Rental market snapshot for Ellenton, Florida

Ellenton, Florida Rental Property Market Overview

The average rent for an apartment in Ellenton is $2,325. The cost of rent varies depending on several factors, including location, size, and quality.

The average rent has decreased by -1.8% over the past year.

Ellenton is a small town in Florida with a population of about 3,000 people. It is located in Manatee County, on the Gulf Coast, about 30 miles south of Tampa. The town is known for its antique shops and its annual Ellenton Ice Festival.

Last Updated December 23, 2022

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Average monthly rent graph in Ellenton Florida | Cost of Living

  • The most expensive ZIP Code in Ellenton is 34222 with an average price of $2,540
  • The cheapest ZIP Code in Ellenton is 34222 with an average price of $2,250

Ellenton ZIP Codes with the highest, most expensive rent

#zip codeaverage rent
134222$2,540
234222$2,469

Live near Ellenton, Florida's Top Sights and Attractions

Gamble Plantation Historic State Park is a former sugar plantation in Ellenton, Florida. The plantation was built in the early 1800s and was one of the largest sugar plantations in the United States. The plantation is now a museum and is open to the public for tours.

Colony Cove is a 55+ retirement community in Ellenton, Florida. It is located on the Manatee River, and features amenities such as a clubhouse, swimming pool, and shuffleboard courts.

Ellenton, Florida area median rent change by ZIP Code map

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How does Ellenton compare to other cities in Florida ?

citymedian price
St Petersburg$2,349
Hollywood$2,839
Lithia$2,340
Sun City Center$2,315
Windermere$2,669
Land O Lakes$2,195
North Lauderdale$2,029
Boynton Beach$2,396
Coconut Creek$2,733
Greenacres$2,420

Average household income in Ellenton area graph - US Census

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The median household income in Ellenton in 2021 was $58,349. This represents a 51.0% change from 2011 when the median was $38,640.

#categorypercent
0Less than $10,0000.8%
1$10,000 to $14,9993.9%
2$15,000 to $19,9993.9%
3$20,000 to $24,9993.7%
4$25,000 to $29,9994.0%
5$30,000 to $34,99910.9%
6$35,000 to $39,9998.5%
7$40,000 to $44,9993.7%
8$45,000 to $49,9991.1%
9$50,000 to $59,99919.0%
10$60,000 to $74,99919.8%
11$75,000 to $99,9993.3%
12$100,000 to $124,9995.0%
13$125,000 to $149,9996.4%
14$150,000 to $199,9994.8%
15$200,000 or more1.2%

Frequently asked questions

Our data is best categorized as "alternative data", which is a burgeoning sector. Through partnerships and direct feeds, we extract key factual elements that are publicly available within rental listings on internet listing sites and property websites. Once aggregated, we mine through the data to parse out relevant insights and calculate important metrics, benchmarks, and other KPIs. Each week, our system sifts through millions of listing observations and other pockets of market information to deliver the most comprehensive picture of rental housing available.

This is a metric that we try not to overthink. Simply, we take each unique listing observation within a geographic boundary and calculate a simple average. Of course, we're careful to filter for duplicates and other listings that aren't reflective of the market.

Yes, but please attribute us accordingly.

Yes. We can deliver bulk raw data in various formats. Please contact us to discuss - [email protected]

While some of our data is refreshed daily and other data comes in weekly, the bulk of it comes in on a biweekly basis.

Our coverage is nationwide! In our platform, we have data points for every ZIP code and neighborhood boundary in the country.

Every rental housing unit is differentiated by attributes such as its location, square footage, and amenity composition. Thanks to machine learning and natural language processing technologies we deploy, we're able to deconstruct our rental listing data points and identify key amenities for each listing. With this information, we're able to give signals around how certain amenities drive rental pricing value in certain areas.

Well, we think so! At the highest level, our process is simple. Listings data is ingested, cleaned (de-duplicated. etc.), analyzed for insights, and then presented to our users.
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