Geocoding in Python Made Easy: Plot map data using GeoPy - Even if you don't have Latitude/Longitude

Are you a beginner looking to enhance your dataset with location data but don't have latitude and longitude information in your dataset? Maybe you are a little more experienced, but just want to see what other people are doing. Look no further! In this step-by-step tutorial, we'll show you how to effortlessly geocode your data using GeoPy and Pandas, even if you don't have any geographical coordinates. We'll be using a powerful geocoding service called Nominatim, which harnesses the vast data from OpenStreetMap to find the latitude and longitude coordinates you need. Then, using Folium, we will generate an interactive geographic map to plot our data. Whether you're working on a business project, research, or just want to explore the world of data manipulation, this video is tailored for you. Watch now to unlock the power of geocoding and level up your data analysis skills!

Once you get the hang of things, you can try out other mapping and geocoding services until you find what is right for you. For mapping, I also like to use Plotly, which can also be used with R and JavaScript. However, for the sake of simplicity, I thought GeoPy would be a good starter tutorial for geocoding.

VIDEO TIMELINE

0:00 - Intro
0:06 - Overview of our dataset
0:36 - Creating new Python file and importing modules
1:26 - Importing our dataset
1:43 - Set up Nominatim geocoding service
1:56 - Define definition to geocode addresses
2:22 - Have our geocode_address set up to loop through rows of data
2:55 - Calculate the mean coordinates to center the map
3:24 - Make the map with folium
3:37 - Set up map markers
4:05 - Save the map to an HTML file
4:17 - Run and save it
4:40 - Check out our map!
5:04 - A sample of a modern looking Plotly map
5:18 - Outro

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