ZIP Code Tabulation Areas (ZCTAs) are approximate area representations of U.S. Postal Service (USPS) ZIP Code service areas that the Census Bureau creates to present statistical data for each decennial census. The Census Bureau uses tabulation blocks as the basis for defining each ZCTA. Tabulation blocks are assigned to a ZCTA based on the most frequently occurring ZIP Code for the addresses contained within that block. The most frequently occurring ZIP Code also becomes the five-digit numeric code of the ZCTA. Blocks that do not contain addresses but are surrounded by a single ZCTA (enclaves) are assigned to the surrounding ZCTA. Because the Census Bureau only uses the most frequently occurring ZIP Code to assign blocks, a ZCTA may not exist for every USPS ZIP Code. Some ZIP Codes may not have a matching ZCTA because too few addresses were associated with the specific ZIP Code or the ZIP Code was not the most frequently occurring ZIP Code within any of the blocks where it exists.

Users are encouraged to refer to the U.S. Census website for more information on ZCTAs: https://www.census.gov/programs-surveys/geography/guidance/geo-areas/zctas.html
and to the U.S. Postal Service for more information on ZIP Codes: https://faq.usps.com/

Demographics, population, housing, income, education, schools, and geography for ZIP Code 56068 (Minnesota Lake, MN). Interactive charts load automatically as you scroll for improved performance.

This dataset consists of housing unit, household, and population estimates for census tracts, census block groups, Transportation Analysis Zones (TAZs), school districts, and ZIP codes in the Twin Cities Region. These data provide a more precise and timely picture of current conditions than the American Community Survey, another source of small area data that is better suited for statistics like percentages and averages than for actual counts. It may be possible to calculate estimates for other small areas upon request; contact Research@metc.state.mn.us for more information.

Demographics, population, housing, income, education, schools, and geography for ZIP Code 55959 (Minnesota City, MN). Interactive charts load automatically as you scroll for improved performance.

This feature layer provides Esri 2014/2019 demographic estimates for categories including population, age, income, race, occupation, industry and more. Data is available from country to block group level. Click the data tab for a full list of attributes. This is a ready-to-use layer for ArcGIS Pro, ArcGIS Online, configurable apps, dashboards, Insights, Story Maps, custom apps, and mobile apps. The service is intended as an archive to the retired 2014 Esri Demographics map services optimized for trending, comparison, analysis and smart mapping. For methodology information, see Esri's 2014/2019 white paper.

This dataset outlines the population vaccinated by zip code. Results are from the Minnesota Department of Health.

The American Community Survey (ACS) provides detailed demographic, social, economic, commuting and housing statistics based on continuous survey data collection. Data collected over the most recent 5 years are batched, summarized and published the following December.

These files contain summary data for Census Block Groups (CensusACSBlockGroup.xlsx), Tracts (CensusACSTract.xlsx), minor civil divisions (CensusACSMCD.xlsx), school districts (CensusACSSchoolDistrict.xlsx), and ZIP code tabulation areas (CensusACSZipCode.xlsx). No shapefiles are included, but these data files can be joined to associated shapefile datasets available elsewhere on this site. To facilitate this, the data files are also available as DBF tables and in a geodatabase.

Starting with the 2016-2020 data, tract and block group boundaries are those used in the 2020 Census. Starting with the 2017-2021 data, ZIP Code Tabulation Areas are those defined based on the 2020 Census. If you need the most recent ACS data for the tract and block group boundaries used in the 2010 Census, contact Matt Schroeder (information below).

Decennial Census 2020 includes tabulations of housing units by occupancy; households by relationship types and tenure; population by age, sex, race, and Hispanic or Latino origin; and total group quarters population. Geographies nationwide can be obtained from Census, with disaggregate geographic detail down to Block-level. Metropolitan Council is publishing files for 2020 Blocks, Block Groups, Tracts, Minor Civil Divisions (MCDs), ZIP Code Tabulation Areas (ZCTAs), and school districts. Only data files are included; they can be joined to shapefiles available elsewhere on this site.

MovieLens 1M Dataset

Overview

The MovieLens 1M dataset is a collection of movie ratings provided by the GroupLens Research Project at the University of Minnesota. This dataset contains 1,000,209 anonymous ratings of approximately 3,900 movies made by 6,040 users who joined MovieLens in 2000. It is widely used in research on recommendation systems, data mining, and machine learning.

Contents

• Ratings: 1,000,209 ratings on a scale of 1-5 stars.
• Movies: Information on 3,883 movies including titles, genres, and release dates.
• Users: Demographic information for 6,040 users including age, gender, occupation, and zip codes.

Features

• Ratings: Each rating has the following attributes:

  • UserID: A unique identifier for the user.
  • MovieID: A unique identifier for the movie.
  • Rating: The rating given by the user (1-5 stars).
  • Timestamp: The time the rating was made.

• Movies: Each movie entry includes:

  • MovieID: A unique identifier for the movie.
  • Title: The title of the movie.
  • Genres: The genres associated with the movie (e.g., Action, Comedy).

• Users: Each user entry includes:

  • UserID: A unique identifier for the user.
  • Gender: The gender of the user.
  • Age: The age of the user.
  • Occupation: The occupation of the user.
  • Zip-code: The zip-code of the user.

Use Cases

• Recommendation Systems: Ideal for building and testing collaborative filtering and content-based recommendation algorithms.
• Data Mining: Suitable for discovering patterns and insights in user behavior.
• Machine Learning: Can be used for training predictive models for various tasks such as predicting user ratings, movie popularity, etc.

Format

The dataset is provided in plain text format with tab-separated values, making it easy to load and process using various data analysis tools and programming languages.

Acknowledgements

This dataset is made available by the GroupLens Research Project at the University of Minnesota. For more information about their work, visit the GroupLens website.

Demographics, population, housing, income, education, schools, and geography for ZIP Code 55131 (Saint Paul, MN). Interactive charts load automatically as you scroll for improved performance.