Category Archives: 113th Congressional Districts

Making & Using Custom 115th Congressional District Maps

.. using GIS resources to create custom 115th Congressional District maps .. use the methods, data and tools described in this section to develop custom congressional district maps. View patterns of economic prosperity by neighborhood for one or all congressional districts. Flexibly associate a congressional district boundary with related geography and subject matter.  See related Web section for more details.

Join the Congressional District-State Legislative District (CDSLD) Group .. be a part of the community. .. click here to join .. there is no cost.

Coming up … mapping/analyzing school district finances in context of the 115th Congressional Districts (June 2017).

See the related section on Making/Using 113th Congressional District Maps.
.. view different congressional district vintages in same map.

115th Congressional Districts by Incumbent Party Affiliation
This view and related GIS project/data update when changes are made to the 115th Congressional Districts incumbents (last updated 5/10/17). Party affiliation shown in this view is also available in the related interactive table. Click graphic for larger view. Expand browser window for best quality view.

– View developed using CV XE GIS and related GIS project.
– see below in this section about using this GIS project.

Use the Geographic Information System (GIS) tools and data to view/show congressional district in context with roads, landmarks and other geography. Flexibly add labels. Create pattern views. Add your own data.

Patterns of Economic Prosperity by 115th Congressional District
The following graphic shows patterns of ACS 2015 median household income (MHI) by 115th Congressional District. Click graphic for larger view. Expand browser window for best quality view.

– View developed using CV XE GIS and related GIS project.
– use the GIS project and tools see below to create different views.

Examine Characteristics of any Congressional District
The following graphic shows patterns of ACS 2015 median household income (MHI) by census tract in context of 115th Congressional Districts in a region of North Carolina. CD 3712 (Charlotte area) is shown with bold boundary. It is easy to see which areas/tracts have different levels of economic prosperity.

– View developed using CV XE GIS and related GIS project.
– use the GIS project and tools see below to create different views; add other layers.

Creating congressional district maps is often specific to a particular analysis, zoom-view, labeling, combination of different geographies or other considerations. While there are no estimates of unemployment by congressional district, using GIS tools it is possible to view/geospatially analyze patterns of unemployment within congressional district by county, census tract, block group and other geography.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

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. Contact Warren. Join Warren on LinkedIn.

Integrating Political/Statistical Geography with OpenStreetMaps

OpenStreetMaps (OSM) is a collaborative project to create/maintain a free editable map of the world. The OSM Internet-based map resource is built by a community of people who contribute and maintain data about roads, local geography and much more, all over the world.

Houston, TX; Texas 113th Congressional District 29
The following view illustrates using a congressional district shapefile (blue boundary) in combination with OSM as a base layer.

GIS Applications Linking/Combining Shapefiles with OSM
This section illustrates viewing political/statistical geography in context of streets/roads shapefiles and/or Web-based street/ground coverage graphics. When using GIS tools to view census tracts (as one example) rendered through the use of shapefiles, there is often no convenient way to view the boundaries in context of roads/ground cover. There are two alternatives. One option is to add a layer using the corresponding streets/roads shapefile. This option has important features but is often difficult, time-consuming or not feasible as the roads shapefile coverages are organized in county units. Also roads shapefiles provide only part of the picture with respect to ground coverage. A second option is to use Web-based roads/ground coverage tiling services such as OpenStreetMap. Both options are reviewed here.

Georgia Metropolitan Statistical Areas shapefile overlay
Metropolitan areas are shown as brown boundaries in the following view.

The CV XE GIS software is used to view a census tracts shapefile/layer in context with 1) roads shapefile/layer and 2) Web-based OpenStreetMap (OSM) layer via OSM WMS (OGC Web Map Service). CV XE GIS supports the OGC WMS standard, which means that it can be used to open map layers from any properly functioning WMS server, including OSM WMS servers. Use of the OSM shown here is available at no cost and has global coverage. Tiling graphics are courtesy of MapQuest.

Honolulu, Hawaii with Census Tract Boundaries
The Hawaii census tracts boundaries (red) are shown in the following view.

Get Started Now
No registration or fees are required to use the CV XE GIS software with OSM. Run the CV XE GIS installer on a Windows-based computer and create views/applications such as those shown below. Make custom maps of your neighborhood or a city/country anywhere in the world.

New York City with Census Tract Boundaries
New York census tracts boundaries (red) are shown in the following view.

Atlanta, GA Region Diversity Patterns Neighborhood
Census tracts are colored based on value of the diversity index. See color patterns assigned based on diversity index values as shown in legend at left of the map. Blue tracts are most diverse; red tracts are least diverse. Tracts shown with black cross-hatched pattern are tracts with 50-percent or more Hispanic population. Transparency of the shapefile layer is set to 80% enabling the view of the OSM basemap layer.

About the Author
— Warren Glimpse, developer of the CV XE GIS software, is former senior Census Bureau statistician responsible for innovative data access and use operations. He is developer of the Columbia, MO GBF/DIME used as the prototype for the Census Bureau TIGER/Line system. 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.

Easy Access to ACS 2013 Demographics

… 4 clicks away from a demographic profile for your selected area …  the American Community Survey (ACS) 2013 1 year estimates provide the most current demographic-economic data for wide-ranging geography having population 65,000 and over.  These geographies include the U.S., regions, divisions, states, counties, county subdivisions, cities/places, native american areas, metros, congressional districts, school districts, public use microdata areas, among others.

These data provide a unique and rich set of data resources for decision-making. They provides analysts and stakeholders with current information they need to plan investments and services. Retailers, homebuilders, police departments, school districts, and town/city planners are among the many private- and public-sector decision makers who count on these annual results.  These data can be made more powerful by integrating them with other data and visually/geospatially analyzing patterns with GIS and modeling tools.

Accessing the Data
The following steps illustrate how you can access data for areas of interest. We use the example of Scottsdale, AZ.
1 – view the table ACS2013.
2 – below the table, replace San Diego with Scottsdale.
3 – click the Find in Name button to the left of Scottsdale.
4 – table refreshes; click get data link in Scottsdale city row.

A new page displays with selected items retrieved:
Area name: Scottsdale city, Arizona
  Total population: 226,909
  One race alone: White: 200,920
  One race alone: Black: 5,017
  One race alone: AI/AN: 2,008
  One race alone: Asian: 9,298
  One race alone: NHOPI: 44
  Hispanic population: 24,961
  Total housing units: 129,434
  Occupied housing units/households: 99,860
  Median household income: $69,690
  Percent high school graduate: 96.7
  Percent college graduate: 54.2
  Median housing value: $382,300
  Median gross rent: $1,134

Optionally import the displayed data into a spreadsheet. Retrieve data for other areas of interest and easily compare attributes for multiple areas.

See details on the main web page —

Support Using these Resources
Learn more about accessing and using ACS data integrated with other data; examine characteristics and patterns for your study areas and applications. Join us in a Decision-Making Information Web session. There is no fee for these one-hour Web sessions. Each informal session is focused on a specific topic. The open structure also provides for Q&A and discussion of application issues of interest to participants.

Computer & Internet Usage Patterns

.. new data resources on computer and Internet usage .. mandated by the 2008 Broadband Data Improvement Act, questions on computer and Internet usage are included in the American Community Survey 2013 for the first time. Initially computer and Internet usage data will be available from the ACS 2013 1-year estimates (September 2014). These estimates are available for areas 65,000 population and over — the September 2014 data are tabulated for the U.S. and all states, metropolitan statistical areas (MSAs), Public Use Microdata Areas (PUMAs), and 113th Congressional Districts as well as large cities, counties and school districts. See related Web section for more detail.

Questions; Scope of Analytical Potential … scroll section
The ACS data are based on two questions on the ACS questionnaire:

The Federal Communications Commission (FCC) will use these data to measure the nationwide development of broadband access, as well as the successful deployment of the next generation of broadband technology. The data will also enable the FCC to develop measures to increase access to broadband technology and decrease barriers. The National Telecommunications and Information Administration (NTIA) will use the data to provide grants that help expand public access to broadband service and fund broadband education and support, particularly to groups that have traditionally underutilized broadband technology.

State and local governments can use the data to evaluate access to broadband in their communities, and institute policies and programs that increase access to areas with less connectivity.

Businesses, investors and other organizations can use the data to analyze computer and Internet usage in their markets and communities. Knowing how many people have access to computers and the Internet helps these groups communicate more effectively with their customers and plan outreach, infrastructure development, ecommerce and more. University researchers and other analysts have a wide range of new ways to examine the how, who and where of computer and Internet usage.

Summary Data Available
There are many new summary statistic tables based on the new questions.
B28001 .. Types of Computers in Household
B28002 .. Presence and Types of Internet Subscriptions in Household
B28003 .. Presence of a Computer and Type of Internet Subscription in Household
B28004 .. Household Income in the Last 12 Months by Presence and Type of Internet Subscription in Household
B28005 .. Age by Presence of a Computer and Types of Internet Subscription in Household
B28006 .. Educational Attainment by Presence of a Computer and Types of Internet Subscription in Household
B28007 .. Labor Force Status by Presence of a Computer and Types of Internet Subscription in Household
B28008 .. Presence of a Computer and Type of Internet Subscription in Household
B28009A-I .. Presence of a Computer and Type of Internet Subscription in Household (By Race and Hispanic Origin)

Related items are included in the Public Use Microdata Sample files and create many new possibilities to develop custom estimates of computer & Internet usage crossed by other population and housing attributes.

Related Data
The report Computer and Internet Use (May 2013) provides household and individual level analysis of computer usage and Internet use. The report is based on data collected in a July 2011 supplement to the Current Population Survey (CPS), which includes questions about computer ownership, Internet use both inside and outside the home, and the additional devices that people use to go online. The U.S. Census Bureau has asked questions in the CPS about computer use since 1984 and Internet use since 1997. The report provides limited scope state-level data and no sub-state data.

Support Using these Resources
Learn more about accessing and using ACS data integrated with other data; examine characteristics and patterns for your study areas and applications. Join us in a Decision-Making Information Web session. There is no fee for these one-hour Web sessions. Each informal session is focused on a specific topic. The open structure also provides for Q&A and discussion of application issues of interest to participants.

2014 Elections: Data Driven Strategies

.. use of geodemographics will have a big impact on the outcomes of many 2014 elections. Many campaigns are gearing up now for the general elections to be held November 4, 2014. Elections will include all 435 seats in the U.S. House of Representatives, 33 seats in the U.S. Senate, 46 state legislatures among many others. How to more effectively examine characteristics and trends of the voting population?  Where are voters with a higher propensity to vote for your candidate located? Which elections might be most effectively impacted by the use of geodemographics?  Join in this no fee one-hour web session where we examine tools and resources to examine geodemographics relating to state legislative districts and congressional districts.

New York 12th Congressional District & vicinity
… using GIS resources to examine a congressional district by neighborhood
… examining neighborhood patterns of economic prosperity
… NY 12th Congressional District (bold black boundary)

click graphic for larger view with details. View developed using CV XE GIS.

2014 Elections: Data Driven Strategies
Geography of State Legislative Districts & 113th Congressional Districts
– State Legislative Districts
– Congressional Districts
Examining Characteristics & Patterns
– strategies for accessing & using demographic-economic data
– geographies: census blocks, voting districts, block groupstractscities/places
– interactive analytical tables:  congressional districts;  state legislative districts
– examining 2012 elections & vote by candidate
– mapping patterns of economic prosperity by neighborhood across districts
– using ACS 2010 5 year estimates and Site Analytics tools to examine sub-district demographics
– accessing census block demographics via API
– voting-age population demographics
Redistricting: congressional; state legislative; city, special area; school districts
2014 elections & campaign strategic planning & analysis

Next Session: June 10, 2014
Register here
Related events

Examining Children’s Demographics by Congressional District

Examining children’s demographics patterns by school district in context of the 113th Congressional Districts … GIS tools enable you to blend different types of geography and subject matter to support planning, analysis and decision-making.

The thematic map below shows patterns of percent grade relevant children ages 5-17 by school district for Ohio and adjacent states. The red pattern shows districts having %Relevant Children Not Enrolled Ages 5-17 value of 10% or more. Click the graphic for larger view and details. The expanded view shows legend and color/interval settings.

113th Congressional Districts are shown with bold black boundaries and yellow labels. It is easy to see groupings of school districts by congressional district with distinctive patterns.

View developed using CV XE GIS software and associated GIS project.

See more about resources to examine children’s demographic-economic characteristics by type of enrollment and school district.

Support Using these Resources
Learn more about accessing, integrating and using data for school districts and congressional districts. Join us in a Decision-Making Information Web session. There is no fee for these one-hour Web sessions. Each informal session is focused on a specific topic. The open structure also provides for Q&A and discussion of application issues of interest to participants.

Community Decision-Making Information

Community decision-making information, as used here, refers to the set of geographic, demographic and economic data that can be used with tools to assess community needs and develop agendas to advance the welfare of community residents and stakeholders. The geographic hub of the community is a city or place — a place of population concentration.

There are approximately 30,000 incorporated cities or census designated places in the U.S. (about cities/places). The focus here is on those incorporated cities, ones with “city limits” and boundaries and government powers designated by the corresponding state.

The concept of the city being a “hub” remains. Geographically, a community is often broader, sometimes narrower, that its defined corporate limits. The graphic shown below shows the combined Jefferson City, MO city, school district and county. The city boundaries differ from those of the school district, a typical scenario with wide ranging variations across the U.S. Typically, residents of the school district have a sense of community centric to the associated city.

Jefferson City, Missouri

Click graphic for larger view. Counties shown with bold gray boundary (white solid label). Cities appear with green fill pattern (white label). The primary school district is shown with bold blue boundary (yellow label); other school districts have lighter blue boundary. Schools appear as red markers.

Community Decision-Making Information
While the leadership, budget, authorizations and related items differ between the school district, city and county, they share the need for a common set of decision-making information. There is a common set of geographic, demographic, and economic data needed by each entity — and neighborhoods throughout the community.

To assess needs, examine change and plan for the future requires data for several types of geography in and around the community. Frequently updated and longitudinal demographic-economic data are needed for geographies including the city, school district(s), schools, county(s), census tracts, ZIP codes, block groups, census blocks, roads and topological structures. Attributes of broader geographic areas including metropolitan areas, Public Use Microdata Areas, state legislative districts and congressional districts are also essential.

These diverse subject matter for diverse geography can often be most effectively assembled and used in a Geographic Information System (GIS).  The view shown below illustrates use of GIS resources to view the location and attributes of low and moderate income neighborhoods.

Affordable Housing; Low & Moderate Income Neighborhoods
See related document for more information.

Organized Access to Key Data
The America’s Communities database and information system assembles selected key data for selected types of geography organized around individual communities. As an example, the Missouri Communities Program provides access to frequently Web-based data with ready-to-use GIS resources. These resources are made available to participating cities and counties at no fee. View the Jefferson City, MO community access Web section to examine the scope and content.

Using Community Decision-Making Information
Participants in the Missouri Community Program are automatically enrolled as members in the ProximityOne User Group — open to anyone at no fee. Join now. The combination of these resources provide a powerful base for community decision-making.

Join us in weekly decision-making information Web sessions where we cover selected data access and use topics as well as Q&A relating to use of the community-focused data profiles and resources.  View sessions  and sign-up here.

Analyzing Social Characteristics Patterns

How does educational attainment vary by congressional district? or by city/place, school district or a range of other geographies? Educational attainment is one of several social characteristics measures. This section reviews the scope of social characteristics measures and how you can access and use these data for different types of geographies. About the data.

Visual Analysis of Educational Attainment by Congressional District
The map presented below shows percent college graduates by congressional district (yellow labels) in the vicinity of Houston, Texas (counties bold black; county names shown as labels). The thematic pattern shows item S067 shown in the DP2 interactive table and further discussed below. Click graphic for larger view and details.

Social Characteristics Measures
A selection of primary social characteristics measures available for wide ranging geographies is shown in the following scroll section. In the scroll section, subject matter items are organized into to mini-tables with related items. The number at the left of the subject matter item is also used as the short name for the subject matter item in the column header in the interactive tables and further described below.

S001     Total households
S002 Family households (families)
S003         With own children under 18 years
S004     Married-couple family
S005         With own children under 18 years
S006     Male householder, no wife present, family
S007         With own children under 18 years
S008     Female householder, no husband present, family
S009         With own children under 18 years
S010 Nonfamily households
S011     Householder living alone
S012           65 years and over
S013   Households with one or more people under 18 years
S014   Households with one or more people 65 years and over
S015   Average household size
S016   Average family size
S017       Population in households
S018   Householder
S019   Spouse
S020   Child
S021   Other relatives
S022   Nonrelatives
S023       Unmarried partner
S024     Males 15 years and over
S025   Never married
S026   Now married, except separated
S027   Separated
S028   Widowed
S029   Divorced
S030     Females 15 years and over
S031   Never married
S032   Now married, except separated
S033   Separated
S034   Widowed
S035   Divorced
S036     Number of women 15 to 50 years old who had a birth in the past 12 months
S037 Unmarried women (widowed, divorced, and never married)
S038     Per 1,000 unmarried women
S039 Per 1,000 women 15 to 50 years old
S040     Per 1,000 women 15 to 19 years old
S041     Per 1,000 women 20 to 34 years old
S042     Per 1,000 women 35 to 50 years old
S043     Number of grandparents living with own grandchildren under 18 years
S044 Responsible for grandchildren
Years responsible for grandchildren
S045         Less than 1 year
S046         1 or 2 years
S047         3 or 4 years
S048         5 or more years
S049     Number of grandparents responsible for own grandchildren under 18 years
S050 Who are female
S051 Who are married
S052     Population 3 years and over enrolled in school
S053 Nursery school, preschool
S054 Kindergarten
S055 Elementary school (grades 1-8)
S056 High school (grades 9-12)
S057 College or graduate school
S058     Population 25 years and over
S059 Less than 9th grade
S060 9th to 12th grade, no diploma
S061 High school graduate (includes equivalency)
S062 Some college, no degree
S063 Associate’s degree
S064 Bachelor’s degree
S065 Graduate or professional degree
S066 Percent high school graduate or higher
S067 Percent bachelor’s degree or higher
S068     Civilian population 18 years and over
S069 Civilian veterans
S070     Total Civilian Noninstitutionalized Population
S071 With a disability
S072     Under 18 years
S073 With a disability
S074     18 to 64 years
S075 With a disability
S076     65 years and over
S077 With a disability
S078     Population 1 year and over
S079 Same house
S080 Different house in the U.S.
S081     Same county
S082     Different county
S083         Same state
S084         Different state
S085 Abroad
S086     Total population
S087 Native
S088     Born in United States
S089         State of residence
S090         Different state
S091     Born in Puerto Rico, U.S. Island areas, or born abroad to American parent(s)
S092 Foreign born
S093     Foreign-born population
S094 Naturalized U.S. citizen
S095 Not a U.S. citizen
S096     Population born outside the United States
S097     Native
S098 Entered 2010 or later
S099 Entered before 2010
S100     Foreign born
S101 Entered 2010 or later
S102 Entered before 2010
S103     Foreign-born population, excluding population born at sea
S104 Europe
S105 Asia
S106 Africa
S107 Oceania
S108 Latin America
S109 Northern America
S110     Population 5 years and over
S111 English only
S112 Language other than English
S113         Speak English less than “very well”
S114     Spanish
S115         Speak English less than “very well”
S116     Other Indo-European languages
S117         Speak English less than “very well”
S118     Asian and Pacific Islander languages
S119         Speak English less than “very well”
S120     Other languages
S121         Speak English less than “very well”
S122     Total population
S123 American
S124 Arab
S125 Czech
S126 Danish
S127 Dutch
S128 English
S129 French (except Basque)
S130 French Canadian
S131 German
S132 Greek
S133 Hungarian
S134 Irish
S135 Italian
S136 Lithuanian
S137 Norwegian
S138 Polish
S139 Portuguese
S140 Russian
S141 Scotch-Irish
S142 Scottish
S143 Slovak
S144 Subsaharan African
S145 Swedish
S146 Swiss
S147 Ukrainian
S148 Welsh
S149 West Indian (excluding Hispanic origin groups)

Social Characteristics Interactive Tables
The U.S. national scope interactive tables provide access to approximately 150 items, updated annually, for a range of geographic levels. Most of these tables include the the primary geography as well as related geography.
Estimates centric to 2012
• U.S.-States-Metros
• Congressional Districts
• Public Use Microdata Areas
Estimates centric to 2010
• U.S.-States-Metros-Counties
• Census Tracts
• ZIP Codes
• School Districts
• Cities/Places

Using the Interactive Tables
Use the interactive tables to view, query, rank, compare social characteristics of the population for these areas. The interactive tables listed above are structured and operate similarly. Items listed in the subject matter scroll box shown above are available for each area via the interactive table.

An example. This short tutorial illustrates use of the interactive tables to examine educational attainment patterns for the Atlanta, Georgia. See a summary of key usage notes below this example.
• Click on U.S.-States-Metros-Counties
• Each row is a summary for the U.S. or a state, metro or county.
• Educational attainment as measured by %high school graduates is item S066.
• Educational attainment as measured by %college graduates is item S067.
• Scroll right to view columns S066 and S067.
• Dbl-click S067 column header cell to rank in descending order.
• Click ShowAll button below table to reset start-up view.
• Examine educational attainment for a metro by county …
• Click the FindCBSA button below the table.
– only rows for the Atlanta metro and Atlanta metro counties appears.
• Click the ColSet1 button below the table.
– ColSet1: shows only AvgHHSize.AvgFamSize.%HSGrad.%CollGrad
– only selected columns appear (and include S066 and S067).
– you are able to examine the educational attainment for each area.
• Click the column header cell for column S067.
– the rows sort ascending on %college graduates.
– you are able to see how educational attainment ranks by area.
• Click the column header cell for column S067 again to sort in other directions.
• Click ShowAll button and repeat process for a different metro.

Related Usage Notes
• All items are estimates centric to mid-2010 or 2012 depending on the table.
• Click ShowAll button between Find/Queries.
• Use mouseover on column header to view column description.
• See ranking table below ranking table. See related ranking tables —
• Cells with -1 value could not be estimated.

About the Data
The American Community Survey (ACS) estimates and ProximityOne projections provide “richer” demographic-economic characteristics for national scope geography. Census 2010 provides data similar to those items in the General Demographics section. Only the ACS 2011 estimates, ACS 2012 estimates and ProximityOne projections provide details on topics such as income and poverty, labor force and employment, housing value and costs, educational participation and attainment, language spoken at home, among many related items. The approximate 600 items accessible via the dataset are supplemented by a wide range of additional subject matter.

Join the ProximityOne User Group to access extended data and more tools;
integrate your own data; use GIS tools to create your own map views.
(join now, no fee).

State Legislative District GeoDemographics

As of the 2012 election cycle updates (reflecting redistricting), the 6,558 state legislative districts in the U.S. are comprised of 4,629 lower/house chambers and 1,929 upper/senate chambers.  See details about state legislative district urban/rural composition — interactive table.  In most states the state legislative district geographic areas changed substantially in connection with redistricting and Census 2010.   The graphic shown below shows Texas senate district 016 as of Census 2010 before redistricting (blue boundary) and Texas senate district 016 as of 2012 after redistricting (red boundary) in the Dallas, Texas area.  The pointer shows where the district has a common boundary in 2010 and 2012.


Understanding the current legislative district geography is essential to analysis, planning and decision-making and the demographic-economic characteristics of the district.  This post is focused on accessing and using state legislative district (SLD) geographic-demographic-economic data.  Census 2010 and American Community Survey (ACS) SLD data are available only for SLD areas as defined in 2010, prior to 2012 election cycle new redrawn boundaries.

State Legislative Districts
State legislative districts are the areas from which members are elected to state or equivalent entity legislatures. State legislative districts are comprised of upper (senate) and lower (house) chambers. Nebraska has a unicameral legislature and the District of Columbia has a single council; these are treated as upper-chamber legislative areas in the interactive table.

State Legislative District Shapefiles & Vintages
2010 and 2012 (2012 election cycle) vintage state legislative district (SLD) shapefiles are included in a U.S. national scope GIS project available to ProximityOne User Group members (no fee).  These shapefiles have been developed by ProximityOne and are based on SLD plans and data submitted to the Census Bureau.

Reference Maps
Where are 2012 (current) vintage state legislative districts?  The SLD GIS project provides the best way to view/examine SLD boundaries of interest.  These resources provide the best capability to view simple SLD boundaries possibly in combination with other types of geography and labeling.

Texas 2012 SLD-House — statewide view
Zoom- to Texas using national scope shapefile; query placed on layer to view only Texas SLD-House with SLD labels.

Texas 2012 SLD-House — zoom into Austin area
The next view shows a zoom into the Austin area (see at pointer in above graphic).  It is easy to see the boundary of SLD-House 048.  Further zoom-in could provide more detail.

State Legislative District Demographic Data & Vintages
While Census 2010 demographic data and American Community Survey (ACS) data are available for the 2010 vintage SLDs,  the Census Bureau has not developed Census 2010 data or  ACS data for 2012 (current) vintage SLDs. There are no Census 2010 or ACS “richer-demographics” tabulated for 2012 (current) vintage SLDs available from Census.

To develop Census 2010 demographics for  2012 (current) vintage SLDs, ProximityOne integrated 2012 SLD codes from state provided census block equivalency files into the Census 2010 Summary File 1 block level header/geography records.  Using the additional 2012 SLD code, population and housing using data have been developed for  2012 (current) vintage SLDs.

Examine State Legislative Districts of Interest
Members of the ProximityOne User Group may download and use the national scope SLD GIS project with CV XE GISJoin now; no fee.  Add other geographic layers.  View SLDs in context of 113th Congressional Districts.  View different SLD vintages.  Create different zoom and labeled views. Integrate your own data.

Neighborhood Patterns of Economic Prosperity by Congressional District

While congressional districts are similar in that the total population of the district is roughly the same, the similarity often stops there.  The 2012 median household income among the 113th Congressional Districts ranged from $23,314 to $108,068.  The educational attainment among the 113th Congressional Districts ranged from 52% to 96.1% high school graduates. Use this interactive table to view/rank/compare districts based on selected 2012 demographic-economic measures.  Use interactive tables accessible on this page to rank/compare congressional districts based on a broader set of data. Access much more detailed 2012 demographic-economic data in the form of structured profiles using the CV XE APIGateway.  Compare one congressional district to others in a comparative analysis spreadsheet structure.

These measures tell us a great deal about the characteristics of the population and housing for the entire area covered by each district.  But how do patterns of economic prosperity, among other such measures, vary by neighborhood across any specific congressional district? The graphic presented below shows a thematic map of median household income by census tract.  New York Congressional District 12 is shown with the  bold black boundary.  See this larger view that shows the legend and pattern/color by median household income interval/range.

New York 12th Congressional District

New York 12th Congressional District

View this gallery section to see similar thematic maps for this and all New York 113th Congressional Districts.  These maps provide visually-based insights into demographic-economic patterns across each district.  Congresspeople, their staffs and stakeholders can develop a better understanding of diversity and needs within a district using GIS tools, relevant data and methods such as shown here.

Neighborhood Geography
Census tracts are an imperfect geography to provide a 100% equivalent to a neighborhood area.  But they are the closest geographic equivalent to a neighborhood which are available wall-to-wall across the U.S.  It might be argued that block group level geography would be better as block groups are subdivisions of census tracts.

Economic Prosperity Measures
Similarly, median household income (MHI) is an imperfect measure of economic prosperity.  But, if we were going to pick just one measure, MHI might be the best choice.  MHI and related measures of economic prosperity are updated annually at the census tract and block group levels by the American Community Survey (ACS) 5-year estimates.  Soon, the growing set of these data will evolve into a time-series and also enable analyzing these same geographies and MHI patterns as trends over time.

Visual Analysis of Each 113th Congressional District
The 113th Congressional Districts Analytical Gallery provides thematic map views of neighborhood patterns of economic prosperity for each/every congressional district.  Click on the link above and navigate to your districts of interest.  See how patterns across the district are the same or dissimilar — and how and where they differ.

An updated (one year more recent) median household income estimate by census tract and block group will be available in December 2013.  We will re-visit this topic in early 2014.