Like many Python libraries, **Bokeh** is a large library with complex commands and detailed representations of many types of plots.

In order to get started, you need to have the library installed on your computer. Write:

```
pip install bokeh
```

Bokeh is used for several kinds of plots namely *scatter plots*, *grid plots*, and *line plots*. Let’s see how to make a simple Scatter Plot in bokeh.

**Grid plots** are used to display multiple plots together in order to visualize and compare them. This can be thought of as an extension of scatter plots.

## Grid Plotimport bokehfrom bokeh.plotting import figure, output_notebook, showfrom bokeh.layouts import gridplot #firstly import gridplotoutput_notebook()from random import seedfrom random import randintseed(1)x_value=[]for i in range(20):x_value.append(i) #fill x with random values.y_one = [x**0.5 for x in x_value] #sqrt(x)y_two = [x**2 for x in x_value] #x^2# gridplot to show graphs of x^2 and sqrt(x)# paramters of figure# plot_width - The width of the solution space for plotting.# plot_height - The height of the solution space for plotting.# title - This refers to the main heading of our graph.# x_axis_label - This shows what does x-axis represent.# y_axis_label - This shows what does y-axis represent.p1 = figure(title="Bokeh Grid plot Example", x_axis_label='x_value', y_axis_label='y_value',plot_width=500, plot_height=500)p1.circle(x_value,y_one,size=14,color='red')p2 = figure(title="Bokeh Grid plot Example", x_axis_label='x_value', y_axis_label='y_value',plot_width=500, plot_height=500)p2.circle(x_value,y_two,size=14, color='blue')p3 = gridplot([[p1,p2]], toolbar_location=None)show(p3)#Comparison of two plots shown as a grid plot.

For this code, x and y are the data points on the x and y-axis. The `figure`

function creates a space for the data to be plotted. The `.circle`

functions draws the co-ordinates that have a circular shape. These functions have several parameters, but for this example, we have used `color`

and `size`

. `Color`

refers to the color of the co-ordinate (in order to differentiate between two different datasets, we have written `color='blue'`

and `color = 'red'`

). `Size`

refers to the size of the co-ordinates that are to be plotted. The `gridplot`

functions draws all these graphs alongside each other. This grid plot shows two plots in a single figure, `y=x^2`

and `y=sqrt(x)`

. These graphs can be visualized together, which makes it easier to differentiate them.

For Further Understanding:

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