, city/place, census tract up
  — only the ACS provides labor force data for every congressional district
• ProximityOne current estimates and projections
  — annual updates, place of work & residence based
  — geography: ZIP Code area, city/place, census tract up
• BLS Local Area Unemployment Program (city/place, county up) — see below
• BLS Quarterly Census of Employment and Wages
  — quarterly, long time series, place of work based;
  — geography: county up
• BEA Regional Economic Information System
  — annual, long time series
  — geography: county up
• Decennial census Census 2000 and earlier

Advantages/disadvantages, strengths/weaknesses and more about accessing, integrating and using these data will be included in the mid-March update.

BLS LAUS Program. Effective with the March 2015 release of the Bureau of Labor Statistics Local Area Unemployment Statistics (LAUS) estimates for metropolitan areas and smaller geography, new data and methodology are available for analyzing local area employment patterns. These new data have several far-reaching implications for local area labor force analysis.

The fact that the new data are for the 2013 current vintage metropolitan areas CBSAs is very important. It makes the LAUS data consistent with CBSA geography used in other Federal statistical programs including the the American Community Survey (ACS).

The new LAUS estimation methodology makes the local area employment and unemployment estimates more consistent with ACS data which are used in the LAUS estimation. Use of the annually updated ACS data in the LAUS estimates development is an important update to Census 2000-related data previously used in the estimation process. Other methodological changes should lead to more accurate and useful local area employment estimates for sub-county areas not otherwise available.

ACS 2013 Labor Force Characteristics by ZIP Code Area
  — Interactive Table
Use the interactive table in the related Web section to view, rank, compare, query selected labor force characteristics by ZIP code area. These data are based on the ACS 2013 5 year estimates (same data as used in map view above).

Houston area ZIP Code 77007 (shown at pointer in this view) has an ACS 2013 5-year estimated unemployment rate of 3.8%. See ZIP code 77007 in context of all Texas ZIP code areas in the following graphic (click for larger view). Among all 1,934 Texas ZIP code areas, ZIP code 77007 is ranked 201 (there are 200 ZIP code areas with a lower unemployment rate).

Use the interactive table to perform similar analyses on ZIP code areas of interest.

See the main Local Area Labor Force Web section for mid-March updates (watch in calendar).

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data.