Bokeh Scatter Plot with Hover and Select Tools

This code defines a function that creates a scatter plot using the Bokeh library, and adds hover and box select tools. The input data is two arrays representing the x and y values.

Technology Stack : The code uses the Bokeh library and other Python packages such as NumPy and matplotlib for plotting.

Code Type : The type of code

Code Difficulty :

                
                    
import numpy as np
import bokeh.plotting as plt
from bokeh.models import ColumnDataSource, HoverTool, BoxSelectTool

def plot_random_scatter(x_values, y_values):
    # Create a random scatter plot using Bokeh
    fig, ax = plt.subplots()
    
    # Create a ColumnDataSource from the input data
    source = ColumnDataSource(data=dict(x=x_values, y=y_values))
    
    # Create a scatter plot
    p = ax.scatter('x', 'y', source=source)
    
    # Add a hover tool
    hover = HoverTool(
        tooltips=[
            ("index", "$index"),
            ("(x,y)", "($x, $y)"),
        ],
        formatters={
            'index': 'numeral',
            'x': 'numeral',
            'y': 'numeral',
        },
        mode='vline'
    )
    ax.add_tools(hover)
    
    # Add a box select tool
    select_tool = BoxSelectTool()
    ax.add_tools(select_tool)
    
    # Display the plot
    plt.show()

# Example usage
x_values = np.random.random(50) * 100
y_values = np.random.random(50) * 100
plot_random_scatter(x_values, y_values)