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Welcome to the Streamlit-Stock-Fundamentals-App wiki!
- In this study, we will walk through the streamlit stock fundamental analysis app based on the published tutorial and open-source code.
- Referring to our recent study, the NVIDIA’s AI-powered earnings and revenues remain our key focus area that falls under the umbrella of fintech.
- Indeed, as US Tech stocks continue to set new high after new high, many investors are questioning whether we have reached “bubble” territory. There has been debate over whether the current valuations are justified, whether the impressive earnings growth can persist.
- Let’s delve into the specifics of the streamlit application itself.
- Copying the CSS style file to the working directory YOURPATH.
- Installing the required libraries
!pip install streamlit, yfinance
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Creating the Python script Create stock_fundamentals_screen.py in YOURPATH
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Running the above script from the cmd prompt as follows
streamlit run stock_fundamentals_screen.py
- Follow the link below
You can now view your Streamlit app in your browser.
Local URL: http://localhost: Network URL: http://
- The following menu should appear in your browser
- This quick demo shows that the proposed streamlit UI provides easy-to-follow access to real-time financial data via yfinance.
- Today we have demonstrated how to build and launch the Stock Search Web App.
- We have used this App to examine the latest NVDA stock price and financial health.
- Next steps will focus on the implementation of “Quarterly Earnings” and “Analysts Recommendation”.
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