app.py

import gradio as gr
import yfinance as yf
import pandas as pd

# Mapping company names to their ticker symbols
company_dict = {
    "Apple": "AAPL",
    "Google": "GOOGL",
    "Microsoft": "MSFT",
    "Amazon": "AMZN",
    "Tesla": "TSLA"
}

# Function to fetch ESG data for the selected company
def fetch_esg_data(company_name):
    ticker = company_dict[company_name]
    stock = yf.Ticker(ticker)
    esg_data = stock.sustainability

    if esg_data is not None and not esg_data.empty:
        esg_df = pd.DataFrame(esg_data)
        esg_scores = esg_df.loc[["environmentScore", "socialScore", "governanceScore"], :].dropna().astype(float)
        
        plot_df = pd.DataFrame({
            "ESG Category": ["Environment", "Social", "Governance"],
            "Score": esg_scores.squeeze().values
        })
        
        # Save the ESG data to a CSV file
        csv_filename = f"{ticker}_esg_data.csv"
        esg_df.to_csv(csv_filename)

        return plot_df, csv_filename
    else:
        return pd.DataFrame(), None

# Gradio interface
def app_interface():
    with gr.Blocks() as app:
        # Dropdown to select company name
        company = gr.Dropdown(
            label="Select Company",
            choices=list(company_dict.keys()),
            value="Apple",  # Default value
            interactive=True  # Make it interactive
        )
        
        # Button to fetch and plot ESG data
        plot_button = gr.Button("Generate ESG Plot")
        
        # LinePlot component for displaying the ESG data
        line_plot = gr.LinePlot(label="ESG Scores Line Plot", x="ESG Category", y="Score", overlay_point=True)
        
        # ScatterPlot component for displaying the ESG data
        scatter_plot = gr.ScatterPlot(label="ESG Scores Scatter Plot", x="ESG Category", y="Score", overlay_point=True)
        
        # File output for CSV download
        csv_output = gr.File(label="Download CSV")

        # Define the action when the "Generate ESG Plot" button is clicked
        plot_button.click(fn=fetch_esg_data, inputs=company, outputs=[line_plot, csv_output, scatter_plot])

    return app

# Launch the Gradio app
app = app_interface()
app.launch()