#30DayMapChallenge: a day-by-day guide - BE Coding Café Knowledge Base

The #30DayMapChallenge runs every day from 1 to 30 November. Each day has a theme, and you make a map for it and share it with #30DayMapChallenge. There is no sign-up and no jury, any tool is welcome, and you do not need to do all 30: one map is a success.

The TU/e BE Coding Café edition collects everyone’s maps in one repository and a showcase site:

Starter repo: https://github.com/TUe-BE-ISBE-Coding-Cafe/30daymapchallenge-2026, with R and Python templates, the Eindhoven data used throughout this section, and instructions for AI agents
All the maps: https://tue-be-isbe-coding-cafe.github.io/30daymapchallenge-2026/
Sign-up form, for updates and a possible show-and-tell at the end of November: https://forms.cloud.microsoft/e/Qqk5yjSuVT

How to take part¶

Pick one or two days below, and put your name in signup.md in the starter repo.
Fork the repo and make your map, starting from r/day01_points.R or python/day01_points.py.
Add a folder maps/dayNN-<github-handle>/ with map.png, your code, and a README.md copied from maps/_TEMPLATE/, including the one-line AI disclosure.
Open a pull request, and post the map with #30DayMapChallenge. Your map appears on the showcase site a few minutes after the pull request is merged.

The themes¶

The Technique column suggests one way to approach the theme, not the only one. The best maps in the challenge are usually the ones that interpret a theme sideways. Always check https://30daymapchallenge.com for the official description of each day.

Week 1: the basics¶

Day	Theme	Technique	Read	Data idea
1	Points	Plot points over a boundary; emphasise a subset	Anatomy	Cafés in Eindhoven (in the starter repo)
2	Lines	Line data, or lines made from points (nearest neighbour, origin–destination)	Vector data	Cycle paths (`highway=cycleway`) from OSM; the Dommel
3	Polygons	Fill polygons by an attribute	Finding data	BAG buildings coloured by construction year
4	Clusters	Buffers and dissolve, DBSCAN, convex hulls	Vector data	Cafés, bars or shops in the centre
5	Senses: Sight	What can be seen from where: viewpoints, sightlines, light	Rasters	Street lights (`highway=street_lamp`), Eindhoven lamp posts, AHN for heights
6	Vintage	Old-map styling: sepia palette, serif fonts, hand-drawn texture; or old data	Map design	BAG buildings built before 1940; historical maps on topotijdreis.nl
7	10 minute map	Set a timer. Reuse yesterday’s script with new data	Anatomy	Any OSM tag you have not tried

Week 2: ideas and places¶

Day	Theme	Technique	Read	Data idea
8	Utopia	Your ideal city: edit data, draw new features, or map a plan	Vector data	A car-free centre; every building within 300 m of a park
9	Urban-rural	Classify areas by density; compare inside and outside the city	Map design	CBS address density (`omgevingsadressendichtheid`) per neighbourhood
10	Prompting only	The whole map made through an AI chat or agent. Save your prompts	Maps with AI	Anything, as long as it is real
11	Senses: Sound	Noise from roads, rail and the airport; quiet places	Finding data	Noise maps (geluidkaarten) on PDOK or the Atlas Leefomgeving
12	Power	Energy infrastructure, or who has power	Finding data	`power=line`, `power=substation`, solar panels (`generator:source=solar`) from OSM
13	Interactions	Flows and connections between places; or an interactive map	Web maps	Commuting flows from CBS; a `folium` or `tmap` view map
14	Borgesian map	A map at 1:1, or a map of a map. Read Borges’ On Exactitude in Science first	Map design	Your own desk, or the boundary of a boundary

Week 3: experiments¶

Day	Theme	Technique	Read	Data idea
15	Inside out	Invert the usual figure and ground: map the gaps, the outside, the negative space	Vector data	Everywhere more than 500 m from a café (`overlay(..., how="difference")`)
16	Collaborative map	Made with another person: AI does not count	—	Pair up at the Coding Café; combine your two datasets
17	Light & dark	Dark basemap, glowing data; or day and night	Rasters	Café density as a glow; street lamps
18	NULL	Map the missing: empty values, data gaps, places with nothing	Finding data	Cafés without opening hours in OSM; CBS negative placeholder values
19	Senses: Smell	Sources and spread: buffers, density, wind direction	Vector data	Bakeries, coffee roasters, the sewage works, flowering trees from Eindhoven’s tree data
20	Hexagons	Aggregate to a hexagon grid	Grids	Cafés or trees per hexagon; H3
21	OpenStreetMap	Anything from OSM, with the credit on the map	Finding data	Benches, bike parking, drinking water (`amenity=drinking_water`)

Week 4: craft¶

Day	Theme	Technique	Read	Data idea
22	Projections	Compare projections, or use an unusual one on purpose	Projections	The world in five projections; the Netherlands in Web Mercator vs RD New
23	Senses: Taste	Food: where it is grown, sold, eaten	Finding data	Restaurants by `cuisine` (a qualitative palette); markets; allotments
24	Network	Street networks, routing, travel time	Finding data	`osmnx` bike network of Eindhoven; distance from TU/e to every café along streets
25	Is this a map?	Push the definition: a diagram, a table, an abstraction	Map design	Cafés as a list sorted by distance to the station, drawn as a map
26	Water	Rivers, flood risk, rain, groundwater	Rasters	The Dommel and Gender (`waterway=*`); AHN low points; Klimaateffectatlas flooding
27	New tool	Use something you have never used: QGIS, R if you use Python, an AI agent	QGIS, Maps with AI	Remake your Day 1 map in the new tool
28	Senses: Feeling	Heat, wind, comfort, safety; or how a place feels	Finding data	Heat maps (hittekaart) from the Klimaateffectatlas; tree cover per neighbourhood
29	Raster	Elevation, hillshade, satellite imagery, a density surface	Rasters	AHN hillshade of the TU/e campus; building heights (DSM minus DTM)
30	Pen & paper	No code. Draw a map by hand, photograph it, and share it	—	Your walk to work

Planning your month¶

You will not do all 30, and nobody expects you to. A few ways to choose:

Follow a thread. Pick one dataset (Eindhoven’s trees, say) and map it on every day where it fits: points, hexagons, density, NULL for trees without a species, Smell for flowering ones.
Follow a technique. Do the four basic days (1 Points, 2 Lines, 3 Polygons, 20 Hexagons) in both Python and R.
Follow a question from your research. If you work on heat, energy, mobility or water, there is a day for it. A map made for the challenge often turns into a figure for a paper.
Do the AI days. Day 10 and Day 27 are a direct way to take part in the Coding Café’s 2026/27 theme, and the comparison is worth sharing at a session.