Open Airbnb datasets for Swansea, UK

Swansea, UK

Total listings: 924

Last Updated: 2025-06-25

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How many Airbnbs are there in Swansea?

There are 752 entire homes listed across Airbnb in Swansea and the surrounding area, with 144 private bedrooms and 9 serviced apartments. The neighbourhood with the most listings is , with 104 entire homes costing an average of £120 per night. The second most populated neighbourhood for whole rental properties is with 97 listings, followed by with 75 entire homes.

Entire Homes

752

Private Rooms

144

Serviced Apartments

Shared Rooms

Bed Homes

217

Bed Homes

275

Bed Homes

148

Bed Homes

Basic Pricing

Average Price per night per Bedrooms

for entire homes and serviced apartments

Average Price per night per Bedrooms

for entire homes and serviced apartments

Average Price per night per Max. Guests

for entire homes and serviced apartments

Average Price per Review Score

Average Price for Other Property Types

Campervan/Motorhome: £79

Holiday park: £160

Airbnbs charging cleaning fee

53.2%

Average Airbnb cleaning fee

£55.25

Average Price for Private Rooms

£49.16

Average Price for Serviced Apartments

£214.00

Airbnbs charging cleaning fee

53.2%

Avg. Airbnb cleaning fee

£55.25

Avg. Price for Private Rooms

£49.16

Avg. Price for Serviced Apartments

£214.00

Basic pricing is taken from the date of data collection for 1 guest. This is the average price over the first 5 consecutive days the listing is available for, within the next two months. Where these conditions are not satisfied, no pricing data is recorded. Full weekly pricing and daily availability data is available on request. All prices are in GBP.

Doorstep Analytics offers comprehensive holiday rental datasets, including detailed pricing, availability, and estimated income. You can access the complete dataset directly or request a tailored analytics report to address specific questions and insights.

Reviews

Rating per Airbnb Listing

Number of Reviews on each Listing

Airbnb review scores in Swansea (4.69) are significantly below the average Airbnb review score across all locations (4.754) Over half of Airbnb listings use self-check in, with lockboxes, keypads or similar. This implies the property is in regular use as an Airbnb listing, or is run as part of a professional business. 13% of hosts have more than one listing in Swansea, also suggesting they are a business.

Hosts

Hosts listed as superhosts

31.5%

Hosts with more than 1 listing

12.6%

59%

of listings welcome guests with lockboxes or other self check-in methods

Hosts with Most Listings

Host Name	No. of Listings	Avg. Review Score
Home From Home	64	4.47
KG Short Stay	48	4.19
Nicola	31	4.4
James	29	4.51
Eve	19	4.26
Matthew	17	4.68
Cottages,Com	17	4.77
Wales Cottage Holidays	16	4.32
Joseph	10	4.64
Bay	8	4.95
Kinga	7	4.49
Swansea	7	4.83
Joan	7	4.74
Eve Joan	6	4.69

59%

of listings welcome guests with lockboxes or other self check-in methods

Neighbourhoods

	Total	All Entire Homes		1-Bed Homes		2-Bed Homes		3-Bed Homes		Private Rooms		Reviews
	Count	Count	Avg. Price	Count	Avg. Price	Count	Avg. Price	Count	Avg. Price	Count	Avg. Price	Avg. Score
Maritime Quarter	127	104	£120	47	£91	43	£134	4	£173	16	£57	4.62
The Mumbles	107	97	£142	15	£102	55	£121	16	£203	6	£80	4.78
Mumbles	79	75	£168	9	£80	36	£145	20	£181	3	£100	4.82
Newton	65	61	£144	20	£110	24	£119	11	£183	2	£80	4.85
Sketty	60	42	£140	9	£81	6	£117	16	£158	18	£41	4.74
Townhill	48	36	£121	18	£97	6	£104	3	£161	12	£49	4.62
West Cross	44	38	£150	10	£91	10	£141	6	£255	6	£50	4.84
Brynmill	37	18	£110	3	£62	7	£119	4	£104	18	£31	4.66
Saint Thomas	34	27	£92	14	£78	7	£94	2	£142	7	£35	4.54
Bishopston	27	26	£117	18	£111	3	£135	5	£129	0	-	4.82
Uplands	26	15	£183	3	£95	3	£172	4	£158	11	£39	4.77
Plasmarl	26	24	£89	7	£51	6	£112	4	£143	2	£33	4.30
Manselton	18	15	£124	1	£56	5	£140	6	£111	3	£47	4.72
Morriston	18	15	£81	2	£48	6	£78	7	£90	3	£30	4.53
Port Tennant	18	13	£129	0	-	2	£80	8	£110	5	£31	4.67

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Neighbourhoods are provided by user input in Airbnb. Where this data is not provided on Airbnb, a kNN machine learning model categorises listings into their most likely neighbourhood. Translated city names and names of large regions are removed where possible.