Python & Bokeh: From Data to Visualization
Key Takeaways
Builds a data visualization with Python and Bokeh
Full Transcript
so there's several steps to go from data to visualization these six steps prepare the data determine where the visualizations going to be rendered set up figures connect to and draw your data organize the layout and then preview and save your beautiful data creation part of steps that you'll follow each time you make a visualization let me talk about each one briefly so first you need to prepare the data this can be in a separate file if you want but typically it comes in the form of large tables those data tables can be handled or data frames can be handled inside of pandas or using something like numpy you'll need to be doing some cleaning usually and preparing the data and then transforming the data to show the types of things that you want to see next need to determine where the visualizations going to be rendered that would be in a static HTML file or inline inside of a Jupiter notebook which I'll show you both then you need to set the figures preparing the canvas customizing titles tick marks backgrounds etc and then enable the type of user interactions step 4 is to connect to and draw your data select the type of renderer they're called glyphs to give shape to your data and these could be charts Maps histograms plots heat maps etc then you'll organise the layout you can have multiple figures for your visualization and so those multipliers can be in a grid-like layout or in tabs and then there's also ways to link interactions across the figures and last step is to preview and save your beautiful data creation either in a browser or notebook as we talked about you can then explore those visualizations and examine how you've customized things and then play with all the interactions that you've added I'd like to show you a template to give you an idea of all those steps and what they would look like inside your script first off in some cases you'll be doing your data handling inside of the script sometimes you'll do it by importing so you may find yourself importing pandas or numpy to do that type of work after importing those for data handling if needed you'll import from the bouquet libraries no need to focus on them now they'll be in each of the upcoming scripts a step 1 prepare the data or import the data that you're going to use and then step two you got to determine where you want the visualization to be rendered so that can be again to an output file or you can output to a notebook next you instantiate a figure object can step three then you connect to and draw the data using glyphs step five is for organizing the layout especially if you have multiple visualizations and last would be previewing and saving using the method show this will act as a template with these six steps for all the upcoming scripts and videos next up time to get boquete installed and setup
Original Description
Building a data visualization with Bokeh involves the following steps:
1. Prepare the data
2. Determine where the visualization will be rendered
3. Set up the figure(s)
4. Connect to and draw your data
5. Organize the layout
6. Preview and save your beautiful data creation
This video will explore each step in more detail.
🐍🎓Click here to learn more about this topic: https://realpython.com/courses/interactive-data-visualization-python-bokeh/
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