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.
Cobleton / Shannon Green median real estate price is $165,158, which is less expensive than 69.8% of Ohio neighborhoods and 85.3% of all U.S. neighborhoods.
The average rental price in Cobleton / Shannon Green is currently $1,826, based on NeighborhoodScout's exclusive analysis. The average rental cost in this neighborhood is higher than 79.1% of the neighborhoods in Ohio.
Cobleton / Shannon Green is a rural neighborhood (based on population density) located in Columbus, Ohio.
Cobleton / Shannon Green real estate is primarily made up of small (studio to two bedroom) to medium sized (three or four bedroom) apartment complexes/high-rise apartments and single-family homes. Most of the residential real estate is occupied by a mixture of owners and renters. Many of the residences in the Cobleton / Shannon Green neighborhood are established but not old, having been built between 1970 and 1999. A number of residences were also built between 2000 and the present.
Home and apartment vacancy rates are 7.7% in Cobleton / Shannon Green. NeighborhoodScout analysis shows that this rate is lower than 49.7% of the neighborhoods in the nation, approximately near the middle range for vacancies.
Notable & Unique Neighborhood Characteristics
Many things matter about a neighborhood, but the first thing most people notice is the way a neighborhood looks and its particular character. For example, one might notice whether the buildings all date from a certain time period or whether shop signs are in multiple languages. This particular neighborhood in Columbus, the Cobleton / Shannon Green neighborhood, has some outstanding things about the way it looks and its way of life that are worth highlighting.
People
Divorcees may find friendship and understanding in this neighborhood, as 39.0% of its residents are divorced. NeighborhoodScout's exclusive analysis found that this divorce rate is higher than in 100.0% of the neighborhoods in America.
In addition, of note, 71.6% of the children in this area live in poverty; an extraordinarily high percentage compared to other neighborhoods in the nation. In a nation where approximately one in four children grows up in poverty, this neighborhood stands out for the depth of the problem manifested here.
Occupations
The government often provides some of the more stable jobs in the economy. From local, to state, to federal government workers, the government can also be a major employer. What NeighborhoodScout's analysis revealed, is that the Cobleton / Shannon Green neighborhood in particular stands out when compared nationally for the proportion of its working residents who are employed by the government. At 13.7% of its workforce, this neighborhood has a greater concentration of government workers than 96.0% of U.S. neighborhoods.
Diversity
Significantly, 3.0% of its residents five years old and above primarily speak African languages at home. While this may seem like a small percentage, it is higher than 97.0% of the neighborhoods in America.
The Neighbors
There are two complementary measures for understanding the income of a neighborhood's residents: the average and the extremes. While a neighborhood may be relatively wealthy overall, it is equally important to understand the rate of people - particularly children - who are living at or below the federal poverty line, which is extremely low income. Some neighborhoods with a lower average income may actually have a lower childhood poverty rate than another with a higher average income, and this helps us understand the conditions and character of a neighborhood.
The neighbors in the Cobleton / Shannon Green neighborhood in Columbus are lower-middle income, making it a below average income neighborhood. NeighborhoodScout's research shows that this neighborhood has an income lower than 74.7% of U.S. neighborhoods. With 71.6% of the children here below the federal poverty line, this neighborhood has a higher rate of childhood poverty than 98.7% of U.S. neighborhoods.
The old saying "you are what you eat" is true. But it is also true that you are what you do for a living. The types of occupations your neighbors have shape their character, and together as a group, their collective occupations shape the culture of a place.
In the Cobleton / Shannon Green neighborhood, 38.9% 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 27.5% of the residents employed. Other residents here are employed in sales and service jobs, from major sales accounts, to working in fast food restaurants (17.2%), and 16.4% in clerical, assistant, and tech support occupations.
Languages
The languages spoken by people in this neighborhood are diverse. These are tabulated as the languages people preferentially speak when they are at home with their families. The most common language spoken in the Cobleton / Shannon Green neighborhood is English, spoken by 98.5% of households. Other important languages spoken here include Italian and African languages.
Ethnicity / Ancestry
Boston's Beacon Hill blue-blood streets, Brooklyn's Orthodox Jewish enclaves, Los Angeles' Persian neighborhoods. Each has its own culture derived primarily from the ancestries and culture of the residents who call these neighborhoods home. Likewise, each neighborhood in America has its own culture – some more unique than others – based on lifestyle, occupations, the types of households – and importantly – on the ethnicities and ancestries of the people who live in the neighborhood. Understanding where people came from, who their grandparents or great-grandparents were, can help you understand how a neighborhood is today.
In the Cobleton / Shannon Green neighborhood in Columbus, OH, residents most commonly identify their ethnicity or ancestry as German (18.0%). There are also a number of people of English ancestry (12.4%), and residents who report Irish roots (11.7%), and some of the residents are also of Italian ancestry (5.0%), along with some Polish ancestry residents (2.1%), among others.
Getting to Work
How you get to work – car, bus, train or other means – and how much of your day it takes to do so is a large quality of life and financial issue. Especially with gasoline prices rising and expected to continue doing so, the length and means of one's commute can be a financial burden. Some neighborhoods are physically located so that many residents have to drive in their own car, others are set up so many walk to work, or can take a train, bus, or bike. The greatest number of commuters in Cobleton / Shannon Green neighborhood spend between 15 and 30 minutes commuting one-way to work (42.3% of working residents), which is shorter than the time spent commuting to work for most Americans.
Here most residents (79.9%) drive alone in a private automobile to get to work. 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.
