This workflow takes as input a list of stock symbols from Yahoo Finance. Afer some preprocessing to determine the date range, this information is sent to the pandas webreader library (through the Python Source node) to collect (near) realtime stock information. The information is sent to the modelling workflow (through the Call Workflow node) where feature creation, model estimation and prediction takes place for each stock symbol. This workflow collects the predictions and the reliability of the model and displays the expected percentage change in value for each stock symbol visually. Note: To use this workflow you need to have Python and the following libraries installed on your machine: -pandas as pd -pandas-datareader -datetime

This is a companion discussion topic for the original entry at https://kni.me/w/BbkpJoYEXRj5S34p
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Hello, this looks fun, thanks for posting.

I’m curious about the “modeling workflow” because it does not appear to be available. It would be cool to understand more about the python, without having to download the workflow, and I believe a lot of people will be able to gain value from this by being able to read the code associated to the solution.

Hope this feedback helps.

Best, T