/pythonsp500-robo-advisor-edition

Repo with all files and data needed for Python for Financial Analyses, Robo Advisor edition.

Primary LanguageJupyter Notebook

pythonsp500-robo-advisor-edition

Repo with all files and data needed for Python for Financial Analyses, Robo Advisor edition.

Summary

This repo contains the Jupyter notebook and Python script with the full code for my "Python for Finance: Robo Advisor Edition" post, as well as the excel file initially read in as the sample portfolio, using pandas, and the csv files generated from the Jupyter notebook. Using a virtual environment, Python 3.6, and the libraries listed in the requirements.txt file, you can run a Plotly Dash dashboard locally based on the csv files generated from the Jupyter notebook.

To recreate the entire analysis, I recommend setting up a virtual environment (described below), loading the requirements.txt file into the virtual environment (also described below), and pip install or conda install any additional packages -- the explanations for how to accomplish all of this should either be described below or provided in the virtual environment link below.

Relevant posts where you can find the tutorial

  1. Medium: https://towardsdatascience.com/python-for-finance-robo-advisor-edition-36571e0fd48e
  2. Personal blog: https://kdboller.github.io/2019/04/06/python-for-finance-robo-advisor-edition.html

Getting set up

  1. Clone this repository: https://github.com/kdboller/pythonsp500-robo-advisor-edition; or
  2. Hit 'Clone or download' on the main repo page in order to grab the Jupyter notebook, python script and the sample excel file.

Note on Anaconda distribution and Python Notebook

I highly recommend that you download the Anaconda distribution. You can also run the notebook without Anaconda using pip to install the required packages, however Anaconda is the industry standard for data science.

Python Version and Virtual Environments

It is recommended that you have Python 3.6 or greater so that you can run the Plotly Dashboard locally with the provided csv files.

I strongly recommend setting up a virtual environment. I manage all of my virtual environments with Anaconda.

Here is a very thorough explanation on how to set up virtual environments within Anaconda.

Requirements

For any packages not distributed under Anaconda, e.g., the Yahoo Finance package fix, you can do the following in your virtual environment: pip install [name of package].