Rental market snapshot for Belvedere, South Carolina

Belvedere, South Carolina Rental Property Market Overview

The average rent for an apartment in Belvedere is $1,261. The cost of rent varies depending on several factors, including location, size, and quality.

The average rent has decreased by -2.6% over the past year.

Belvedere is a town in South Carolina with a population of 1,171. The town is located in Aiken County and is part of the Augusta metropolitan area.

Last Updated December 23, 2022

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Average monthly rent graph in Belvedere South Carolina | Cost of Living

  • The most expensive ZIP Code in Belvedere is 29841 with an average price of $1,455
  • The cheapest ZIP Code in Belvedere is 29841 with an average price of $1,455

Belvedere ZIP Codes with the highest, most expensive rent

#zip codeaverage rent
129841$1,455

Live near Belvedere, South Carolina's Top Sights and Attractions

Thomas Park is a small, family-friendly park located in the heart of the historic district of Belvedere, South Carolina. The park features a playground, picnic tables, and a walking trail.

Anderson Portable Buildings is a local business that specializes in the sale and rental of storage sheds, garages, and other portable buildings. They offer a wide variety of sizes and styles to choose from, and their prices are very competitive.

Hazel Street Park is a small, neighborhood park located in the historic district of Belvedere, South Carolina. The park is home to a playground, picnic pavilion, and a small pond.

Belvedere, South Carolina area median rent change by ZIP Code map

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How does Belvedere compare to other cities in South Carolina ?

citymedian price
Belton$1,450
Charleston$1,995
Cayce$1,250
Woodruff$1,799
Spartanburg$1,495
Lexington County$1,749
Lexington$1,510
Okatie$1,915
Moncks Corner$2,095

Average household income in Belvedere area graph - US Census

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The median household income in Belvedere in 2021 was $50,390. This represents a 29.6% change from 2011 when the median was $38,882.

#categorypercent
0Less than $10,0004.3%
1$10,000 to $14,9998.5%
2$15,000 to $19,9994.2%
3$20,000 to $24,99911.0%
4$25,000 to $29,9991.3%
5$30,000 to $34,9992.5%
6$35,000 to $39,9993.7%
7$40,000 to $44,99910.4%
8$45,000 to $49,9993.6%
9$50,000 to $59,9999.0%
10$60,000 to $74,99915.4%
11$75,000 to $99,99916.8%
12$100,000 to $124,9995.6%
13$125,000 to $149,9992.2%
14$150,000 to $199,9991.6%
15$200,000 or more0.0%

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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