Create app.py

app.py

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+import streamlit as st
+import yfinance as yf
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+# Function to fetch data from Yahoo Finance
+def fetch_data(symbols, start_date, end_date):
+    data = yf.download(symbols, start=start_date, end=end_date)
+    return data['Adj Close']
+
+# Function to plot line chart
+def plot_line_chart(data, title):
+    st.write("##", title)
+    st.line_chart(data)
+
+# Function to calculate correlation matrix and plot heatmap
+def plot_correlation(data):
+    st.write("## Correlation Matrix")
+    correlation_matrix = data.corr()
+    sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt=".2f")
+    st.pyplot()
+
+# Streamlit App
+def main():
+    st.title("Financial Data Analysis App")
+    st.write("This app fetches data from Yahoo Finance, plots charts, and calculates correlations.")
+
+    # Input for symbols
+    symbols_input = st.text_input("Enter symbols separated by commas (e.g., AAPL, MSFT, GOOGL)", "AAPL, MSFT, GOOGL")
+    symbols = [symbol.strip() for symbol in symbols_input.split(',')]
+
+    # Fetch data
+    if st.button("Fetch Data"):
+        st.write("Fetching data...")
+        try:
+            data = fetch_data(symbols, pd.Timestamp.now() - pd.DateOffset(years=15), pd.Timestamp.now())
+            st.success("Data fetched successfully!")
+            
+            # Plot line charts
+            for symbol in symbols:
+                plot_line_chart(data[symbol], f"Adjusted Close Price for {symbol}")
+
+            # Plot correlation matrix
+            plot_correlation(data)
+
+        except Exception as e:
+            st.error(f"Error fetching data: {e}")
+
+if __name__ == "__main__":
+    main()