Create app.py

app.py

@@ -0,0 +1,49 @@
+import yfinance as yf
+import pandas as pd
+import streamlit as st
+import plotly.graph_objs as go
+
+# Function to load data with the updated cache method
+@st.cache_data
+def load_data(ticker):
+    data = yf.download(ticker, start='2020-01-01', end='2023-01-01')
+    data.reset_index(inplace=True)
+    return data
+
+def calculate_moving_averages(data, window):
+    data[f'MA{window}'] = data['Close'].rolling(window=window).mean()
+    return data
+
+def main():
+    st.title("FinanceTracker: Financial Dashboard")
+    st.sidebar.title("Settings")
+
+    # User input for ticker symbol
+    ticker = st.sidebar.text_input("Ticker Symbol", "AAPL")
+
+    # Load data
+    data = load_data(ticker)
+
+    # User input for moving average window
+    ma_window = st.sidebar.slider("Moving Average Window", 5, 100, 20)
+    data = calculate_moving_averages(data, ma_window)
+
+    # Plotting the data
+    fig = go.Figure()
+    fig.add_trace(go.Scatter(x=data['Date'], y=data['Close'], mode='lines', name='Close'))
+    fig.add_trace(go.Scatter(x=data['Date'], y=data[f'MA{ma_window}'], mode='lines', name=f'MA{ma_window}'))
+
+    st.plotly_chart(fig)
+
+    # Additional metrics and analysis
+    st.write(f"### {ticker} Data Summary")
+    st.write(data.describe())
+
+    st.write(f"### {ticker} Close Price")
+    st.line_chart(data['Close'])
+
+    st.write(f"### {ticker} Volume")
+    st.line_chart(data['Volume'])
+
+if __name__ == "__main__":
+    main()