Spaces:
Sleeping
Sleeping
File size: 2,483 Bytes
76ba4f4 2086e56 a8a3333 76ba4f4 a8a3333 76ba4f4 a8a3333 ac0650f 76ba4f4 ac0650f 76ba4f4 ac0650f 76ba4f4 ac0650f 76ba4f4 0919ad9 76ba4f4 0919ad9 76ba4f4 0919ad9 76ba4f4 ac0650f 76ba4f4 ac0650f 76ba4f4 0919ad9 ac0650f 0919ad9 76ba4f4 2086e56 ac0650f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
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):
# Get the ticker symbol from the company name
ticker = company_dict[company_name]
# Fetch ESG data from Yahoo Finance
stock = yf.Ticker(ticker)
esg_data = stock.sustainability
# If ESG data is available, process it into a DataFrame
if esg_data is not None:
esg_df = pd.DataFrame(esg_data)
# Extract only the relevant ESG scores and convert to a DataFrame
esg_scores = esg_df.loc[["environmentScore", "socialScore", "governanceScore"], :].dropna().astype(float)
# Prepare a DataFrame for plotting
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 # Return the plot DataFrame and the CSV filename
else:
# Return an empty DataFrame and None if no data is available
return pd.DataFrame(), None
# Gradio interface with a dropdown for company selection, line plot visualization, and CSV download
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")
# Button to fetch and plot ESG data
plot_button = gr.Button("Generate ESG Plot")
# LinePlot component for displaying the ESG data
plot_output = gr.LinePlot(label="ESG Scores Plot", x="ESG Category", y="Score", overlay_point=True)
# Textbox to display messages
message = gr.Textbox(label="Message", interactive=False)
# 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=[plot_output, csv_output])
return app
# Launch the Gradio app
app = app_interface()
app.launch()
|