Delete app2.py

app2.py

@@ -1,55 +0,0 @@
-import yfinance as yf
-import pandas as pd
-import plotly.graph_objects as go
-import streamlit as st
-
-# Sidebar inputs for stock symbol
-sidebar = st.sidebar
-symbol = sidebar.text_input("Enter stock symbol:", "AAPL")
-data = yf.download(symbol, start="2020-01-01", end="2021-01-01")
-
-# Check if data is empty
-if data.empty:
-    st.error("No data available for the selected symbol. Please try another symbol.")
-else:
-    # Determine the valid date range for Fibonacci analysis
-    min_date, max_date = data.index.min().date(), data.index.max().date()
-
-    # Dynamic default dates based on data range
-    default_start, default_end = min_date, max_date
-
-    # Sidebar inputs for Fibonacci time frame
-    fib_start_date = sidebar.date_input("Fibonacci Start Date", value=default_start, min_value=min_date, max_value=max_date)
-    fib_end_date = sidebar.date_input("Fibonacci End Date", value=default_end, min_value=min_date, max_value=max_date)
-
-    if fib_start_date >= fib_end_date:
-        st.error("Error: The start date must be before the end date.")
-    else:
-        # Filter data for Fibonacci analysis
-        fib_data = data.loc[fib_start_date:fib_end_date]
-
-        # Calculate high and low prices for Fibonacci levels
-        high_price = fib_data['High'].max()
-        low_price = fib_data['Low'].min()
-
-        # Fibonacci retracement levels
-        fib_levels = [0, 0.236, 0.382, 0.5, 0.618, 0.786, 1]
-        price_diff = high_price - low_price
-
-        # Initialize figure for plotting
-        fig = go.Figure()
-
-        # Plot close prices and moving averages
-        fig.add_trace(go.Scatter(x=data.index, y=data['Close'], name='Close Price', line=dict(color='black')))
-        for ma in [20, 50, 200]:
-            ma_label = f"MA{ma}"
-            data[ma_label] = data['Close'].rolling(window=ma).mean()
-            fig.add_trace(go.Scatter(x=data.index, y=data[ma_label], name=ma_label, line=dict(width=2)))
-
-        # Plot Fibonacci levels
-        for level in fib_levels:
-            value = high_price - (price_diff * level)
-            fig.add_hline(y=value, line_dash="dot", annotation_text=f"{level*100}%", annotation_position="right")
-
-        # Display chart
-        st.plotly_chart(fig)