Time Travelling
On Sept. 28, Hurricane Ian made landfall near Cayo Costa in southwestern Florida. In this example, we want to visualize the impact that the Hurricane had in terms of sentiment of Twitter tweets over time around the world.
We first read in a prepared dataset that contains the timestamp, location, and sentiment of tweets about Hurricane Ian. We then visualize the sentiment across the whole globe for the time before, during and after the Hurricane using time playback function of the Kepler.gl Geoview node.
The component view shows on the left hand site an animation that shows how this analysis can be performed in the Kepler.gl view which is shown on the right hand site for you to give it a try.
Geospatial Analytics is fully developed in Python, e.g. the Geopandas library, which was heavily used to write the nodes. All the nodes provided with the extension are the perfect toolkit to apply geospatial technologies in a no-code/low-code way, so also beginners can benefit from this kind of analysis. The time travelling visualization is done using the time playback function in the Kepler.gl Geoview node.