Building a visualization with Bokeh involves the following steps:
- Prepare the data
- Determine where the visualization will be rendered
- Set up the figure(s)
- Connect to and draw your data
- Organize the layout
- Preview and save your beautiful data creation
This video will explore each step in more detail.
The template below can be used to explore the six building blocks used across this course.
Python
"""Bokeh Visualization Template
This template is a general outline for turning your data into a
visualization using Bokeh.
"""
# Data handling
import pandas as pd
import numpy as np
# Bokeh libraries
from bokeh.io import output_file, output_notebook
from bokeh.plotting import figure, show
from bokeh.models import ColumnDataSource
from bokeh.layouts import row, column, gridplot
from bokeh.models.widgets import Tabs, Panel
# Prepare the data
# Determine where the visualization will be rendered
output_file('filename.html') # Render to static HTML, or
output_notebook() # Render inline in a Jupyter Notebook
# Set up the figure(s)
fig = figure() # Instantiate a figure() object
# Connect to and draw the data
# Organize the layout
# Preview and save
show(fig) # See what I made, and save if I like it