Updated README

Author: mayur7garg

README.md

@@ -7,32 +7,63 @@ Easy to follow stock price analysis on Indian stock data with results hosted at
 <summary>Click to expand</summary>
 
 - [Data](#data)
-- [Project Requirements](#project-requirements)
+- [Project Prerequisites](#project-prerequisites)
+- [Usage](#usage)
 - [Notes and Caveats](#notes-and-caveats)
 - [About this project](#about-this-project)
 </details>
 
 ## Data
+
+### Sources
 This project uses historical data acquired from publicly available sources listed below:
 
-1. [NSE India](https://www.nseindia.com/)
-2. [Screener.in](https://www.screener.in/)
+1. [NSE India](https://www.nseindia.com/) - Daily stock prices
+2. [Screener.in](https://www.screener.in/) - Stock PE
+
+### Update schedule
+Stock pricing data is updated 3 times a week for a set of symbols via a [cron workflow](.github/workflows/main.yml) running on GitHub actions.
+
+Updating PE data, however, is a manual process. Hence, PE information is not likely to be correct for recent dates and should not be relied upon.
 
-## Project Requirements
+## Project Prerequisites
 
 ### Docker
-Development of this project was done inside a developmental Docker container using the base image of `Python v3.11.6`. The same environment can be set up using the `docker-compose.yml` available [here](./docker-compose.yml).
+Development of this project was done inside a Docker container using the base image of `Python v3.11.6`. The same environment can be set up using the `docker-compose.yml` available [here](./docker-compose.yml).
+
+If using VS Code or GitHub Codespaces, a developmental container can be instantiated using the [devcontainer.json](.devcontainer/devcontainer.json) file
 
 ### Requirements
 All top level packages used in this project are listed in the [requirements](./requirements.txt) file. This project does not use any niche functionality from any of the listed packages and hence should work with their most recent releases.
 
+## Usage
+
+### Static reports
+This project generates static HTML reports which are hosted using GitHub Pages which can be viewed at [FinancialModelling](https://mayur7garg.github.io/FinancialModelling/).
+
+To regenerate the reports and the associated plots, run the following command:
+```sh
+cd 'Stock Forecasting' && python main.py
+```
+
+Once generated, the reports can be viewed by opening [index.html](index.html) in any web browser.
+
+### Interactive notebook
+An interactive [marimo](https://marimo.io/) notebook has been included which can be run using the following command:
+```sh
+cd 'Stock Forecasting' && marimo run stock_interactive.py
+```
+
 ## Notes and Caveats
-- This project only focuses on day level stock price data and does not factor in intraday price changes.
+- This project is only meant to be educational and analytical purposes and should not be interpreted as a financial advice.
+- This project only focuses on day level stock price data and does not factor in intraday price changes or company fundamentals.
+- Data used in this project is not updated in realtime and may be out of date.
 - Currently, the analysis doesn't factor in stock splits, bonus shares, etc. as structured data for the same is difficult to obtain.
-- This project is only meant to be educational and should not be interpreted as a financial advice.
 
 ## About this project
 
+Feel free to leave a star if you liked this project.
+
 ```bibtex
 @misc{MayurGarg_FinancialModelling,
     title={Financial Modelling},

requirements.txt

@@ -2,5 +2,6 @@ ipykernel
 marimo[sql]
 pandas
 pyarrow
+requests
 seaborn
 scikit-learn