Feature Layer. Zip Codes St. Louis County, Missouri. Link to Metadata

Demographics, population, housing, income, education, schools, and geography for ZIP Code 63110 (Saint Louis, MO). Interactive charts load automatically as you scroll for improved performance.

List of cities, zip codes and counties in Missouri

Map of Missouri Zip Codes as of 2010.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

Map of Missouri Zip Codes as of 2010.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. County subdivisions are the primary divisions of counties and their equivalent entities for the reporting of Census Bureau data. They include legally- recognized minor civil divisions (MCDs) and statistical census county divisions (CCDs), and unorganized territories. For the 2010 Census, the MCDs are the primary governmental and/or administrative divisions of counties in 29 States and Puerto Rico; Tennessee changed from having CCDs for Census 2000 to having MCDs for the 2010 Census. In MCD States where no MCD exists or is not defined, the Census Bureau creates statistical unorganized territories to complete coverage. The entire area of the United States, Puerto Rico, and the Island Areas are covered by county subdivisions. The boundaries of most legal MCDs are as of January 1, 2019, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CCDs, delineated in 20 states, are those as reported as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2010 Census.

St. Louis Brewery Data Set

St. Louis Brewery Data: Types, Locations, and Contact Details

By Throwback Thursday [source]

About this dataset

The STL Viz Brew - Brewery Data Set is a comprehensive collection of information pertaining to breweries situated in the St. Louis area. This dataset provides valuable insights into various aspects of these breweries, including their name, type (such as microbreweries, regional breweries, or brewpubs), and contact details.

For each brewery, the dataset includes their precise location information such as street address, additional address details (if applicable), city, state, county or province name, and postal code. Furthermore, latitude and longitude coordinates are also provided to pinpoint the exact geographical position of each brewery.

To facilitate easy access for users interested in exploring more about these breweries online, this dataset also features website URLs associated with each establishment. Additionally included are contact phone numbers for direct communication.

The dataset highlights tags associated with individual breweries which can offer further insights into their unique characteristics or specializations within the industry.

With continuous updates being made to ensure accuracy and timeliness of data representation within this dataset's records, users can rely on its robustness for various research purposes or decision-making processes.

In conclusion,the STL Viz Brew - Brewery Data Set serves as an extensive resource providing valuable information about breweries in the St. Louis area. It encompasses essential details such as brewery names; types; location addresses with additional address lines if relevant; city names along with state; county or province; postal codes; website URLs facilitating online exploration; contact phone numbers enabling direct communication channels; precise geolocation coordinates denoting longitude and latitude values for positioning on maps; tags offering additional insights into specific attributes or specialties associated with individual establishments.

Please note that the dataset does not include specific dates related to creation or last update timestamps

How to use the dataset

Guide: How to Use the St. Louis Brewery Dataset

Welcome to the St. Louis Brewery Dataset! This dataset contains valuable information about breweries in the St. Louis area, including their type, location, website, and contact details. Whether you are a beer enthusiast, a business owner looking for collaboration opportunities, or a data analyst looking for insights into the brewery industry in this region, this guide will help you navigate and extract useful information from this dataset.

• Understanding the Columns:

  • name: The name of the brewery.
  • brewery_type: The type of brewery (e.g., micro, regional, brewpub).
  • street: The street address of the brewery.
  • address_2: Additional address information if applicable.
  • address_3: Additional address information if applicable.
  • city: The city where the brewery is located.
  • state: The state where the brewery is located.
  • county_province: The county or province where the brewery is located.
  • postal_code: The postal code of the brewery's location.
  • website_url:The website URL of the brewery.
  • phone:The contact phone number of the brewery.

• Extracting Specific Data:

You can extract specific data based on your requirements using filters or queries in your preferred programming language or software tool.

Examples: - If you want to find all microbreweries in St. Louis: SELECT * FROM breweries WHERE city = 'St. Louis' AND brewer_type = 'micro';

• If you want to filter breweries based on their location within a specific postal code range: SELECT * FROM breweries WHERE postal_code BETWEEN 63101 AND 63110;

• If you need contact details for further communication with breweries: SELECT name,brewery_type,address_1,address_2,address_3,city,state,county_province, postal_code,website_url,phone FROM breweries;

• Analyzing and Visualizing the Data:

Once you have extracted the relevant data, you can perform various analyses or create visualizations to gain insights.

Examples: - Analyzing the distribution of different brewery types in St. Louis. - Visualizing the geographical locations of breweries on a map using latitude and longitude coordinates. - Investigating correlations between brewery types and their website presence.

• Additional Considerations:

When using ...

A dataset listing the richest zip codes in Missouri per the most current US Census data, including information on rank and average income.