Update app.py

app.py

@@ -3,7 +3,7 @@
 import streamlit as st
 import pandas as pd
 import numpy as np
-# import plotly.express as px
+import plotly.express as px
 
 import os
 import time
@@ -100,19 +100,12 @@ def get_options_merge(current_datetime):
 DF_options, tickerlst = get_options_merge(current_datetime)
 
 
-
-
-
-
 # Title
-st.title("📊 Options Data Dashboard")
-
-
+st.title("📊 Unusual Options Activity Dashboard")
 
 st.write(f'Number of avialable tickers: {len(tickerlst)}')
 
-
-st.write(f'Number of options records: {len(DF_options)}')
+st.write(f'Number of options contract records: {len(DF_options)}')
 
 # Display options data
 st.header("Options Data")
@@ -120,56 +113,118 @@ st.header("Options Data")
 # Sidebar
 st.sidebar.header("Controls")
 st.sidebar.markdown("### Filter Options Data")
-# Add volume and open interest filters in sidebar
-min_volume = st.sidebar.number_input("Minimum Volume", min_value=0, value=100)
-min_open_interest = st.sidebar.number_input("Minimum Open Interest", min_value=0, value=100)
-min_vol_oi_ratio = st.sidebar.number_input("Minimum Volume/Open Interest Ratio", min_value=0.0, value=0.5, step=0.1)
 
+# Change number inputs to range sliders for volume and open interest
+volume_range = st.sidebar.slider(
+    "Volume Range",
+    min_value=0,
+    max_value=DF_options['volume'].max().astype(int),
+    value=(0, DF_options['volume'].max().astype(int) ),
+    step=100
+)
+
+open_interest_range = st.sidebar.slider(
+    "Open Interest Range", 
+    min_value=0,
+    max_value=DF_options['openInterest'].max().astype(int),
+    value=(0, DF_options['openInterest'].max().astype(int) ),
+    step=100
+)
+
+# Add range selector for Volume/Open Interest Ratio
+vol_oi_ratio_range = st.sidebar.slider(
+    "Volume/Open Interest Ratio Range",
+    min_value=0.0,
+    max_value=np.nanmax(DF_options['Volume_OpenInterest_Ratio'][~np.isinf(DF_options['Volume_OpenInterest_Ratio'])]),
+    value=(0.5, np.nanmax(DF_options['Volume_OpenInterest_Ratio'][~np.isinf(DF_options['Volume_OpenInterest_Ratio'])])/2),
+    step=0.1
+)
 
 st.sidebar.markdown("---")  # Add a horizontal line as a visual separator
 
 st.sidebar.markdown("### Filter Stock Data")
 min_relative_volume = st.sidebar.number_input("Minimum Relative Volume", min_value=0.0, value=1.5, step=0.1)
-min_put_call_volume = st.sidebar.number_input("Minimum Put/Call Volume Ratio", min_value=0.0, value=0.0, step=0.1)
-min_put_call_oi = st.sidebar.number_input("Minimum Put/Call OI Ratio", min_value=0.0, value=0.0, step=0.1)
-
-# Filter the dataframe
-filtered_df = DF_options[
-    (DF_options['volume'] >= min_volume) & 
-    (DF_options['openInterest'] >= min_open_interest) &
-    (DF_options['Relative Volume'] >= min_relative_volume) &
-    (DF_options['Put_Call_Volume_Ratio'] >= min_put_call_volume) &
-    (DF_options['Put_Call_OI_Ratio'] >= min_put_call_oi) &
-    (DF_options['Volume_OpenInterest_Ratio'] >= min_vol_oi_ratio)
-]
-
-st.write(f"Filtered records: {len(filtered_df)} rows")
-
 
-interestedColumns = ['contractSymbol' , 'volume', 'openInterest', 'impliedVolatility', 'Volume_OpenInterest_Ratio' , 'Relative Volume' , 'Put_Call_Volume_Ratio' , 'Put_Call_OI_Ratio' , ]
+# Changed to range sliders
+put_call_volume_range = st.sidebar.slider(
+    "Put/Call Volume Ratio Range",
+    min_value=0.0,
+    max_value=10.0,
+    value=(0.0, 0.6),
+    step=0.1
+)
 
-selected_columns = st.multiselect(
-    "Select columns to display",
-    options=filtered_df.columns.tolist(),
-    default=interestedColumns
+put_call_oi_range = st.sidebar.slider(
+    "Put/Call OI Ratio Range",
+    min_value=0.0,
+    max_value=10.0,
+    value=(0.0, 3.0),
+    step=0.1
 )
 
-if selected_columns:
-    st.dataframe(filtered_df[selected_columns])
+if st.sidebar.button("Filter"):
+# Filter the dataframe with the range
+    filtered_df = DF_options[
+        (DF_options['volume'] >= volume_range[0]) & 
+        (DF_options['volume'] <= volume_range[1]) &
+        (DF_options['openInterest'] >= open_interest_range[0]) &
+        (DF_options['openInterest'] <= open_interest_range[1]) &
+        (DF_options['Relative Volume'] >= min_relative_volume) &
+        (DF_options['Put_Call_Volume_Ratio'] >= put_call_volume_range[0]) &
+        (DF_options['Put_Call_Volume_Ratio'] <= put_call_volume_range[1]) &
+        (DF_options['Put_Call_OI_Ratio'] >= put_call_oi_range[0]) &
+        (DF_options['Put_Call_OI_Ratio'] <= put_call_oi_range[1]) &
+        (DF_options['Volume_OpenInterest_Ratio'] >= vol_oi_ratio_range[0]) &
+        (DF_options['Volume_OpenInterest_Ratio'] <= vol_oi_ratio_range[1])
+    ]
+
+    st.write(f"Filtered records: {len(filtered_df)} rows")
+
+    interestedColumns = ['contractSymbol' , 'volume', 'openInterest', 'impliedVolatility', 'Volume_OpenInterest_Ratio' , 'Relative Volume' , 'Put_Call_Volume_Ratio' , 'Put_Call_OI_Ratio' , ]
+
+    selected_columns = st.multiselect(
+        "Select columns to display",
+        options=filtered_df.columns.tolist(),
+        default=interestedColumns
+    )
+
+    if selected_columns:
+        st.dataframe(filtered_df[selected_columns])
 
 # Download button for the DataFrame
-csv = convert_df(filtered_df)
-st.download_button(
-    label="Download Options Data as CSV",
-    data=csv,
-    file_name=f'options_data_{current_datetime}.csv',
-    mime='text/csv',
-)
+    csv = convert_df(filtered_df)
+    st.download_button(
+        label="Download Options Data as CSV",
+        data=csv,
+        file_name=f'options_data_{current_datetime}.csv',
+        mime='text/csv',
+    )
 
-st.write(f"Filtered Tickers: {filtered_df['Ticker'].unique()} ")
+    st.write(f"Filtered Tickers: {filtered_df['Ticker'].unique()} ")
 
 
 
+st.sidebar.markdown("---")  # Add a horizontal line as a visual separator
+st.sidebar.header("Ticker")
+
+selectedTicker = st.sidebar.selectbox("Select Ticker", options=tickerlst, index=tickerlst.index('AAPL') if 'AAPL' in tickerlst else 0)
+
+if st.sidebar.button("Submit"):
+    st.write(f"Ticker {selectedTicker}")
+    # filter DF_options for selectedTicker
+    filtered_ticker_df = DF_options[DF_options['Ticker'] == selectedTicker]
+    #plot plotly3D scatter plot for filtered_ticker_df for volume, openInterest and impliedVolatility
+    fig = px.scatter_3d(filtered_ticker_df, x='volume', y='openInterest', z='impliedVolatility', color='Type')
+    fig.update_layout(
+        autosize=True,
+        width=2560,
+        height=600,
+        margin=dict(l=50, r=50, b=50, t=50)
+    )
+    st.plotly_chart(fig) #, use_container_width=True)
+    # Display the filtered DataFrame
+    
+    
 
 st.sidebar.markdown("---")  # Add a horizontal line as a visual separator
 st.sidebar.header("Advanced")