The Data Series: Interactive Visualization in Python
The first post in our Data Series is written by Multiverse Data Coach - Ashray Shetty
Most of us who have used python before are already familiar with using Matplotlib and seaborn for creating beautiful visualizations.
While Matplotlib and Seaborn are amazing libraries, they help create mostly static plots. In order to make the plots interactive in matplotlib we usually need to add lots of lines of code.Plotly on the other hand allows to us to create beautiful, interactive, exportable figures in just a few lines of code.
If you have never used Plotly before, you can always read more about them here. I have prepared a short tutorial on how to use Plotly express to add sliders into your plots, this will allow us to make our plots more interactive and explore different dimensions of the data. You can find the tutorial here. The tutorial is based on the survey dataset from Kaggle conducted on all the data scientists from around the world. It's an amazing dataset if you are interested to learn more about the data science community.
Hopefully, you find the tutorial useful, if you have an account with Kaggle, then by all means copy and edit the code in the notebook and share any of your amazing visualization and findings in this post. I will keep updating the notebook to reflect any of the feedback that you can provide. I wish you good luck and happy coding!