This repo contains the Jupyter notebook and Python script with the full code for my "Python for Finance: Plotly Dash" 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.

1. Medium: https://towardsdatascience.com/python-for-finance-dash-by-plotly-ccf84045b8be
2. Personal blog: https://kdboller.github.io/2018/07/13/python-for-finance-plotly-dash.html

1. Clone this repository: git clone https://github.com/kdboller/pythonsp500-plotly-dash; 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.

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.

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.

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].