About VivirDonde
Your smart guide to finding a neighborhood in Madrid
What is VivirDonde?
VivirDonde is a free tool that helps you find the best neighborhood in Madrid based on your budget and personal preferences. We analyze official open data to score each area of the city across dimensions such as public transport, green spaces, safety and nightlife, and combine them with real rental prices to offer personalized recommendations. No registration, no cost, no hassle.
Where does the data come from?
Every score comes from public open data, downloaded from its official source:
- ·Madrid City Council and Madrid Region — population register by district, Municipal Police activity and microdata from the Quality of Life Survey (datos.madrid.es); official registers of schools, pharmacies and health centres (datos.comunidad.madrid).
- ·CRTM, Renfe, Ministry of the Interior, INE and Eurostat — GTFS timetables for Metro, light rail, EMT, urban and interurban buses (CRTM) and for Cercanías commuter rail (Renfe); the Crime Balance by municipality; official population figures; and the 1 km² population grid from the 2021 Census, which tells us where people actually live within each area.
- ·OpenStreetMap and Overture Maps — parks, residential land, shops, bars and services. OpenStreetMap is very complete in Madrid city but patchy in some municipalities, so we merge it with Overture Maps (open data from Meta, Microsoft and Foursquare) without counting the same place twice.
- ·Idealista — public rental price report by district, neighbourhood and municipality. No data from individual listings is used.
Prices are updated every month from Idealista's public report. Scores are recalculated when the sources publish new data: transport timetables and OpenStreetMap continuously; Overture Maps a couple of times a year; crime, population register and the city survey every year; the census every ten.
Methodology
Every score answers the same question: what does someone living in this area have within walking distance? Inside the real boundary of each area we place a point every 100 metres wherever there is housing, weight it by the people who live there according to the 2021 Census, measure from each point and take the average. That way the El Pardo woodland and the Barajas runways don't count, and a block of flats weighs more than a block of detached houses: the score is that of the average resident. The scale is absolute: a 10 means the same in Chamberí as in Navalcarnero, and an area's score does not change because others do. On every area page, under each score, you can see the fact it comes from.
Public Transport
Walking distance to the nearest metro entrance or Cercanías station (counts in full up to 400 m and not at all beyond 1,200 m; light rail and the Parla tram count 60%), number of different lines within 800 m, and frequency of the buses stopping within 300 m. Weights: 55% rail access, 20% lines, 25% bus.
Green Spaces
Half for having a park of at least one hectare near home (counts in full up to 300 m, the WHO threshold, and not at all beyond 900 m) and half for the amount of green within a one-kilometre radius (30% already earns the top score). Parks, public gardens and woodland all count, including large ones such as El Retiro or Casa de Campo.
Safety
Municipalities: conventional crimes per 1,000 residents per year (Ministry of the Interior and INE); 15 or fewer is a 10 and 300 or more is a 1, on a logarithmic scale. Madrid districts: the Ministry publishes no district figures, so we start from the rate for Madrid city, assign Centro the concentration of incidents shown by Municipal Police interventions, and adjust each district by how safe its own residents say they feel in the City Council's Quality of Life Survey. Neighbourhoods and zones inherit the score of their district or municipality: no finer open data exists.
Nightlife
Bars, pubs, nightclubs and live-music venues within 500 m of home, weighted by how night-oriented they are: a nightclub counts 4, a live venue 3, a pub or cocktail bar 2 and the ordinary neighbourhood bar 0.3. A 10 is the level of Sol, Huertas or Malasaña. Cafés and restaurants do not count.
Family
Schools within walking distance and a choice of several (20%), nursery (5%), playground within 150-500 m (15%), green space (20%), health centre (5%), calm, i.e. little nightlife under your window (15%), and how many children already live in the area: from 8% to 20% of residents under 15 according to the Census (20%). Schools and health centres come from the official registers of the Madrid region.
Walkability
The “15-minute city”. 60% of the score is the walking distance to the nearest of nine needs: food shopping, pharmacy, bar or restaurant, park and public-transport stop (count in full up to 200 m and not at all beyond 600 m), and school, doctor, bank or post office, and culture or sport (from 300 to 900 m). The other 40% is variety: how many food shops, bars and restaurants, and services there are within 500 m. Pharmacies, doctors and schools come from official registers.
What we don't know. No map has every shop. We measure how much we are missing by comparing our list with the official pharmacy register: in Madrid city we locate more than 90%; in most municipalities between 60% and 90%; and in a few (Alcobendas, Tres Cantos, Navalcarnero, Arroyomolinos, Villaviciosa de Odón) less than half. Counts of bars and shops are corrected for that coverage, but in those municipalities the nightlife and walkability scores are less precise. Playgrounds come from OpenStreetMap only. Safety for neighbourhoods and zones is that of their district or municipality: no finer open data exists.
Update cadence: prices are reviewed every month; scores are recalculated with each new release from the sources.
Distance and travel time calculations
Travel times from the points you enter (work, gym, school…) to each neighborhood are calculated with OpenRouteService on the real OpenStreetMap road network, not as the crow flies. Supported profiles are walking, cycling and driving. For public transport we apply an empirical factor over driving time (Madrid ≈ 1.4×) while we integrate GTFS routes from CRTM. If the routing service is unavailable, the system falls back to a Haversine estimate with a street correction factor.
Contact
Have suggestions, found a data error or want to collaborate? Write to us at [email protected]