Update app.py

app.py

@@ -0,0 +1,211 @@
+import streamlit as st
+import pandas as pd
+import plotly.express as px
+import plotly.graph_objects as go
+from plotly.subplots import make_subplots
+
+default_start_date = pd.to_datetime('2020-11-02')
+date_limit = pd.to_datetime('2021-08-12')
+
+st.title("Stock Analysis Dashboard")
+
+# Load data
+data_file_path = r"C:\Niki\Study\MSDS\AI Challenge\technicalRecommendation.csv"  # Update this with your file path
+data = pd.read_csv(data_file_path)
+# Convert 'Date' column to datetime format
+data['Date'] = pd.to_datetime(data['Date'])
+print(data.shape, data.columns)
+market_analysis, news_analysis, trade_recs = st.tabs(["Market Analysis", "News Analysis", "Trading Recommendations"])
+
+with market_analysis:
+    st.header("Market Analysis")
+    start_date = st.sidebar.date_input('Start Date', value=default_start_date, min_value=data['Date'].min(), max_value=date_limit)
+    end_date = st.sidebar.date_input("End Date", value=date_limit, min_value=data['Date'].min(), max_value=date_limit)
+    start_date = pd.to_datetime(start_date)
+    end_date = pd.to_datetime(end_date)
+    data2 = data[data['Date'].between(start_date, end_date)]
+
+    # Dropdown for selecting the indicator
+    selected_indicator = st.sidebar.selectbox("Select an Indicator", ['EMA 9', 'EMA 55', 'MACD', 'RSI'])
+    # Dropdown for selecting the Number of Signal Days
+    num_signals = st.sidebar.selectbox("Signals to Show", ['None', 'All', 'Last 5 Days', 'Last 15 Days', 'Last 20 Days'])
+    
+    if selected_indicator == 'EMA 9':
+        # Plot close price and EMA 9
+        fig = px.line(data2, x='Date', y=['Close_price', 'EMA_9'], title='Close Price vs EMA 9',
+                    labels={'Date': 'Date', 'value': 'Price', 'variable': 'Type'})
+        fig.update_traces(selector=dict(type='scatter'))
+        ema9_signal = 'EMA9_Signal'
+        # Plot ‘strong buy’ signals
+        if num_signals != 'None':
+            if num_signals == 'All':
+                strong_buy_dates = data2[data2[ema9_signal] == 3.0]
+            elif num_signals == 'Last 5 Days':
+                last5 = data2.tail(5)
+                strong_buy_dates = last5[last5[ema9_signal] == 3.0]
+            elif num_signals == 'Last 15 Days':
+                last15 = data2.tail(15)
+                strong_buy_dates = last15[last15[ema9_signal] == 3.0]
+            elif num_signals == 'Last 20 Days':
+                last20 = data2.tail(20)
+                strong_buy_dates = last20[last20[ema9_signal] == 3.0]
+
+            fig.add_scatter(x=strong_buy_dates['Date'], y=strong_buy_dates['EMA_9'], mode='markers', marker=dict(symbol='triangle-up', size=10, color='green'), name='Strong buy')
+
+        # Plot ‘strong sell’ signals
+        if num_signals != 'None':
+            if num_signals == 'All':
+                strong_sell_dates = data2[data2[ema9_signal] == -3.0]
+            elif num_signals == 'Last 5 Days':
+                last5 = data2.tail(5)
+                strong_sell_dates = last5[last5[ema9_signal] == -3.0]
+            elif num_signals == 'Last 15 Days':
+                last15 = data2.tail(15)
+                strong_sell_dates = last15[last15[ema9_signal] == -3.0]
+            elif num_signals == 'Last 20 Days':
+                last20 = data2.tail(20)
+                strong_sell_dates = last20[last20[ema9_signal] == -3.0]
+
+            fig.add_scatter(x=strong_sell_dates['Date'], y=strong_sell_dates['EMA_9'], mode='markers', marker=dict(symbol='triangle-down', size=10, color='red'), name='Strong sell')
+
+        st.plotly_chart(fig)
+    
+    elif selected_indicator == 'EMA 55':
+        # Plot close price and EMA 9
+        fig = px.line(data2, x='Date', y=['Close_price', 'EMA_55'], title='Close Price vs EMA 9',
+                    labels={'Date': 'Date', 'value': 'Price', 'variable': 'Type'})
+        fig.update_traces(selector=dict(type='scatter'))
+        ema55_signal = 'EMA55_Signal'
+        # Plot ‘strong buy’ signals
+        if num_signals != 'None':
+            if num_signals == 'All':
+                strong_buy_dates = data2[data2[ema55_signal] == 3.0]
+            elif num_signals == 'Last 5 Days':
+                last5 = data2.tail(5)
+                strong_buy_dates = last5[last5[ema55_signal] == 3.0]
+            elif num_signals == 'Last 15 Days':
+                last15 = data2.tail(15)
+                strong_buy_dates = last15[last15[ema55_signal] == 3.0]
+            elif num_signals == 'Last 20 Days':
+                last20 = data2.tail(20)
+                strong_buy_dates = last20[last20[ema55_signal] == 3.0]
+
+            fig.add_scatter(x=strong_buy_dates['Date'], y=strong_buy_dates['EMA_55'], mode='markers', marker=dict(symbol='triangle-up', size=10, color='green'), name='Strong buy')
+
+        # Plot ‘strong sell’ signals
+        if num_signals != 'None':
+            if num_signals == 'All':
+                strong_sell_dates = data2[data2[ema55_signal] == -3.0]
+            elif num_signals == 'Last 5 Days':
+                last5 = data2.tail(5)
+                strong_sell_dates = last5[last5[ema55_signal] == -3.0]
+            elif num_signals == 'Last 15 Days':
+                last15 = data2.tail(15)
+                strong_sell_dates = last15[last15[ema55_signal] == -3.0]
+            elif num_signals == 'Last 20 Days':
+                last20 = data2.tail(20)
+                strong_sell_dates = last20[last20[ema55_signal] == -3.0]
+
+            fig.add_scatter(x=strong_sell_dates['Date'], y=strong_sell_dates['EMA_55'], mode='markers', marker=dict(symbol='triangle-down', size=10, color='red'), name='Strong sell')
+
+        st.plotly_chart(fig)
+
+    elif selected_indicator == 'MACD':
+        # Set up the figure and subplots
+        macd_signal = 'MACD_Signals'
+
+        fig = make_subplots(rows=2, cols=1)
+        # fig = go.Figure()
+        # Add subplot for Close Price and Signals
+        fig.add_trace(go.Scatter(x=data2['Date'], y=data2['Close_price'], mode='lines', name='Close Price'),
+                        row=1, col=1)
+        if num_signals != 'None':
+            if num_signals == 'All':
+                strong_buy_dates = data2[data2[macd_signal] == 3.0]
+                strong_sell_dates = data2[data2[macd_signal] == -3.0]
+                strong_hold_dates = data2[data2[macd_signal] == 0]
+            elif num_signals == 'Last 5 Days':
+                last5 = data2.tail(5)
+                strong_buy_dates = last5[last5[macd_signal] == 3.0]
+                strong_sell_dates = last5[last5[macd_signal] == -3.0]
+                strong_hold_dates = last5[last5[macd_signal] == 0]
+            elif num_signals == 'Last 15 Days':
+                last15 = data2.tail(15)
+                strong_buy_dates = last15[last15[macd_signal] == 3.0]
+                strong_sell_dates = last15[last15[macd_signal] == -3.0]
+                strong_hold_dates = last15[last15[macd_signal] == 0]
+            elif num_signals == 'Last 20 Days':
+                last20 = data2.tail(20)
+                strong_buy_dates = last20[last20[macd_signal] == 3.0]
+                strong_sell_dates = last20[last20[macd_signal] == -3.0]
+                strong_hold_dates = last20[last20[macd_signal] == 0]
+
+            fig.add_trace(go.Scatter(x=strong_buy_dates['Date'], y=strong_buy_dates['Close_price'], mode='markers', marker=dict(symbol='triangle-up', size=10, color='green'), name='Strong Buy'), row=1, col=1)
+            fig.add_trace(go.Scatter(x=strong_sell_dates['Date'], y=strong_sell_dates['Close_price'], mode='markers', marker=dict(symbol='triangle-down', size=10, color='red'), name='Strong Sell'), row=1, col=1)
+            fig.add_trace(go.Scatter(x=strong_hold_dates['Date'], y=strong_hold_dates['Close_price'], mode='markers', marker=dict(symbol='circle', size=10, color='orange'), name='Strong Sell'), row=1, col=1)
+
+        # Add subplot for MACD
+        # fig2 = go.Figure()
+        fig.add_trace(go.Scatter(x=data2['Date'], y=data2['MACD_12_26_9'], mode='lines', name='MACD', yaxis='y2'), row=2, col=1)
+        fig.add_trace(go.Scatter(x=data2['Date'], y=data2['MACDs_12_26_9'], mode='lines', name='Signal', yaxis='y2'), row=2, col=1)
+        fig.add_trace(go.Bar(x=data2['Date'], y=data2['MACDh_12_26_9'], name='Histogram', yaxis='y2'), row=2, col=1)
+
+        # # Update layout
+        # fig.update_layout(title='MACD Analysis',
+        #                 xaxis=dict(title='Date'),
+        #                 yaxis=dict(title='Close Price', side='left', showgrid=False),
+        #                 yaxis2=dict(title='MACD', side='right', overlaying='y', showgrid=False))
+        fig.update_layout(title='MACD Analysis')
+        st.plotly_chart(fig, use_container_width=True)
+        # st.plotly_chart(fig2, use_container_width=True)
+
+    elif selected_indicator == 'RSI':
+        # Set up the figure
+        fig = go.Figure()
+
+        # Add RSI line
+        fig.add_trace(go.Scatter(x=data2['Date'], y=data2['RSI'], mode='lines', name='RSI'))
+
+        # Add overbought and oversold lines
+        overbought_strong = 70
+        oversold_strong = 30
+        fig.add_shape(type="line", x0=data2['Date'].min(), y0=overbought_strong, x1=data2['Date'].max(), y1=overbought_strong, line=dict(color="red", width=1, dash="dash"), name="Overbought")
+        fig.add_shape(type="line", x0=data2['Date'].min(), y0=oversold_strong, x1=data2['Date'].max(), y1=oversold_strong, line=dict(color="green", width=1, dash="dash"), name="Oversold")
+
+        rsi_signal = 'RSI_Signals'
+        if num_signals != 'None':
+            if num_signals == 'All':
+                strong_buy_dates = data2[data2[rsi_signal] >= 1.0]
+                strong_sell_dates = data2[data2[rsi_signal] <= -1.0]
+                strong_hold_dates = data2[data2[rsi_signal] == 0]
+            elif num_signals == 'Last 5 Days':
+                last5 = data2.tail(5)
+                strong_buy_dates = last5[last5[rsi_signal] >= 1.0]
+                strong_sell_dates = last5[last5[rsi_signal] <= -1.0]
+                strong_hold_dates = last5[last5[rsi_signal] == 0]
+            elif num_signals == 'Last 15 Days':
+                last15 = data2.tail(15)
+                strong_buy_dates = last15[last15[rsi_signal] >= 1.0]
+                strong_sell_dates = last15[last15[rsi_signal] <= -1.0]
+                strong_hold_dates = last15[last15[rsi_signal] == 0]
+            elif num_signals == 'Last 20 Days':
+                last20 = data2.tail(20)
+                strong_buy_dates = last20[last20[rsi_signal] >= 1.0]
+                strong_sell_dates = last20[last20[rsi_signal] <= -1.0]
+                strong_hold_dates = last20[last20[rsi_signal] == 0]
+
+            fig.add_trace(go.Scatter(x=strong_buy_dates['Date'], y=strong_buy_dates['RSI'], mode='markers', marker=dict(symbol='triangle-up', size=10, color='green'), name='Strong Buy'))
+            fig.add_trace(go.Scatter(x=strong_sell_dates['Date'], y=strong_sell_dates['RSI'], mode='markers', marker=dict(symbol='triangle-down', size=10, color='red'), name='Strong Sell'))
+            fig.add_trace(go.Scatter(x=strong_hold_dates['Date'], y=strong_hold_dates['RSI'], mode='markers', marker=dict(symbol='circle', size=10, color='orange'), name='Strong Sell'))
+        
+        fig.update_layout(title='RSI Analysis')
+        st.plotly_chart(fig)
+    # st.write(data2)
+
+with news_analysis:
+    st.header("News Analysis")
+    st.write('data to be added.')
+
+with trade_recs:
+    st.header("Trading Recommendations")
+    st.write('recommendations to be added.')