Spatial Thoughts

Want to level-up your #Python skills? We are launching a 30-day free challenge to learn Mapping and Data Visualization with Python. You will learn how to create charts and maps, work with large raster and vector datasets, create interactive maps, dashboards, and data-driven apps. All you need to do is spend 30 minutes every day watching a video and working on a coding exercise. Share your progress with the hashtag #PythonDatavizChallenge. Ready? Get started at ➡ https://lnkd.in/dBKAvgge ---- Week 1, 2 and 3 videos are already live. ---- Day 22 Streamlit Basics https://lnkd.in/dWhsm2bN Day 23 Building a Simple Dashboard App with Streamlit https://lnkd.in/dgQJf7sk Day 24 Building a Simple Geocoder App with Streamlit https://lnkd.in/d-uWhm6d Day 25 [Video will be released on 7 November 2024]

Registration for the upcoming cohort of the Advanced QGIS Course in November 2024 is now open. This will be an instructor-led live online class covering advanced topics in #QGIS. If you are interested, you can review the course details, check the session timings, and book your seat using the following link ➡ https://lnkd.in/dZpYmCXG

The #30daymapchallenge kicks off today, focusing on daily map posts following specific themes. With an academic background in GIS, I am now shifting towards open-source tools like QGIS and Python for map making. Today's theme, 'points,' led me to delve into crime data in Kent, UK, specifically examining recorded burglaries over the past 12 months until August 2024, compared to the previous year. Surprisingly, the analysis revealed no significant increase in burglaries in any particular area. The spatial distribution and total count of burglaries have largely remained consistent throughout this period. Special thanks to Ujaval Gandhi and the 'SpatialThoughts' team for their invaluable training courses and resources. Stay tuned for more maps inspired by the knowledge gained from their expertise. #Mapping #GIS #DataAnalysis Ujaval Gandhi

I’m excited to share that I have completed the #AdvancedQGIS Series by Spatial Thoughts on YouTube! This experience has been a fantastic way to refresh and deepen my knowledge of QGIS. A big thank you to Ujaval Gandhi and the Spatial Thoughts team for their outstanding guidance and for making these resources free. If you’re looking to enhance your skills in spatial analysis, I highly recommend checking out this series. Here are some key areas I explored: - Aggregate Functions for #Spatial #Analysis - Animating GPS Tracks - 3D Animations - Fuzzy Table Joins Whether you're new to QGIS or want to brush up on your skills, this resource is invaluable. https://lnkd.in/g2xq3GRp #QGIS #SpatialAnalysis #GIS

New Post: Tiling Large Exports in Google #EarthEngine with best practices on dealing with very large images. The post demystifies some of the advanced concepts in GEE such as projections, resampling and nodata masks along with a reproducible example for creating perfectly aligned gridded exports ➡ https://lnkd.in/dUxAgYN9

Here is a map of the current mining claims in Ontario that I created today entirely using Python code in a Jupyter Lab Notebook. I used the geopandas, matplotlib and contextily libraries to manipulate some geospatial data, calculate the area of the claims and fetch an open-source basemap. This is the first map I've created entirely in Python using open-source libraries! Stay tuned for the historical maps of mining claims in Ontario from the past ten years. Thanks to Spatial Thoughts for the excellent lessons you are providing in your 30-day #pythondatavizchallenge course! #python #opensource #jupyterlab #geopandas #geospatial

🌍 Last week, we had the pleasure of hosting Ujaval Gandhi from Spatial Thoughts in Tartu for a short course on Applied Remote Sensing with Google #EarthEngine, as part of our URBANGIS and GEM Erasmus Mundus MSc program! 🛰💻 Our students gained invaluable skills in using Google Earth Engine for remote sensing analysis and learned how to publish their results as apps. It was an incredible opportunity to learn from one of the leading experts in GEE! 😊👏 Additionally, Ujaval delivered an insightful talk on “Building a Career with Open-Source Technologies,” packed with excellent advice for young professionals looking to carve out their path in the field. 🤩 Thank you, Ujaval, for your expertise and inspiration! 🙏 #RemoteSensing #Geospatial #Education #OpenSource

🌍 30 Days of Mapping and Data Visualization with Python: A Journey! 🚀 Day 1: Introduction I am kicking off an exciting 30-day challenge to #master mapping and #data #visualization with #Python! 🌟 This challenge will covers everything from #creating stunning #charts and #animations to #crafting insightful #maps. Can't wait to dive into this! 📊 Day 2: #Notebooks and #Datasets Working with #Google #Colab for all #exercises no installations needed! 🚀 Google Colab gives me free cloud #resources to run #Python #code, which is perfect for #managing data and #visualizing it in #real-time. That day, I explored #basic #matplotlib features and #created a #plot displaying two #points with unique symbols and colors. 🔴🟢 📈 Day 3: Creating Charts Used #Pandas to create interactive #charts from a #London crime #dataset. From #pie charts to #bar graphs, I am seeing how data #visualization brings insights to life. The day’s #challenge: #visualize the #trend of bicycle thefts using a #line #chart. 🚲📉 🗺️ Day 4: Creating Maps Next up, #GeoPandas! Using #census data, I created a #choropleth #map showing #population #density. This involved some data wrangling—merging #shapefiles with population data and calculating population #density. #Visualizing #these stats on a map feels powerful! 🌐📊 🗺️ Day 5: Using #Basemaps Mapped the path of the 2017 Solar Eclipse with #Contextily, a #powerful tool for #overlaying data on #basemaps. Context helps! Trying out different #basemaps like #Esri.WorldTerrain and #CartoDB.Positron really gave me new #perspectives on #visualizing #geographical data. 🌘🌍 🔥 Stay tuned for more as I continue this 30-day challenge! Special thanks to Spatial Thoughts for the guidance. Let’s keep learning and growing! 💪 #PythonDatavizChallenge #30DaysChallenge #DataScience Feel free to connect and share your insights on mapping and data viz! 🎉

On day three of the #PythonDatavizChallenge, I dove into creating charts and exploring the customizations available through Matplotlib and Seaborn. It was an exciting journey enhancing visualizations with style and flair! Huge thanks again to Spatial Thoughts for organizing this fantastic challenge! If you’re interested in joining, check out the link! https://lnkd.in/gGqYJRKu #SpatialThoughts #Python #Matplotlib #Seaborn #GoogleColab #pythondatavizchallenge

On the second day of the #PythonDatavizChallenge, I learnt about Google Colab and the foundations of Matplotlib, the most popular Data visualization library in the Python ecosystem. I've solved the exercise and had a lot of fun! Thanks, Spatial Thoughts for this amazing challenge! If you want to join it, follow the link https://lnkd.in/dc6kMSfd