New

app.py

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+import gradio as gr
+import pandas as pd
+import numpy as np
+import yfinance as yf
+from prophet import Prophet
+from prophet.plot import plot_plotly, plot_components_plotly
+
+
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+
+stocks = pd.read_excel('Stocks.xlsx', usecols =[1,2,3])
+
+period_options = {
+    "1wk": "1 Week",
+    "1mo": "1 Month",
+    "1y": "1 Year",
+    "5y": "5 Years"
+}
+
+
+# Create a Gradio radio button group for the period
+period = gr.Radio(label="Training Period: ", choices=list(period_options.values()), value="1 Week")
+
+
+# Define the function to return the symbol corresponding to the selected company name
+def get_forecast(company_name):
+    symbol_nse = stocks[stocks['Company Name'] == company_name]['Symbol'].values[0] + '.NS'
+    #period_key = [key for key, value in period_options.items() if value == period][0]
+    #stock_df = yf.download(symbol_nse, period = period_key)
+    
+    stock_df = yf.download(symbol_nse, period = '5y')
+    stock_df.drop(stock_df.columns[[0,1,2,4,5]], axis=1, inplace=True)
+    stock_df.reset_index(inplace=True)
+    stock_df.columns = ['ds', 'y']
+    #stock_df = stock_df[['ds', 'y', 'cap']]
+    
+    #model = Prophet(growth='logistic')
+    model = Prophet()
+    model.fit(stock_df)
+    
+    future = model.make_future_dataframe(periods = 7)
+    forecast = model.predict(future)
+    forecast_df = forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']]
+    
+    fig = plot_plotly(model, forecast_df)
+    fig.update_layout(xaxis_title="Date", yaxis_title="Price")
+    
+    return fig
+
+
+with gr.Blocks() as demo:
+    
+    gr.Markdown(
+        """
+        # NSE Stock Price Trend Prediction
+        Select the Stock from Dropdown Menu to get next week Prediction
+        
+        """
+        
+    )
+    with gr.Row():
+        dropdown = gr.Dropdown(label="Company Name", choices=stocks['Company Name'].tolist(), filterable = True, info = 'Select NSE Stock')
+    
+    with gr.Row():
+        with gr.Column():
+            None
+        with gr.Column():
+            None
+        with gr.Column():
+            None
+        with gr.Column():    
+            submit_btn = gr.Button(value = "Predict")
+    
+    with gr.Row():
+        forecast_plot = gr.Plot(label = 'Forecast Plot')
+    
+    
+    submit_btn.click(get_forecast, inputs=dropdown, outputs=forecast_plot)            
+    
+      
+demo.launch(share=True, debug=True)