5 examples from the Vital Volcanic Eruption database
Plotly is a good open supply library for visualizing information. On this weblog submit, I’m going to point out you find out how to generate cartographic plots with plotly, working with the Python backend.
For illustration functions, I’ll use the Vital Volcanic Eruption Database, revealed by the US Nationwide Facilities for Environmental Info underneath the U.S. Government Work License. The dataset is out there for obtain right here: https://public.opendatasoft.com/explore/dataset/significant-volcanic-eruption-database/information/
You’re going to see the next 5 visualizations:
- International distribution of serious volcanic eruptions
- Volcano varieties in North America
- Volcanic eruptions related to tsunamis
- Most damaging volcanic eruptions
- Humorous map projections
For readers excited about utilizing plotly for information evaluation, please consult with my current submit on visualizing information from the Ladies’s World Cup:
Getting ready the info
After downloading the volcanic eruption database, we load it as a pandas DataFrame. DataFrames combine naturally with Plotly and are handy for information evaluation. We rework the columns that encode whether or not a volcanic eruption is related to a volcano or an earthquake to True/False values and add new columns for the latitude and longitude of an eruption.
