Streamlit STOCK dashboard using Python 🔴

Introduction

In this tutorial, you will learn how to build a stock dashboard using Streamlit and Python. This dashboard will enable you to visualize stock prices, analyze fundamental data, and access stock news. Streamlit is an open-source app framework that simplifies the creation of web applications, making it an excellent choice for data-driven projects in finance.

Step 1: Set Up Your Streamlit Environment

1. Install Streamlit:

   • Open your terminal or command prompt.
   • Run the following command to install Streamlit:

     pip install streamlit
     

2. Create a New Python File:

   • Create a new directory for your project.
   • Inside this directory, create a Python file (e.g., stock_dashboard.py).

3. Launch Streamlit:

   • Navigate to your project directory in the terminal.
   • Run the following command to start the Streamlit app:

     streamlit run stock_dashboard.py
     

Step 2: Extract Stock Prices Using yfinance

1. Install yfinance:

   • In your terminal, run:

     pip install yfinance
     

2. Import yfinance in Your Script:

   • Add the following import statement at the top of your Python file:

     import yfinance as yf
     

3. Fetch Stock Data:

   • Create a function to fetch stock prices:

     def get_stock_data(ticker):
         stock = yf.Ticker(ticker)
         return stock.history(period="1d")
     

Step 3: Create Dashboard Tabs

1. Import Streamlit Components:

   • At the top of your Python file, import Streamlit:

     import streamlit as st
     

2. Set Up Tabs:

   • Use Streamlit's st.tabs() function to create tabs for pricing, fundamentals, and news:

     tabs = st.tabs(["Pricing", "Fundamentals", "News"])
     

Step 4: Implement Stock Price Analysis

1. Display Stock Prices:
   • In the "Pricing" tab, fetch and display stock prices:

     with tabs[0]:
         ticker = st.text_input("Enter Stock Ticker")
         if ticker:
             data = get_stock_data(ticker)
             st.line_chart(data['Close'])
     

Step 5: Fetch Fundamental Data Using Alpha Vantage

1. Sign Up for Alpha Vantage:

   • Create an account at Alpha Vantage to obtain your API key.

2. Install Alpha Vantage Library:

   • Run the following command:

     pip install alpha-vantage
     

3. Fetch Fundamental Data:

   • Add code to retrieve and display fundamental data:

     from alpha_vantage.fundamentaldata import FundamentalData
     
     def get_fundamental_data(ticker, api_key):
         fd = FundamentalData(key=api_key, output_format='pandas')
         data, _ = fd.get_company_overview(ticker)
         return data
     

4. Display Fundamental Data:

   • In the "Fundamentals" tab, call the get_fundamental_data function and display the results.

Step 6: Implement Stock News Analysis

1. Install Stocknews API:

   • Run the following command:

     pip install stocknews
     

2. Fetch Stock News:

   • Use the Stocknews API to retrieve news articles related to the stock:

     from stocknews import StockNews
     
     def get_stock_news(ticker):
         sn = StockNews(ticker)
         return sn.get_news()
     

3. Display News Articles:

   • In the "News" tab, call the get_stock_news function and display the articles.

Conclusion

You have successfully built a stock dashboard using Streamlit and Python. This dashboard allows you to analyze stock prices, fundamental data, and news, providing valuable insights into stock performance.

Next Steps

• Explore additional features like sentiment analysis for news articles.
• Consider deploying your Streamlit app using platforms like Streamlit Sharing or Heroku.
• Experiment with different stock tickers and settings to enhance your dashboard.