Eduardo E Sierra Hello everyone!
Going back to the exploratory data analysis performed on the NYC Airbnb Open Data public dataset, I showed you some of Seaborn’s data visualization capabilities.
The great thing about Python is that you have several resources at your disposal to create beautiful graphs and maps. Other than Seaborn, Plotly is another library that I use for data visualization.
In this case, I’ve combined the power of both Plotly and Mapbox to create the following interactive maps.
FYI: In case the maps are not displaying properly, please rotate your phone screen horizontally.
Take a look at all the NYC Airbnb listings mapped out per borough:
Here’s a breakdown of the nightly rates in Manhattan:
Now let’s map Brooklyn out by property type:
Isn’t this cool? Next time I’ll show you how to create these maps.
Have a wonderful weekend!
