![]() ![]() The most basic example for that would be to try and draw lines for the equations y = x, y = x^2, and y = x^3. What we've done so far is rather basic, let's now try to make multiple lines/map equations in a single graph. The reset_output method resets the figure ID that the show function currently holds so that a new one can be assigned to it. To resolve that error, run the following code: from otting import reset_output In the image above, you can see the tools on the right side (pan, box zoom, wheel zoom, save, reset, help - from top to bottom) these tools enable you to interact with the graph.Īnother important thing which will come in handy is that after every call to the "show" function if you create a new "figure" object, a subsequent call to the "show" function with the new figure passed as an argument would generate an error. When you run the above script, you should see the following square opening in a new tab of your default browser. If you'd prefer to use a notebook then replace the output_file function with output_notebook in the code throughout this article. You may have noticed in the code that there is an alternative to the output_file function, which would instead show the result in a Jupyter notebook by using the output_notebook function. #square.circle(x, y) # Uncomment this line to add a circle mark on each coordinate # Show plot #output_notebook() # Uncomment this line to use iPython notebook Output_file( 'Square.html', title= 'Square in Bokeh') ![]() # Display the output in a separate HTML file from bokeh.io import output_file, output_notebook The line method then draws a line between our coordinates, which is in the shape of a square. Here we can specify both the X range and Y range of the graph, which we set from 0 to 4, which covers the range of our data. The figure function instantiates a figure object, which stores the configurations of the graph you wish to plot. Here we specify the x and y coordinates for points, which will be followed in sequence when the line is being drawn. Furthermore, there might be 'alternative' or additional functionality that would be commented out, but you can try running it by uncommenting those lines. Note: Comments in the codes throughout this article are very important they will not only explain the code but also convey other meaningful information. In this part, we will be doing some hands-on examples by calling Bokeh library's functions to create interactive visualizations. the version gets printed, then you can go ahead and use bokeh library in your programs. If the above command runs successfully i.e. Simply go to your terminal or command prompt and run this command:Īfter completing this step, run the following command to ensure that your installation was successful: $ bokeh -version Note: If you choose this method of installation, you need to have numpy installed in your system alreadyĪnother method to install Bokeh is through Anaconda distribution. ![]() If you have pip installed in your system, run the following command to download and install Bokeh: $ pip install bokeh ![]() The easiest way to install Boken using Python is through pip package manager. What distinguishes Bokeh from these libraries is that it allows dynamic visualization, which is supported by modern browsers (because it renders graphics using JS and HTML), and hence can be used for web applications with a very high level of interactivity.īokeh is available in R and Scala language as well however, its Python counterpart is more commonly used than others. as they are very popular python libraries for graphics and visualizations. Most of you would have heard of matplotlib, numpy, seaborn, etc. In this tutorial, we're going to learn how to use Bokeh library in Python. ![]()
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