Create app.py
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import streamlit as st
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# Tickers to choose from
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tickers = ['AAPL', 'AMZN', 'NIO', 'AMD', 'NVDA', 'META', 'PLUG', 'INTC', 'FORD', 'TSLA', 'GOOGL']
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# Image options for each ticker
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image_options = {
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'AAPL': 'AAPL.jpg',
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'AMZN': 'AMZN.jpg',
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'NIO': 'NIO.jpg',
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'AMD': 'AMD.jpg',
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'NVDA': 'NVDA.jpg',
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'META': 'META.jpg',
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'PLUG': 'PLUG.jpg',
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'INTC': 'INTC.jpg',
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'FORD': 'FORD.jpg',
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'TSLA': 'TSLA.jpg',
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'GOOGL': 'GOOGL.jpg',
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}
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# Stock names for each ticker
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stock_names = {
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'AAPL': 'Apple Inc.',
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'AMZN': 'Amazon.com Inc.',
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'NIO': 'NIO Inc.',
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'AMD': 'Advanced Micro Devices Inc.',
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'NVDA': 'NVIDIA Corporation',
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'META': 'Meta Platforms Inc.',
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'PLUG': 'Plug Power Inc.',
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'INTC': 'Intel Corporation',
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'FORD': 'Ford Motor Company',
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'TSLA': 'Tesla Inc.',
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'GOOGL': 'Alphabet Inc. (Google)',
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}
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st.title("Stock Forecaster")
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# Create a dropdown to select a ticker
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selected_ticker = st.selectbox("Select a ticker:", tickers)
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# Display the image for the selected ticker
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if selected_ticker:
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image_path = image_options[selected_ticker]
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image = st.image(image_path)
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# Display the stock name for the selected ticker
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stock_name = stock_names[selected_ticker]
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st.write(f"Stock name: {stock_name}")
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st.markdown("This app has been trained on the past 6 years of data until November 22nd, 2023 for each of the selected stocks. For a more comprehensive analysis with a different date range, access to thousands of stocks, hundreds of cryptocurrencies, and more up-to-date predictions, please visit our website: https://stock.quu.fr")
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