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Property Data for W1U 5NN
LONDON, GREATER LONDON — House prices, crime rates & area statistics
Avg. property price
£2,750,000
Based on 1 recent sales
Most common type
Other
100% of properties
Crime level
High
3,217 crimes reported in April 2026
Top crime type
Theft From The Person
698 incidents (22% of total)
Main tenure type
Rented: Private Landlord
60% of households
Largest age group
25-29
15% of residents
Recently sold here
See all sold prices →- 26, NOTTINGHAM PLACE, LONDON, GREATER LONDON, W1U 5NN Other · Dec 2018 £2,750,000
Explore W1U 5NN
Homes for sale
What's on the market in and around this postcode.
Homes to rent
Rentals available nearby, nearest first.
House prices
Average prices, trends and a breakdown by type.
Sold prices
Every recorded Land Registry sale here.
New builds
The newest homes listed near this postcode.
Letting agents
Agencies that cover this area.
Crime Rates in W1U 5NN
There were 3,217 crimes reported in W1U 5NN during April 2026. The most common category was Theft From The Person accounting for 22% of all incidents. Other Theft was the next highest with 550 reports.
3,217
Total Crimes
Most Common
Theft From The Person (698)
| Category | Count | % | |
|---|---|---|---|
| Theft From The Person | 698 | 22% | |
| Other Theft | 550 | 17% | |
| Shoplifting | 464 | 14% | |
| Anti Social Behaviour | 389 | 12% | |
| Violent Crime | 381 | 12% | |
| Drugs | 205 | 6% | |
| Public Order | 121 | 4% | |
| Robbery | 94 | 3% | |
| Burglary | 91 | 3% | |
| Vehicle Crime | 75 | 2% | |
| Criminal Damage Arson | 60 | 2% | |
| Bicycle Theft | 49 | 2% | |
| Other | 40 | 1% |
Policing area: Marylebone — Force website ↗
Data source: police.uk open data. Covers street-level crime and policing data for England, Wales and Northern Ireland.
Area Statistics for W1U 5NN
W1U 5NN is primarily a Rented: Private Landlord area with 60% of households in this category. The most common property type is Flat (Purpose-Built) (46%). The largest age group is 25-29 making up 15% of the local population.
Housing Tenure
| Category | % | |
|---|---|---|
| Rented: Private Landlord | 60.3% | |
| Owned Outright | 17.8% | |
| Owned with Mortgage | 15.1% | |
| Rented: Other Social | 4.1% | |
| Rented: From Council | 1.4% | |
| Rented: Other | 1.4% |
Housing Types
| Category | % | |
|---|---|---|
| Flat (Purpose-Built) | 46.5% | |
| Flat (Converted) | 38.0% | |
| Terraced | 12.7% | |
| Semi-Detached | 1.4% | |
| Residence in Commercial Building | 1.4% |
Household Deprivation
| Category | % | |
|---|---|---|
| Not Deprived | 59.5% | |
| Deprived In One Dimension | 35.1% | |
| Deprived In Two Dimension | 5.4% |
Household Composition
| Category | % | |
|---|---|---|
| 1 Person Household | 50.7% | |
| Family Household | 41.3% | |
| Other Household | 8.0% |
Housing Occupancy
| Category | % | |
|---|---|---|
| One Person | 51.4% | |
| Two People | 31.1% | |
| Three People | 13.5% | |
| Four People | 4.1% |
Education & Qualifications
| Category | % | |
|---|---|---|
| Degree or above, or Similar | 71.8% | |
| HNC, HND or 2+ A Levels | 10.3% | |
| 5+ GCSEs, an A-Level or 1-2 AS Levels | 6.8% | |
| No GCSEs or Equivalent | 4.3% | |
| Other | 3.4% | |
| Apprenticeship | 2.6% | |
| 1-4 GCSEs or Equivalent | 0.9% |
Age Groups
| Category | % | |
|---|---|---|
| 25-29 | 15.0% | |
| 30-34 | 15.0% | |
| 20-24 | 9.4% | |
| 50-54 | 8.7% | |
| 45-49 | 7.1% | |
| 35-39 | 6.3% | |
| 65-69 | 6.3% | |
| 10-14 | 4.7% | |
| 15-19 | 4.7% | |
| 40-44 | 4.7% | |
| 55-59 | 3.9% | |
| 70-74 | 3.9% | |
| 60-64 | 3.1% | |
| 75-79 | 3.1% | |
| 0-4 | 1.6% | |
| 80-84 | 1.6% | |
| 5-9 | 0.8% |
Health
| Category | % | |
|---|---|---|
| Very Good | 71.7% | |
| Good | 23.6% | |
| Fair | 4.7% |
Relationship Status
| Category | % | |
|---|---|---|
| Single | 56.0% | |
| Married | 33.6% | |
| Divorced | 8.6% | |
| Widowed | 1.7% |
Gender
| Category | % | |
|---|---|---|
| Female | 51.2% | |
| Male | 48.8% |
Length of Residence
| Category | % | |
|---|---|---|
| Born in The United Kingdom | 34.6% | |
| 10+ Years | 25.2% | |
| 2-5 Years | 17.3% | |
| Less Than 2 Years | 12.6% | |
| 5-10 Years | 10.2% |
Country of Birth
| Category | % | |
|---|---|---|
| Europe | 69.3% | |
| Middle East | 15.7% | |
| The Americas | 9.4% | |
| Antarctica | 5.5% |
Ethnic Group
| Category | % | |
|---|---|---|
| Black | 77.0% | |
| White | 11.9% | |
| Asian | 5.6% | |
| Other | 4.8% | |
| Mixed | 0.8% |
Passport(s) Held
| Category | % | |
|---|---|---|
| Europe | 83.5% | |
| Middle East | 8.7% | |
| The Americas | 3.9% | |
| Antarctica | 3.1% | |
| None | 0.8% |
Religion
| Category | % | |
|---|---|---|
| Christian | 40.3% | |
| No Religion | 37.2% | |
| Not Started | 10.9% | |
| Jewish | 7.0% | |
| Other Religion | 2.3% | |
| Buddhist | 1.6% | |
| Muslim | 0.8% |
Socio-Economic Classification
| Category | % | |
|---|---|---|
| Large Employer or Higher Managerial/Professional | 37.6% | |
| Supervisory, or Lower Managerial/Administrative/Professional | 17.9% | |
| Own Account Worker/Small Employer | 15.4% | |
| Full-time Student | 14.5% | |
| Routine Occupation | 4.3% | |
| Semi-Routine Occupation | 3.4% | |
| Intermediate Occupation | 2.6% | |
| Never Worked or Long-Term Unemployed | 2.6% | |
| Lower Technical or Supervisory Occupation | 1.7% |
Occupation Group
| Category | % | |
|---|---|---|
| Professional Occupations | 32.9% | |
| Managers, Directors and Senior Officials | 29.4% | |
| Associate Professional Occupations | 15.3% | |
| Caring, Leisure and Other Service Occupations | 8.2% | |
| Administrative and Secretarial Occupations | 7.1% | |
| Skilled Trades Occupations | 3.5% | |
| Elementary Occupations | 2.4% | |
| Process, Plant and Machine Operatives | 1.2% |
Economic Activity
| Category | % | |
|---|---|---|
| Full-Time Employee | 45.7% | |
| Self Employed (No Subordinates) | 14.7% | |
| Retired | 13.8% | |
| Full-Time Student | 11.2% | |
| Self Employed (With Subordinates) | 9.5% | |
| Part-Time Employee | 2.6% | |
| Other | 1.7% | |
| Unemployed | 0.9% |
Data source: Office for National Statistics (ONS) via Nomis. Based on Census 2021 data.
All data is sourced from official UK government and public sector datasets. Pilbe aggregates this data to help you make informed property decisions.