Setting tools

The agency is now interested in understanding whether the most accurate shooters are more likely to average a higher amount of points per game. They would like to have the toolbar customized to include poly_select, wheel_zoom, reset, and save, so they can further investigate the plot themselves.

The nba DataFrame is again available to you.

This exercise is part of the course

Interactive Data Visualization with Bokeh

View Course

Exercise instructions

Create a list of required tools, poly_select, wheel_zoom, reset, and save.
Create a figure, fig, labeling the x and y axes as "Field Goal (%)" and "Points per Game", along with setting the tools to be included.
Add circle glyphs to represent "field_goal_perc" as x and "points" as y.
Generate an HTML file called "points_vs_field_goal_perc.html", and display the plot.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Create a list of tools
tools = ____

# Create figure and set tools
fig = ____(x_axis_label="Field Goal (%)", y_axis_label="Points per Game", tools=____)

# Add circle glyphs
fig.____(____=____, ____=____)

# Generate HTML file and display plot
____
____(____)

Edit and Run Code