Web scraped S&P 500 Data from Wikipedia using Pandas and performed Exploratory Data Analysis on the data.

Overview

Web application to explore the S&P500 Stocks

A real time deployed web application that is built using data, scraped from Wikipedia, that explores S&P500 Companies and their stock details. You can also view the different sector of companies and can sort the companies according to the sectors. You can also download the data of the companies in csv format for your future uses. Plesae this repository if you found it useful.

Technologies Used :

  • Python
  • Streamlit
  • Matplotlib
  • Pandas
  • base64
  • YFinance (For getting Stock data of the companies)

Preview

S&P-01|635x380 S&P500-02|635x380

Installation :

A good practice to start with a new project and use it, is to make a virtual enviornment for the particular project. Here is the steps for making virtual enviornment ::

  1. pip install virtualenv
  2. python -m virtualenv myenv

Install the dependencies of the App ::

Run commands on python terminal or anaconda terimial or any terminal you are using in your system.

  • pip install -r requirements.txt

Test :

  • Run streamlit run app.py.
  • The app will be up and running at the following URL http://localhost:8501/
  • Now explore the app

Deployed Version

Hope you like this project !!!

Owner
Samrat Mitra
Aspiring Data Scientist | Community member @EddieHubCommunity, @web3community, @Collective | Research interest in Deep Learning and Computer Vision, NLP
Samrat Mitra
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