Frequently Asked Questions
Last updated on January 23, 2025.
Where does the data come from?
The data comes from the U.S. Census Bureau, specifically from data.census.gov, which provides access to a wide range of datasets, including the American Community Survey (ACS), the Decennial Census, the Economic Census, and other key surveys. The ACS, for instance, is an ongoing survey that provides detailed demographic, social, economic, and housing statistics every year. The Decennial Census, conducted every ten years, provides a comprehensive count of the population and is used to allocate congressional seats and distribute federal funding. By pulling data from these authoritative sources, data.census.gov provides reliable and up-to-date information that can be used for community planning, business analysis, and research purposes.
What is a ZCTA, and how is it different from a zip code?
ZCTAs, or ZIP Code Tabulation Areas, are generalized representations of U.S. Postal Service ZIP codes created by the Census Bureau to help with data collection and statistical analysis. Unlike USPS ZIP codes, which are designed for mail delivery and can change frequently, ZCTAs are used to approximate ZIP code areas for census purposes and are more stable over time. ZIP codes can overlap or have complex boundaries, especially in areas where postal routes cross different neighborhoods or administrative boundaries. ZCTAs simplify these into distinct areas, often aligning better with census tracts or blocks, which makes them ideal for demographic and economic analysis. This means ZCTAs are often more suitable for use in research, public planning, and analysis compared to traditional ZIP codes, which are subject to frequent changes by the USPS.
How many zips/ZCTAs are there in the Census’ dataset?
There are approximately 33,000 ZCTAs in the Census dataset. This number may vary slightly over time due to changes and updates, such as the creation of new residential areas or adjustments to existing ZIP codes by the USPS. ZCTAs are designed to cover most populated areas of the country, which means that each ZCTA generally represents a geographic area where people live, work, and receive services. Unlike ZIP codes, which can include specialized delivery routes or cover areas without residential addresses, ZCTAs are structured to ensure a broad and representative coverage of populated regions, making them particularly useful for demographic analysis, public planning, and resource allocation.
How do I know if this data is any good?
The data provided by the Census Bureau is widely regarded as highly reliable because it is collected using robust, well-established methodologies, including surveys that reach a large cross-section of the U.S. population. The American Community Survey (ACS) and the Decennial Census employ rigorous quality control measures to ensure the accuracy and completeness of the data. For instance, ACS uses statistical sampling to gather data from millions of households, and the Census Bureau takes additional steps to minimize errors and ensure representativeness. However, like any survey data, there are inherent margins of error, especially in smaller geographic areas where fewer responses are available. These margins of error are included with the data to provide transparency and help users assess the reliability of the estimates. Users should consider these margins, particularly when analyzing small populations or less common variables, to make informed conclusions.
Why do you recommend using median income instead of average income?
Median income is often recommended over average income when analyzing household or individual earnings because it provides a more accurate representation of what a typical household earns.
The median is the middle value in a list of incomes arranged from lowest to highest, meaning that half of the households earn more than the median and half earn less. This measure is less affected by extremely high or low values, which can skew the results and give a misleading impression of the economic situation.
For instance, a few very high-income households can significantly raise the average income, making it seem that the overall population is wealthier than it actually is. In contrast, the median provides a better picture of the “typical” income, helping policymakers, businesses, and researchers understand the economic reality faced by the majority of households.
What does “(in 2022 inflation-adjusted dollars)” mean?
In US Census data, the phrase “(in 2022 inflation-adjusted dollars)” means that the reported monetary values have been converted into equivalent purchasing power for the year 2022. This adjustment accounts for inflation, which is the rise in prices of goods and services over time. By presenting the data in inflation-adjusted terms, it becomes possible to compare values from different years on an equal footing, as though all the dollars had the same purchasing power as in 2022.
For example: If a household’s income was reported as $50,000 in 2015, and the same household’s income is presented as $60,000 (in 2022 inflation-adjusted dollars), it means that the $50,000 from 2015 would have the same purchasing power as $60,000 in 2022, considering inflation.
This adjustment helps provide a clearer picture of real economic trends, eliminating distortions caused by changes in the value of money over time.
Can you help me sort my data by counties, cities or zips/ZCTAs?
Yes, data from the Census can often be sorted by different geographic levels, including counties, cities, and ZCTAs, depending on the granularity you need for your analysis. This flexibility allows for targeted insights, such as comparing different regions or analyzing trends within specific areas. For example, you might want to compare income levels between cities or evaluate housing trends within specific counties. Tools like data.census.gov allow users to filter and sort data by these geographic boundaries, and software like Excel, R, or GIS (Geographic Information System) tools can also be used to manipulate and visualize data. If you need help sorting or organizing the data, consider using these tools, or look for support from data analysis services that are familiar with Census data.
How often are the reports and website updated with new data?
All of our data is sourced from the U.S. Census Bureau’s American Community Survey (ACS) and Decennial Census.
The American Community Survey (ACS) is a vital program of the U.S. Census Bureau that provides detailed demographic, social, economic, and housing information about the U.S. population. It is updated on two primary schedules:
1-Year Estimates
- What It Covers: The 1-year estimates are based on data collected over 12 months and are released for geographic areas with populations of 65,000 or more.
- When They Are Released: Typically, the 1-year estimates are released every September of the following year. For example, data collected in 2023 would generally be released in September 2024.
- Use Cases: These estimates are used for timely analysis of larger geographic areas, allowing users to see more current trends in the data.
5-Year Estimates
- What It Covers: The 5-year estimates aggregate data collected over a five-year period. They provide information for all geographic areas, regardless of population size, including small towns, neighborhoods, and rural areas.
- When They Are Released: The 5-year estimates are typically released every December of the following year. For example, the 2018-2022 ACS 5-year estimates would be released in December 2023.
- Use Cases: These estimates provide more reliable data for smaller areas and detailed population subgroups, as they are based on a larger sample size.
Key Differences in Timing and Usage | Feature | 1-Year Estimates | 5-Year Estimates | |——————–|—————————————|————————————-| | Population Threshold | Areas with populations of 65,000+ | All areas (no population limit) | | Data Period | 12 months | 60 months | | Release Month | September | December | | Reliability | More current but less precise | More precise but less current |
Update Schedule
- 1-Year Estimates: Released every September.
- 5-Year Estimates: Released every December.
This schedule allows for the ACS data to remain both timely (through 1-year estimates) and comprehensive (through 5-year estimates).
You can also check the U.S. Census Bureau’s website for more information on the ACS. Its data release schedule can be found here: https://www.census.gov/programs-surveys/acs/data/data-release-schedule.html.
What is the best way to analyze historical trends in the ACS data?
Analyzing historical trends in the American Community Survey (ACS) data can be a complex task due to the different types of estimates available. Understanding the nuances between the 1-year and 5-year estimates is crucial for selecting the right data for your analysis. Each type of estimate serves different purposes and is suited for different kinds of analyses, depending on the geographic area and the level of detail required.
Choosing Between ACS 1-Year and 5-Year Data
1-Year Estimates
- Use for recent trends in large areas (populations of 65,000+).
- Reflect short-term changes but have higher margins of error.
- Best for timeliness and large-scale analyses.
5-Year Estimates
- Use for small areas or detailed analysis (all geographies).
- Offer greater precision due to larger sample sizes.
- Reflect long-term trends but obscure year-specific changes.
Criterion | 1-Year Estimates | 5-Year Estimates |
---|---|---|
Population Size | Large areas (65,000+) | All areas, regardless of size |
Time Sensitivity | Recent, short-term trends | Long-term trends |
Data Precision | Less precise | More precise |
Analysis Scale | Regional or metropolitan | Localized or small subgroups |
Handling Overlap in 5-Year Data
- Compare Non-Overlapping Periods: Use intervals like 2010–2014 vs. 2015–2019 for clear trends.
- Acknowledge Averaging Effects: Consecutive datasets (e.g., 2017–2021 vs. 2018–2022) share four years of data, muting changes.
- Avoid treating overlapping datasets as independent; focus on broader trends.
Is there data available for countries outside of the US and Canada?
Currently, our data focus is primarily on the United States. The datasets available through data.census.gov are collected by the U.S. Census Bureau and are therefore centered on U.S. demographics, economics, and housing. There is some limited information for Canada, particularly in cross-border studies or specialized datasets, but comprehensive data for other countries is not included. If you need international data, you might want to explore other sources, such as the United Nations, the World Bank, or national statistical agencies of the countries of interest, which provide similar types of demographic and economic data.
Why is there some data missing?
Data may be missing for several reasons, and understanding these reasons can help users better interpret the available information. One common reason is non-response from survey participants, which occurs when individuals or households do not provide answers to some or all of the questions. In order to protect privacy, the Census Bureau also uses data suppression techniques, which means that data may be withheld in certain areas or for certain variables to avoid identifying specific individuals or households. Additionally, the Census Bureau may not collect specific types of data in all areas, especially in smaller geographic regions where collecting detailed data is not statistically feasible. Margins of error and data reliability are also factors; if the sample size is too small or the data is considered unreliable, it may be excluded or marked as missing.