Monetizing Machine Learning: Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud

© Manuel Amunategui, Mehdi Roopaei 2018

Manuel Amunategui and Mehdi RoopaeiMonetizing Machine Learninghttps://doi.org/10.1007/978-1-4842-3873-8_9

9. Case Study Part 2: Displaying Dynamic Charts

Manuel Amunategui¹  and Mehdi Roopaei²

(1)

Portland, Oregon, USA

(2)

Platteville, Wisconsin, USA

 

Displaying dynamic stock charts on PythonAnywhere.

Let’s add a few more features to the original case study web application (make sure you are familiar with “Running on PythonAnywhere” in Chapter 5). The idiom “a picture is worth a thousand words” is absolutely applicable here and by offering visual chart support of the price action surrounding the recommended pair trade, will go a long way to help the user evaluate things. We will add three charts (Figure 9-1), a ...