This is a small community in a single neighborhood.
As throughout the site, some neighborhood-level data are reserved for subscribers.
What do we mean by a neighborhood?
NeighborhoodScout® uses the official government designation for neighborhoods - the census tract.
Census tracts are small, relatively permanent subdivisions of a county that are defined by the U.S. Census Bureau in conjunction with local authorities all across the country to define real neighborhoods that are bounded to contain areas with homogeneous population characteristics (including economic status, lifestyle, and living conditions). Census tracts usually have 4,000 persons, but can range between 1,500 and 8,000 persons. This is the most fine-grained area for which detailed information is made available from the government, to protect the individual privacy of each of us. Because census tracts are based on population, they vary in size depending on the density of settlement. In urban areas, they are small, and in rural areas they can cover an entire small town or even a few small towns in very rural areas.
Since census tracts are subdivisions of a county, we did a spatial overlay of the census tracts onto city and town boundaries using a geographic information system to properly assign each census tract to its appropriate city or town. Then we named each census tract to the local colloquially recognized neighborhood name for that spot (e.g., Boston, MA (Dorchester). If there was not a name available, we named the census tract by the largest street intersection in the census tract (e.g., Worcester, MA (Lincoln St/Plantation St)
Why we don't use Zip Codes as neighborhoods
Zip codes were developed by the Postal Service for the purpose of delivering mail, but were never intended to define coherent neighborhoods. In addition, Zip Codes can have as many as 10 distinctly different census tracts contained within them. When distinct census tracts are blended together in a single Zip Code, the data reflects their average conditions and often gives a false sense of the area. The result is that potentially great matching neighborhoods can be missed, and erroneous matches can also be produced and delivered to you.
Using census tracts makes great matches possible, and helps people find the areas that are best for them and their families. Because we are committed to providing the highest possible quality and finding the neighborhoods that best meet your criteria, we use census tracts. And, as always, we show you the actual street map of the neighborhood so you know exactly where your best matching neighborhood is located.
What is a Condition Alert?
A condition alert is a condition in the neighborhood that triggers an alert. NeighborhoodScout contains condition alerts to highlight conditions that are extreme, whether good or bad. This helps answer crucial questions about the state of the neighborhood being evaluated, such as:
What are the risks of violent crime here?
Is the risk of home break-ins or other property crimes increasing?
Does real estate here hold its value?
Are the trends in local vacancies or unemployment concerning?
...and dozens more.
Information at a glance that you need to know to invest, appraise or finance a property.
Evans City is a very small borough located in the state of Pennsylvania. With a population of 850 people and just one neighborhood, Evans City is the 686th largest community in Pennsylvania.
Evans City real estate is some of the most expensive in Pennsylvania, although Evans City house values don't compare to the most expensive real estate in the U.S.
Occupations and Workforce
Unlike some boroughs where white-collar or blue-collar occupations dominate the local economy, Evans City is neither predominantly one nor the other. Instead, it has a mixed workforce of both white- and blue-collar jobs. Overall, Evans City is a borough of sales and office workers, professionals, and service providers. There are especially a lot of people living in Evans City who work in office and administrative support (11.47%), sales jobs (10.07%), and management occupations (8.86%).
One interesting thing about the economy is that relatively large numbers of people worked from their home: 11.12% of the workforce. While this number may seem small overall, as a fraction of the total workforce this is high compared to the rest of the county. These workers are often telecommuters who work in knowledge-based, white-collar professions. For example, Silicon Valley has large numbers of people who telecommute. Other at-home workers may be self-employed people who operate small businesses out of their homes.
Setting & Lifestyle
Being a small borough, Evans City does not have a public transit system used by locals to get to and from work.
Demographics
In terms of college education, Evans City is somewhat better educated than the 21.84% who have a 4-year degree or higher in the typical US community: 27.55% of adults 25 and older in the borough have at least a bachelor's degree.
The per capita income in Evans City in 2018 was $36,243, which is upper middle income relative to Pennsylvania and the nation. This equates to an annual income of $144,972 for a family of four. However, Evans City contains both very wealthy and poor people as well.
The people who call Evans City home describe themselves as belonging to a variety of racial and ethnic groups. The greatest number of Evans City residents report their race to be White, followed by Asian. Important ancestries of people in Evans City include German, Irish, Italian, English, and Polish.
The most common language spoken in Evans City is English. Other important languages spoken here include Polish and Spanish.
Notable & Unique Neighborhood Characteristics
The way a neighborhood looks and feels when you walk or drive around it, from its setting, its buildings, and its flavor, can make all the difference. This neighborhood has some really cool things about the way it looks and feels as revealed by NeighborhoodScout's exclusive research. This might include anything from the housing stock to the types of households living here to how people get around.
Diversity
Did you know that the neighborhood has more Hungarian and German ancestry people living in it than nearly any neighborhood in America? It's true! In fact, 3.4% of this neighborhood's residents have Hungarian ancestry and 41.9% have German ancestry.
The Neighbors
How wealthy a neighborhood is, from very wealthy, to middle income, to low income is very formative with regard to the personality and character of a neighborhood. Equally important is the rate of people, particularly children, who live below the federal poverty line. In some wealthy gated communities, the areas immediately surrounding can have high rates of childhood poverty, which indicates other social issues. NeighborhoodScout's analysis reveals both aspects of income and poverty for this neighborhood.
The neighbors in the neighborhood in Evans City are upper-middle income, making it an above average income neighborhood. NeighborhoodScout's exclusive analysis reveals that this neighborhood has a higher income than 62.1% of the neighborhoods in America. In addition, 2.6% of the children seventeen and under living in this neighborhood are living below the federal poverty line, which is a lower rate of childhood poverty than is found in 72.9% of America's neighborhoods.
A neighborhood is far different if it is dominated by enlisted military personnel rather than people who earn their living by farming. It is also different if most of the neighbors are clerical support or managers. What is wonderful is the sheer diversity of neighborhoods, allowing you to find the type that fits your lifestyle and aspirations.
In the neighborhood, 48.6% of the working population is employed in executive, management, and professional occupations. The second most important occupational group in this neighborhood is manufacturing and laborer occupations, with 21.5% of the residents employed. Other residents here are employed in sales and service jobs, from major sales accounts, to working in fast food restaurants (15.2%), and 14.2% in clerical, assistant, and tech support occupations.
Languages
The most common language spoken in the neighborhood is English, spoken by 98.4% of households.
Ethnicity / Ancestry
Culture is shared learned behavior. We learn it from our parents, their parents, our houses of worship, and much of our culture – our learned behavior – comes from our ancestors. That is why ancestry and ethnicity can be so interesting and important to understand: places with concentrations of people of one or more ancestries often express those shared learned behaviors and this gives each neighborhood its own culture. Even different neighborhoods in the same city can have drastically different cultures.
In the neighborhood in Evans City, PA, residents most commonly identify their ethnicity or ancestry as German (41.9%). There are also a number of people of Irish ancestry (19.3%), and residents who report Polish roots (11.5%), and some of the residents are also of English ancestry (8.8%), along with some Italian ancestry residents (8.5%), among others.
Getting to Work
Even if your neighborhood is walkable, you may still have to drive to your place of work. Some neighborhoods are located where many can get to work in just a few minutes, while others are located such that most residents have a long and arduous commute. The greatest number of commuters in neighborhood spend between 15 and 30 minutes commuting one-way to work (48.1% of working residents), which is shorter than the time spent commuting to work for most Americans.
Here most residents (73.5%) drive alone in a private automobile to get to work. In addition, quite a number also carpool with coworkers, friends, or neighbors to get to work (8.0%) . In a neighborhood like this, as in most of the nation, many residents find owning a car useful for getting to work.
SCOUT’s patented match algorithm identifies the most similar neighborhoods to a subject location, and quantifies the similarity to the subject location. This allows analysts to identify the most similar neighborhoods in a local market area for appraisals, investments, and research.
The algorithm uses 273 neighborhood conditions, identifies the dominant dimensions underlying the conditions and calculates the similarity. This captures the true culture and character of locations, economic conditions, and trends.
The closer to 100% means the locations are nearly identical. 80% is a very good, but not excellent match, and so forth.
