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My Fourth Week of the #30DayMapChallange

My personal take on the fourth week of the #30DayMapChallange, a daily social challenge aimed at designing thematic maps every day in…

Since 2019, the Geographic Information System (GIS) and spatial analytics community have been quite busy each November – thanks to a fun challenge called the #30DayMapChallange. Each year, this challenge has a thematic schedule, proposing a topic that should be the primary directive for map visualisation to be posted on that particular day. While the pre-defined daily topics certainly mean a constraint for the creative mind, they also help participants to find mutual interest, share data sources, and express individual styles visually and technologically.

Here, I would like to briefly overview my fourth – and last – week of this challenge, detailing and showing the different maps I created – usually in Python using various tools of spatial analytics and Geospatial data.

In this article, all images were created by the author.

Day 22 – ๐๐จ๐ซ๐ญ๐ก ๐ข๐ฌ ๐๐จ๐ญ ๐€๐ฅ๐ฐ๐š๐ฒ๐ฌ ๐”๐ฉ

I have wrestled a lot with this piece, both in terms of topic and visuals. In the end, I defaulted to my background in Physics and decided to draw up the Earth’s magnetic field with its Main Field Declination lines. These lines, as magnetic poles, can either be positive or negative. The Earth’s magnetic north pole is defined by these lines – which is not always up. Its moving! In recent years, it started migrating from the Canadian Arctic towards Russia at a speed of several kilometres per year.

Day 23 – 3๐ƒ

My first 3D map ever – so I kept the data relatively simple and went for downtown Budapest home, particularly District V. and District VI. in Pest and visualised its building height profile based on ATLO s Budapest Open Data Atlas. As for the tech part, I used Python as always and finally learned the basics of Pydeck to create this piece. Enjoy the interactive version here, each building height being proportional to its actual height, which information is also encoded in the colour sharing:.

For locals – its reassuring to see the Parlament and the Basilica as the highest buildings!

Day 24โ€” Black and White

I finally created my first ridge map in my black and white map following several great examples on beautiful Joy-division album-cover-styled Maps. I used the Python version implemented by Colin Carroll. To the technical end, the elevation data used by ridge_map comes from NASA’s Shuttle Radar Topography Mission. The only slight change I added in my notebook is that I hooked the bounding box part up to OSMNx, so now one just has to type the name of the area they wish to visualise.

Beautiful tool and results; enjoy the view of Italy here:

Day 25โ€” Antarctica

This was a tricky one – so few data available. I am exceptionally curious about others’ posts! As for myself, I ended up simply visualising a 125m resolution SAR image of the whole continent provided by the National Snow and Ice Data Center. The false color tones correspond to different morphological properties, as the documentation puts it:

[](https://daacdata.apps.nsidc.org/pub/DATASETS/nsidc0103_radarsat_sar/geoTIF_V2/ https://nsidc.org/sites/default/files/nsidc-0103-v002-userguide_0.pdf)”๐˜›๐˜ฉ๐˜ฆ 25 ๐˜ฎ ๐˜ช๐˜ฎ๐˜ข๐˜จ๐˜ฆ ๐˜ต๐˜ช๐˜ญ๐˜ฆ๐˜ด ๐˜ฑ๐˜ณ๐˜ฆ๐˜ด๐˜ฆ๐˜ณ๐˜ท๐˜ฆ ๐˜ข ๐˜ต๐˜ณ๐˜ถ๐˜ฆ ๐˜ฒ๐˜ถ๐˜ข๐˜ฏ๐˜ต๐˜ช๐˜ต๐˜ข๐˜ต๐˜ช๐˜ท๐˜ฆ ๐˜ฎ๐˜ฆ๐˜ข๐˜ด๐˜ถ๐˜ณ๐˜ฆ ๐˜ฐ๐˜ง ๐˜ฃ๐˜ข๐˜ค๐˜ฌ๐˜ด๐˜ค๐˜ข๐˜ต๐˜ต๐˜ฆ๐˜ณ ๐˜ธ๐˜ฉ๐˜ช๐˜ค๐˜ฉ ๐˜ฎ๐˜ข๐˜บ ๐˜ฃ๐˜ฆ ๐˜ฅ๐˜ช๐˜ณ๐˜ฆ๐˜ค๐˜ต๐˜ญ๐˜บ ๐˜ณ๐˜ฆ๐˜ญ๐˜ข๐˜ต๐˜ฆ๐˜ฅ ๐˜ต๐˜ฐ ๐˜ด๐˜ช๐˜จ๐˜ฎ๐˜ข-๐˜ฏ๐˜ข๐˜ถ๐˜จ๐˜ฉ๐˜ต. ๐˜๐˜ฐ๐˜ณ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ฐ๐˜ต๐˜ฉ๐˜ฆ๐˜ณ ๐˜ฑ๐˜ณ๐˜ฐ๐˜ฅ๐˜ถ๐˜ค๐˜ต๐˜ด, ๐˜ฆ๐˜ข๐˜ค๐˜ฉ ๐˜ฑ๐˜ช๐˜น๐˜ฆ๐˜ญ’๐˜ด ๐˜ช๐˜ฏ๐˜ต๐˜ฆ๐˜ฏ๐˜ด๐˜ช๐˜ต๐˜บ ๐˜ฒ๐˜ถ๐˜ข๐˜ญ๐˜ช๐˜ต๐˜ข๐˜ต๐˜ช๐˜ท๐˜ฆ๐˜ญ๐˜บ ๐˜ณ๐˜ฆ๐˜ฑ๐˜ณ๐˜ฆ๐˜ด๐˜ฆ๐˜ฏ๐˜ต๐˜ด ๐˜ช๐˜ต๐˜ด ๐˜ณ๐˜ข๐˜ฅ๐˜ข๐˜ณ ๐˜ฃ๐˜ข๐˜ค๐˜ฌ๐˜ด๐˜ค๐˜ข๐˜ต๐˜ต๐˜ฆ๐˜ณ ๐˜ช๐˜ฏ๐˜ต๐˜ฆ๐˜ฏ๐˜ด๐˜ช๐˜ต๐˜บ, ๐˜ฃ๐˜ถ๐˜ต ๐˜ข๐˜ค๐˜ต๐˜ถ๐˜ข๐˜ญ ๐˜ฃ๐˜ข๐˜ค๐˜ฌ๐˜ด๐˜ค๐˜ข๐˜ต๐˜ต๐˜ฆ๐˜ณ ๐˜ท๐˜ข๐˜ญ๐˜ถ๐˜ฆ๐˜ด ๐˜ฉ๐˜ข๐˜ท๐˜ฆ ๐˜ฃ๐˜ฆ๐˜ฆ๐˜ฏ ๐˜ข๐˜ณ๐˜ฃ๐˜ช๐˜ต๐˜ณ๐˜ข๐˜ณ๐˜ช๐˜ญ๐˜บ ๐˜ข๐˜ฅ๐˜ซ๐˜ถ๐˜ด๐˜ต๐˜ฆ๐˜ฅ ๐˜ต๐˜ฐ ๐˜ช๐˜ฎ๐˜ฑ๐˜ณ๐˜ฐ๐˜ท๐˜ฆ ๐˜ฎ๐˜ฐ๐˜ด๐˜ข๐˜ช๐˜ค ๐˜ช๐˜ฎ๐˜ข๐˜จ๐˜ฆ ๐˜ฒ๐˜ถ๐˜ข๐˜ญ๐˜ช๐˜ต๐˜บ. ๐˜๐˜ข๐˜ณ๐˜ช๐˜ข๐˜ฃ๐˜ญ๐˜ฆ๐˜ด ๐˜ข๐˜ง๐˜ง๐˜ฆ๐˜ค๐˜ต๐˜ช๐˜ฏ๐˜จ ๐˜ณ๐˜ข๐˜ฅ๐˜ข๐˜ณ ๐˜ฃ๐˜ข๐˜ค๐˜ฌ๐˜ด๐˜ค๐˜ข๐˜ต๐˜ต๐˜ฆ๐˜ณ ๐˜ช๐˜ฏ๐˜ค๐˜ญ๐˜ถ๐˜ฅ๐˜ฆ ๐˜ด๐˜ถ๐˜ณ๐˜ง๐˜ข๐˜ค๐˜ฆ ๐˜ณ๐˜ฐ๐˜ถ๐˜จ๐˜ฉ๐˜ฏ๐˜ฆ๐˜ด๐˜ด, ๐˜ต๐˜ฉ๐˜ฆ ๐˜ด๐˜ถ๐˜ณ๐˜ง๐˜ข๐˜ค๐˜ฆ ๐˜ฎ๐˜ข๐˜ต๐˜ฆ๐˜ณ๐˜ช๐˜ข๐˜ญ’๐˜ด ๐˜ฅ๐˜ช๐˜ฆ๐˜ญ๐˜ฆ๐˜ค๐˜ต๐˜ณ๐˜ช๐˜ค ๐˜ฑ๐˜ณ๐˜ฐ๐˜ฑ๐˜ฆ๐˜ณ๐˜ต๐˜ช๐˜ฆ๐˜ด, ๐˜ข๐˜ฏ๐˜ฅ ๐˜ต๐˜ฉ๐˜ฆ ๐˜จ๐˜ฆ๐˜ฐ๐˜ฎ๐˜ฆ๐˜ต๐˜ณ๐˜บ ๐˜ฃ๐˜ฆ๐˜ต๐˜ธ๐˜ฆ๐˜ฆ๐˜ฏ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ด๐˜ฑ๐˜ข๐˜ค๐˜ฆ๐˜ค๐˜ณ๐˜ข๐˜ง๐˜ต ๐˜ข๐˜ฏ๐˜ฅ ๐˜ต๐˜ข๐˜ณ๐˜จ๐˜ฆ๐˜ต. ๐˜๐˜ฐ๐˜ณ ๐˜ฎ๐˜ฐ๐˜ณ๐˜ฆ ๐˜ช๐˜ฏ๐˜ง๐˜ฐ๐˜ณ๐˜ฎ๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ, ๐˜ด๐˜ฆ๐˜ฆ ๐˜›๐˜ฆ๐˜ค๐˜ฉ๐˜ฏ๐˜ช๐˜ค๐˜ข๐˜ญ ๐˜™๐˜ฆ๐˜ง๐˜ฆ๐˜ณ๐˜ฆ๐˜ฏ๐˜ค๐˜ฆ ๐˜ฐ๐˜ฏ ๐˜š๐˜ˆ๐˜™ ๐˜›๐˜ฉ๐˜ฆ๐˜ฐ๐˜ณ๐˜บ/๐˜๐˜ฏ๐˜ต๐˜ฆ๐˜ณ๐˜ฑ๐˜ณ๐˜ฆ๐˜ต๐˜ช๐˜ฏ๐˜จ ๐˜๐˜ฎ๐˜ข๐˜จ๐˜ฆ๐˜ด."

Day 26โ€” Minimal

So here we went minimal – and my minimalistic map is my all-time favourite, Budapest, especially its elevation contour lines collected from the Budapest Open Data Portal. The map clearly shows how the Danube split the city in half, how plain the Pest side is on the right (at around 100m above sea level), and how the Buda hills look down on it from a whopping height of 500m!

Day 27 – Dot

For my dot map, I again went for the Budapest Open Data Portal, which has a nice rasterised population map of Budapest (for more on population raster data, also check my tutorial on TDS)! Then, I turned each grid cell into the POI of its polygon and drew each POI with a marker with a size proportional to the number of inhabitants in the corresponding grid cell. Then, I coloured each dot red, blue, and white at random to give it this slightly old-school 3d vibe (I also have to admit, I became the biggest one of the neon red-blue colour palette this year, somewhat inspired by Star Wars).

Day 28โ€” Is this a chart or a map?

Undoubtedly, this was the strangest topic. Should I create a map or not? In the end, I decided to recreate one of my favourite map derivative visualisations, originally crafted Geoff Boeing. This map essentially shows how much a particular city – here, a whole bunch of European cities – stretches out. This can easily be captured by measuring the total length of road segments whose orientation falls into a certain bin (e.g. between 0 and 5 degrees). Then, turning these into polar bar plots, we arrive at this interesting digital footprint of city road networks:

Day 29 – Population

Here I am recapping my previous article, ๐„๐ฑ๐ฉ๐ฅ๐จ๐ซ๐ข๐ง๐  ๐‹๐š๐ซ๐ ๐ž-๐ฌ๐œ๐š๐ฅ๐ž ๐‘๐š๐ฌ๐ญ๐ž๐ซ ๐๐จ๐ฉ๐ฎ๐ฅ๐š๐ญ๐ข๐จ๐ง ๐ƒ๐š๐ญ๐š, published on Towards Data Science, where I explore two global population data sets available in raster format, and show how to visualize and process them at global, country, and city level as well:

"๐˜ ๐˜ฉ๐˜ข๐˜ท๐˜ฆ ๐˜ฐ๐˜ง๐˜ต๐˜ฆ๐˜ฏ ๐˜ด๐˜ฆ๐˜ฆ๐˜ฏ ๐˜ฃ๐˜ฆ๐˜ข๐˜ถ๐˜ต๐˜ช๐˜ง๐˜ถ๐˜ญ ๐˜ฑ๐˜ฐ๐˜ฑ๐˜ถ๐˜ญ๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ ๐˜ฎ๐˜ข๐˜ฑ๐˜ด ๐˜ค๐˜ช๐˜ณ๐˜ค๐˜ถ๐˜ญ๐˜ข๐˜ต๐˜ช๐˜ฏ๐˜จ ๐˜ฐ๐˜ฏ๐˜ญ๐˜ช๐˜ฏ๐˜ฆ; ๐˜ฉ๐˜ฐ๐˜ธ๐˜ฆ๐˜ท๐˜ฆ๐˜ณ, ๐˜ ๐˜ถ๐˜ด๐˜ถ๐˜ข๐˜ญ๐˜ญ๐˜บ ๐˜จ๐˜ฐ๐˜ต ๐˜ด๐˜ต๐˜ถ๐˜ค๐˜ฌ ๐˜ข๐˜ต ๐˜ด๐˜ฐ๐˜ฎ๐˜ฆ ๐˜ต๐˜ฆ๐˜ค๐˜ฉ๐˜ฏ๐˜ช๐˜ค๐˜ข๐˜ญ ๐˜ฑ๐˜ข๐˜ณ๐˜ต๐˜ด, ๐˜ญ๐˜ช๐˜ฌ๐˜ฆ ๐˜ท๐˜ช๐˜ด๐˜ถ๐˜ข๐˜ญ๐˜ช๐˜ป๐˜ช๐˜ฏ๐˜จ ๐˜ฐ๐˜ต๐˜ฉ๐˜ฆ๐˜ณ ๐˜ฎ๐˜ข๐˜ฑ ๐˜ด๐˜ฆ๐˜จ๐˜ฎ๐˜ฆ๐˜ฏ๐˜ต๐˜ด ๐˜ต๐˜ฉ๐˜ข๐˜ฏ ๐˜ด๐˜ฉ๐˜ฐ๐˜ธ๐˜ฏ ๐˜ช๐˜ฏ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ต๐˜ถ๐˜ต๐˜ฐ๐˜ณ๐˜ช๐˜ข๐˜ญ ๐˜ฐ๐˜ณ ๐˜ต๐˜ถ๐˜ณ๐˜ฏ๐˜ช๐˜ฏ๐˜จ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ญ๐˜ข๐˜ณ๐˜จ๐˜ฆ-๐˜ด๐˜ค๐˜ข๐˜ญ๐˜ฆ ๐˜ณ๐˜ข๐˜ด๐˜ต๐˜ฆ๐˜ณ ๐˜ฅ๐˜ข๐˜ต๐˜ข ๐˜ช๐˜ฏ๐˜ต๐˜ฐ ๐˜ฎ๐˜ฐ๐˜ณ๐˜ฆ ๐˜ค๐˜ฐ๐˜ฎ๐˜ฑ๐˜ถ๐˜ต๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ-๐˜ง๐˜ณ๐˜ช๐˜ฆ๐˜ฏ๐˜ฅ๐˜ญ๐˜บ ๐˜ท๐˜ฆ๐˜ค๐˜ต๐˜ฐ๐˜ณ ๐˜ง๐˜ฐ๐˜ณ๐˜ฎ๐˜ข๐˜ต๐˜ด. ๐˜ ๐˜ฐ๐˜ท๐˜ฆ๐˜ณ๐˜ค๐˜ฐ๐˜ฎ๐˜ฆ ๐˜ด๐˜ฐ๐˜ฎ๐˜ฆ ๐˜ฐ๐˜ง ๐˜ต๐˜ฉ๐˜ฆ๐˜ด๐˜ฆ ๐˜ด๐˜ฉ๐˜ฐ๐˜ณ๐˜ต๐˜ค๐˜ฐ๐˜ฎ๐˜ช๐˜ฏ๐˜จ๐˜ด ๐˜ช๐˜ฏ ๐˜ต๐˜ฉ๐˜ช๐˜ด ๐˜ข๐˜ณ๐˜ต๐˜ช๐˜ค๐˜ญ๐˜ฆ ๐˜ธ๐˜ช๐˜ต๐˜ฉ ๐˜ข ๐˜ฉ๐˜ข๐˜ฏ๐˜ฅ๐˜ด-๐˜ฐ๐˜ฏ ๐˜จ๐˜ถ๐˜ช๐˜ฅ๐˜ฆ ๐˜ต๐˜ฐ ๐˜ต๐˜ธ๐˜ฐ ๐˜ฑ๐˜ณ๐˜ช๐˜ฎ๐˜ข๐˜ณ๐˜บ ๐˜จ๐˜ญ๐˜ฐ๐˜ฃ๐˜ข๐˜ญ ๐˜ฑ๐˜ฐ๐˜ฑ๐˜ถ๐˜ญ๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ ๐˜ฅ๐˜ข๐˜ต๐˜ข ๐˜ด๐˜ฐ๐˜ถ๐˜ณ๐˜ค๐˜ฆ๐˜ด.

๐˜๐˜ต ๐˜ช๐˜ด ๐˜ข๐˜ญ๐˜ด๐˜ฐ ๐˜ช๐˜ฎ๐˜ฑ๐˜ฐ๐˜ณ๐˜ต๐˜ข๐˜ฏ๐˜ต ๐˜ต๐˜ฐ ๐˜ฏ๐˜ฐ๐˜ต๐˜ฆ ๐˜ต๐˜ฉ๐˜ข๐˜ต ๐˜ฃ๐˜ฆ๐˜ด๐˜ช๐˜ฅ๐˜ฆ๐˜ด ๐˜ต๐˜ฉ๐˜ฆ๐˜ช๐˜ณ ๐˜ข๐˜ฆ๐˜ด๐˜ต๐˜ฉ๐˜ฆ๐˜ต๐˜ช๐˜ค ๐˜ท๐˜ข๐˜ญ๐˜ถ๐˜ฆ, ๐˜ฑ๐˜ฐ๐˜ฑ๐˜ถ๐˜ญ๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ ๐˜ฅ๐˜ข๐˜ต๐˜ข ๐˜ข๐˜ฏ๐˜ฅ ๐˜ฎ๐˜ข๐˜ฑ๐˜ด ๐˜ด๐˜ฉ๐˜ฐ๐˜ธ๐˜ช๐˜ฏ๐˜จ ๐˜ต๐˜ฉ๐˜ฆ๐˜ฎ ๐˜ข๐˜ณ๐˜ฆ ๐˜ข๐˜ฎ๐˜ฐ๐˜ฏ๐˜จ๐˜ด๐˜ต ๐˜ต๐˜ฉ๐˜ฆ ๐˜ฎ๐˜ฐ๐˜ด๐˜ต ๐˜ฃ๐˜ข๐˜ด๐˜ช๐˜ค ๐˜ช๐˜ฏ๐˜ง๐˜ฐ๐˜ณ๐˜ฎ๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ ๐˜ข๐˜ฏ๐˜ฅ ๐˜ท๐˜ข๐˜ญ๐˜ถ๐˜ข๐˜ฃ๐˜ญ๐˜ฆ ๐˜ช๐˜ฏ๐˜ง๐˜ฐ๐˜ณ๐˜ฎ๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ ๐˜ฐ๐˜ฏ๐˜ฆ ๐˜ค๐˜ข๐˜ฏ ๐˜จ๐˜ข๐˜ต๐˜ฉ๐˜ฆ๐˜ณ ๐˜ข๐˜ฏ๐˜ฅ ๐˜ช๐˜ฏ๐˜ค๐˜ฐ๐˜ณ๐˜ฑ๐˜ฐ๐˜ณ๐˜ข๐˜ต๐˜ฆ ๐˜ง๐˜ฐ๐˜ณ ๐˜ข๐˜ฏ๐˜บ ๐˜ถ๐˜ณ๐˜ฃ๐˜ข๐˜ฏ ๐˜ฅ๐˜ฆ๐˜ท๐˜ฆ๐˜ญ๐˜ฐ๐˜ฑ๐˜ฎ๐˜ฆ๐˜ฏ๐˜ต ๐˜ฐ๐˜ณ ๐˜ญ๐˜ฐ๐˜ค๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ ๐˜ช๐˜ฏ๐˜ต๐˜ฆ๐˜ญ๐˜ญ๐˜ช๐˜จ๐˜ฆ๐˜ฏ๐˜ค๐˜ฆ ๐˜ต๐˜ข๐˜ด๐˜ฌ. ๐˜›๐˜ฉ๐˜ฆ๐˜บ ๐˜ค๐˜ฐ๐˜ฎ๐˜ฆ ๐˜ช๐˜ฏ ๐˜ฑ๐˜ข๐˜ณ๐˜ต๐˜ช๐˜ค๐˜ถ๐˜ญ๐˜ข๐˜ณ๐˜ญ๐˜บ ๐˜ฉ๐˜ข๐˜ฏ๐˜ฅ๐˜บ ๐˜ช๐˜ฏ ๐˜ถ๐˜ด๐˜ฆ ๐˜ค๐˜ข๐˜ด๐˜ฆ๐˜ด ๐˜ด๐˜ถ๐˜ค๐˜ฉ ๐˜ข๐˜ด ๐˜ฑ๐˜ญ๐˜ข๐˜ฏ๐˜ฏ๐˜ช๐˜ฏ๐˜จ ๐˜ฏ๐˜ฆ๐˜ธ ๐˜ข๐˜ฎ๐˜ฆ๐˜ฏ๐˜ช๐˜ต๐˜ช๐˜ฆ๐˜ด, ๐˜ด๐˜ช๐˜ต๐˜ฆ ๐˜ด๐˜ฆ๐˜ญ๐˜ฆ๐˜ค๐˜ต๐˜ช๐˜ฐ๐˜ฏ ๐˜ข๐˜ฏ๐˜ฅ ๐˜ค๐˜ข๐˜ต๐˜ค๐˜ฉ๐˜ฎ๐˜ฆ๐˜ฏ๐˜ต ๐˜ข๐˜ฏ๐˜ข๐˜ญ๐˜บ๐˜ด๐˜ช๐˜ด, ๐˜ฆ๐˜ด๐˜ต๐˜ช๐˜ฎ๐˜ข๐˜ต๐˜ช๐˜ฏ๐˜จ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ด๐˜ค๐˜ข๐˜ญ๐˜ฆ ๐˜ฐ๐˜ง ๐˜ถ๐˜ณ๐˜ฃ๐˜ข๐˜ฏ ๐˜ฑ๐˜ณ๐˜ฐ๐˜ฅ๐˜ถ๐˜ค๐˜ต๐˜ด, ๐˜ฐ๐˜ณ ๐˜ฑ๐˜ณ๐˜ฐ๐˜ง๐˜ช๐˜ญ๐˜ช๐˜ฏ๐˜จ ๐˜ฅ๐˜ช๐˜ง๐˜ง๐˜ฆ๐˜ณ๐˜ฆ๐˜ฏ๐˜ต ๐˜ฏ๐˜ฆ๐˜ช๐˜จ๐˜ฉ๐˜ฃ๐˜ฐ๐˜ณ๐˜ฉ๐˜ฐ๐˜ฐ๐˜ฅ๐˜ด, ๐˜ซ๐˜ถ๐˜ด๐˜ต ๐˜ต๐˜ฐ ๐˜ฎ๐˜ฆ๐˜ฏ๐˜ต๐˜ช๐˜ฐ๐˜ฏ ๐˜ข ๐˜ง๐˜ฆ๐˜ธ."

Day 30 – My favourite

To close off this year’s map challenge, I decided not to pick my personal favourite but take people’s top 12 favourite – cities, showing their road network based on OpenStreetMap via the OSMNx package. While now I have made the code totally reproducible, it was originally published with the Data Visualization Society in the article linked below, starting like:

"๐˜™๐˜ฐ๐˜ข๐˜ฅ ๐˜ฏ๐˜ฆ๐˜ต๐˜ธ๐˜ฐ๐˜ณ๐˜ฌ๐˜ด ๐˜ข๐˜ณ๐˜ฆ ๐˜ฎ๐˜ข๐˜จ๐˜ฏ๐˜ช๐˜ง๐˜ช๐˜ค๐˜ฆ๐˜ฏ๐˜ต ๐˜ฃ๐˜ช๐˜ณ๐˜ฅ-๐˜ฆ๐˜บ๐˜ฆ ๐˜ท๐˜ช๐˜ฆ๐˜ธ ๐˜ง๐˜ช๐˜ฏ๐˜จ๐˜ฆ๐˜ณ๐˜ฑ๐˜ณ๐˜ช๐˜ฏ๐˜ต๐˜ด ๐˜ฐ๐˜ง ๐˜ค๐˜ช๐˜ต๐˜ช๐˜ฆ๐˜ด, ๐˜ข๐˜จ๐˜ฆ-๐˜ฐ๐˜ญ๐˜ฅ ๐˜ต๐˜ฐ๐˜ฑ๐˜ช๐˜ค๐˜ด ๐˜ฐ๐˜ง ๐˜ถ๐˜ณ๐˜ฃ๐˜ข๐˜ฏ ๐˜ฑ๐˜ญ๐˜ข๐˜ฏ๐˜ฏ๐˜ช๐˜ฏ๐˜จ, ๐˜ข๐˜ฏ๐˜ฅ ๐˜ด๐˜ต๐˜ข๐˜ฃ๐˜ญ๐˜ฆ ๐˜ค๐˜ฐ๐˜ณ๐˜ฏ๐˜ฆ๐˜ณ๐˜ด๐˜ต๐˜ฐ๐˜ฏ๐˜ฆ๐˜ด ๐˜ฐ๐˜ง ๐˜ด๐˜ฑ๐˜ข๐˜ต๐˜ช๐˜ข๐˜ญ ๐˜ฅ๐˜ข๐˜ต๐˜ข ๐˜ด๐˜ค๐˜ช๐˜ฆ๐˜ฏ๐˜ค๐˜ฆ. ๐˜ˆ๐˜ด ๐˜ข ๐˜ฑ๐˜ณ๐˜ช๐˜ฎ๐˜ข๐˜ณ๐˜บ ๐˜จ๐˜ฐ๐˜ข๐˜ญ ๐˜ฐ๐˜ง ๐˜ต๐˜ฐ๐˜ฅ๐˜ข๐˜บ’๐˜ด ๐˜ถ๐˜ณ๐˜ฃ๐˜ข๐˜ฏ ๐˜ฑ๐˜ญ๐˜ข๐˜ฏ๐˜ฏ๐˜ช๐˜ฏ๐˜จ ๐˜ช๐˜ด ๐˜ต๐˜ฐ ๐˜ฅ๐˜ฆ๐˜ด๐˜ช๐˜จ๐˜ฏ ๐˜ญ๐˜ช๐˜ท๐˜ข๐˜ฃ๐˜ญ๐˜ฆ, ๐˜ง๐˜ถ๐˜ต๐˜ถ๐˜ณ๐˜ฆ-๐˜ฑ๐˜ณ๐˜ฐ๐˜ฐ๐˜ง ๐˜ค๐˜ช๐˜ต๐˜ช๐˜ฆ๐˜ด ๐˜ท๐˜ช๐˜ข ๐˜ค๐˜ฐ๐˜ฏ๐˜ค๐˜ฆ๐˜ฑ๐˜ต๐˜ด ๐˜ญ๐˜ช๐˜ฌ๐˜ฆ ๐˜ต๐˜ฉ๐˜ฆ 15-๐˜ฎ๐˜ช๐˜ฏ๐˜ถ๐˜ต๐˜ฆ ๐˜ค๐˜ช๐˜ต๐˜บ, ๐˜ฉ๐˜ฆ๐˜ณ๐˜ฆ ๐˜ ๐˜ค๐˜ฐ๐˜ญ๐˜ญ๐˜ฆ๐˜ค๐˜ต ๐˜ต๐˜ฉ๐˜ฆ ๐˜ต๐˜ฐ๐˜ฑ ๐˜ญ๐˜ช๐˜ด๐˜ต๐˜ด ๐˜ฐ๐˜ง ๐˜ฎ๐˜ฐ๐˜ด๐˜ต ๐˜ญ๐˜ช๐˜ท๐˜ข๐˜ฃ๐˜ญ๐˜ฆ ๐˜ค๐˜ช๐˜ต๐˜ช๐˜ฆ๐˜ด ๐˜ข๐˜ฏ๐˜ฅ ๐˜จ๐˜ช๐˜ท๐˜ฆ ๐˜ข ๐˜ท๐˜ช๐˜ด๐˜ถ๐˜ข๐˜ญ ๐˜ฐ๐˜ท๐˜ฆ๐˜ณ๐˜ท๐˜ช๐˜ฆ๐˜ธ ๐˜ฐ๐˜ง ๐˜ต๐˜ฉ๐˜ฆ๐˜ช๐˜ณ ๐˜ณ๐˜ฐ๐˜ข๐˜ฅ ๐˜ฏ๐˜ฆ๐˜ต๐˜ธ๐˜ฐ๐˜ณ๐˜ฌ๐˜ด – ๐˜ธ๐˜ช๐˜ต๐˜ฉ ๐˜ข ๐˜Š๐˜ฉ๐˜ข๐˜ต๐˜Ž๐˜—๐˜› ๐˜ต๐˜ธ๐˜ช๐˜ด๐˜ต."

Its a wrap – this was the summary of my last week doing the #30DayMapChallange. The first year I went for the complete package, I learned a lot, had lots of fun, and also spent exhausting hours trying to make maps look nice, no matter the topic!

See the overview of the third week here!

See the overview of the second week here!

See the overview of the first week here!


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