stockport9 / app.py
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Update app.py
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import gradio as gr
import yfinance as yf
from prophet import Prophet
import pandas as pd
import plotly.graph_objects as go
def download_data(ticker, start_date='2010-01-01'):
data = yf.download(ticker, start=start_date)
if data.empty:
raise ValueError(f"No data returned for {ticker}")
data.reset_index(inplace=True)
if 'Adj Close' in data.columns:
data = data[['Date', 'Adj Close']].copy()
data.rename(columns={'Date': 'ds', 'Adj Close': 'y'}, inplace=True)
else:
raise ValueError("Expected 'Adj Close' in columns")
data['ds'] = pd.to_datetime(data['ds'])
return data
def predict_future_prices(ticker, periods=1825):
data = download_data(ticker)
model = Prophet(daily_seasonality=False, weekly_seasonality=True, yearly_seasonality=True)
model.fit(data)
future = model.make_future_dataframe(periods=periods, freq='D')
forecast = model.predict(future)
fig = go.Figure()
fig.add_trace(go.Scatter(x=data['ds'], y=data['y'], mode='lines', name='Actual (Black)', line=dict(color='black')))
fig.add_trace(go.Scatter(x=forecast['ds'], y=forecast['yhat'], mode='lines', name='Forecast (Blue)'))
# Make sure to return both the figure and the forecast data
return fig, forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']]
with gr.Blocks() as app:
with gr.Row():
ticker_input = gr.Textbox(value="AAPL", label="Enter Stock Ticker for Forecast")
periods_input = gr.Number(value=1825, label="Forecast Period (days)")
forecast_button = gr.Button("Generate Forecast")
forecast_chart = gr.Plot(label="Forecast Chart")
forecast_data = gr.Dataframe(label="Forecast Data")
forecast_button.click(
fn=predict_future_prices,
inputs=[ticker_input, periods_input],
outputs=[forecast_chart, forecast_data]
)
app.launch()