Milan Janosov’s Post

#30𝐃𝐚𝐲𝐌𝐚𝐩𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 - 𝐃𝐚𝐲 14 - 𝐀 𝐰𝐨𝐫𝐥𝐝 𝐦𝐚𝐩 For this map, I combined my two passions - network science and spatial analytics and created a neighborhood graph of the global countries. Building on Natural Earth's country data, I connected two countries if they share a physical border. Then, visualized it using Gephi. Learn how to build this graph from my Python tutorial arriving on Substack soon! #datascience #networkscience #connectingthedots #GIS #spatialanalytics #geospatialdata #geospatial #datascience #datavisualization

𝐈𝐍𝐓𝐑𝐎𝐃𝐔𝐂𝐓𝐈𝐎𝐍 𝐓𝐎 𝐆𝐄𝐎𝐒𝐏𝐀𝐓𝐈𝐀𝐋 𝐃𝐀𝐓𝐀 𝐒𝐂𝐈𝐄𝐍𝐂𝐄 (𝐕𝐈𝐃𝐄𝐎 𝐂𝐎𝐔𝐑𝐒𝐄) – 𝐕𝐞𝐜𝐭𝐨𝐫 𝐃𝐚𝐭𝐚 𝐄𝐝𝐢𝐭𝐢𝐨𝐧 This nearly two and a half hour pre-recorded course aims to give a comprehensive overview of getting started in geospatial data science using Python. The course covers the key concepts of spatial analytics, such as geometries and coordinate reference systems, different types of geometric data, such as road networks and building footprints, and map status and interactive visualizations. 𝐌𝐨𝐫𝐞 𝐢𝐧𝐟𝐨: https://lnkd.in/dG8SqMEP #GIS #spatialanalytics #geospatialdata #geospatial #datascience #datavisualization

#30𝐃𝐚𝐲𝐌𝐚𝐩𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 - 𝐃𝐚𝐲 12 - 𝐓𝐢𝐦𝐞 𝐚𝐧𝐝 𝐬𝐩𝐚𝐜𝐞 Here I wanted to visualize and compare Pangea and today's world map. While even getting the right data was a challenge (thanks go to Reddit), the map projection is still a bit off, so I would call this a work in progress. For the Python code behind, keep an eye on my Substack! #datascience #networkscience #connectingthedots #GIS #spatialanalytics #geospatialdata #geospatial #datascience #datavisualization 

Do you want to get on board with spatial analytics in Python or overview the 101 best practices in geospatial data? Then, take my new course, 𝐈𝐍𝐓𝐑𝐎𝐃𝐔𝐂𝐓𝐈𝐎𝐍 𝐓𝐎 𝐆𝐄𝐎𝐒𝐏𝐀𝐓𝐈𝐀𝐋 𝐃𝐀𝐓𝐀 𝐒𝐂𝐈𝐄𝐍𝐂𝐄! 𝐂𝐨𝐮𝐫𝐬𝐞: https://lnkd.in/dG8SqMEP 𝐎𝐔𝐓𝐋𝐈𝐍𝐄: 1. Geometries - The Building Blocks of Spatial Analytics 2. GeoPandas in Practice - The Spatial Swiss Knife 3. Collecting and Exploring Vector Data - OpenStreetMap 4. Geospatial Features and Urban Analytics #GIS #spatialanalytics #geospatialdata #geospatial #datascience #datavisualization

This weekend, I am enjoying Milan Janosov's new book - Geospatial Data Science Essentials 🚀. Milan is one of the main Pythonic GIS people that I follow on LinkedIn, and his new book covers the following topics: ✅ Foundation of geometries ✅ Vector and GIS data in Python ✅ GIS data visualization ✅ Map projections ✅ OpenStreatMap data ❤️ ✅ Stats and ML applications for GIS data An online version of the book is available on Amazon: https://lnkd.in/gRCeig5e #datascience #dataviz #python #gis

My latest piece on Towards Data Science is out - 𝐒𝐮𝐦𝐦𝐞𝐫 𝐎𝐥𝐲𝐦𝐩𝐢𝐜 𝐆𝐚𝐦𝐞𝐬 𝐓𝐡𝐫𝐨𝐮𝐠𝐡 𝐭𝐡𝐞 𝐋𝐞𝐧𝐬 𝐨𝐟 𝐃𝐚𝐭𝐚 - Using Python and Wikipedia to draw geographical and network maps of the medal-winning countries. In this article, I walk you through a long and tedious data collection and cleaning process using Wikipedia and then draw the Gold, Silver, and Bronze world maps. Read it here: https://lnkd.in/dscHvhb5  #geodatascience101 #geospatialessentials #GIS #spatialanalytics #geospatialdata #geospatial #datascience #datavisualization

Geo-Py in Urban Analytics Today marks the beginning of my new course on Python in Urban Spatial Analytics (currently available only in Russian). I'm excited about the opportunity to structure and share the knowledge I have in this field. The interactive book for the course: https://lnkd.in/dW-QGn_5 The YouTube playlist for the course: https://lnkd.in/dND39A6Q You can also join my Telegram channel for updates on the course (and other fun GIS materials): https://t.me/GIS_PEACE The first two videos are already available on YouTube, and the playlist will be updated with new topics every week. P.S. Everything is in Russian, but I have ambitions to create an English version later.

I have a big announcement coming next week: my next book, GEOSPATIAL DATA SCIENCE ESSENTIALS—101 Practical Python Tips and Tricks, will be out on Amazon and many other global stores! To be amongst the first to learn about that, join my newsletter: https://lnkd.in/dCebRmdH #geodatascience101 #geospatialessentials #GIS #spatialanalytics #geospatialdata #geospatial #datascience #datavisualization

My new book, 𝐆𝐞𝐨𝐬𝐩𝐚𝐭𝐢𝐚𝐥 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐄𝐬𝐬𝐞𝐧𝐭𝐢𝐚𝐥𝐬: 101 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐚𝐥 𝐏𝐲𝐭𝐡𝐨𝐧 𝐓𝐢𝐩𝐬 𝐚𝐧𝐝 𝐓𝐫𝐢𝐜𝐤𝐬 has been out for a few days now - and here comes a quick outline and sample of it! 𝐀𝐦𝐚𝐳𝐨𝐧: https://lnkd.in/dUkHadCW    𝐒𝐡𝐨𝐩𝐢𝐟𝐲: https://lnkd.in/dwEperZ7 𝐖𝐡𝐚𝐭 𝐭𝐡𝐞 𝐫𝐞𝐬𝐭 𝐨𝐟 𝐭𝐡𝐢𝐬 𝐛𝐨𝐨𝐤 𝐢𝐬 𝐚𝐛𝐨𝐮𝐭: - Introduction to Geometries - Vector Data in Python - Visualizing Geospatial Data - Map Projections - Spatial Indexing  - Geocoding - Raster Data in Python - Introduction to OpenStreetMap Data - Spatial Networks - Geospatial Statistics and Machine Learning 𝐁𝐨𝐨𝐤 𝐝𝐞𝐬𝐜𝐫𝐢𝐩𝐭𝐢𝐨𝐧: Geospatial Data Science Essentials is your hands-on guide to mastering the science of geospatial analytics using Python. Designed for practitioners and enthusiasts alike, this book distills years of experience by wrapping up 101 key concepts from theory to implementation, ensuring you gain a practical understanding of the tools and methods that define the geospatial data science landscape today. Whether you are a seasoned data scientist, a GIS professional, a newcomer to spatial data, or simply a map lover, this book provides you solid foundation to level up your skills... #geodatascience101 #geospatialessentials #GIS #spatialanalytics #geospatialdata #geospatial#datascience

#30daymapchallenge Day 06: Interactive Map 🌍 Just finished working on an exciting project! 🎉 I created an interactive population map of Berlin (2022) using Folium for the interactive visualization and Geopandas for geospatial analysis. The map is powered by population data from Geoportal Berlin, providing an insightful view of the city's population distribution. 📊 This project allowed me to apply my data and GIS skills in a meaningful way. Looking forward to diving deeper into the world of geospatial analysis and uncovering more data-driven insights! Feel free to check it out and share your thoughts! 🌐 #GIS #DataScience #Berlin #GeospatialAnalysis #Folium #GeoPandas #DataVisualization #InteractiveMap #Chloropleth #Python