pages/comps_data.py

import streamlit as st
import pandas as pd
from streamlit_folium import folium_static
import numpy as np
import folium
import matplotlib.pyplot as plt
import seaborn as sns
from datetime import datetime, timedelta

def main():
    st.set_page_config(initial_sidebar_state="collapsed", layout="wide")
        
    data = {
        "favorite": [True, False, False, True, True, False, False, True],
        'Address': ['Location_A', 'Location_B', 'Location_C', 'Location_D', 'Location_E',
                'Location_F', 'Location_G', 'Location_H'
                ],
        'latitude': np.random.uniform(40.7, 40.8, size=8),  # Assuming latitude range between 40.7 and 40.8
        'longitude': np.random.uniform(-74.0, -73.9, size=8),  # Assuming longitude range between -74.0 and -73.9
        'Match score': [90, 89, 88, 87, 86, 85, 84, 83],
        'Market': ["M1", "M1", "M1", "M1", "M1", "M1", "M1", "M1"],
        'Sub-market': ["S1", "S1", "S1", "S1", "S1", "S1", "S1", "S1"],
        'Lease Date': ["2024/1/1", "2024/1/1", "2024/1/1", "2024/1/1", "2024/1/1", "2024/1/1", "2024/1/1", "2024/1/1"],
        'LSF': [20000, 30000, 20000, 30000, 20000, 30000, 50000, 35000],
        'RSF': [20000, 30000, 20000, 30000, 20000, 30000, 50000, 35000],
        'Rent (NNN)': [11, 11, 11, 12, 12, 12, 12, 15],
        'Year Built': [2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019],
        'Office %': [20, 20, 20, 20, 20, 20, 20, 20],
        'Clear Height':[19, 18, 19, 18, 17, 19, 19, 18],
        'Doors (drive in / Dock)': [2, 2, 2, 2, 2, 2, 2, 2],
        'Lease Term ': [60, 60, 60, 60, 60, 60, 60, 60],
        'Rent (Gross)': [11, 11, 11, 12, 12, 12, 12, 15],
        'TIs ': [1, 1, 1, 1, 1, 1,  1, 1]
    }
    
    # Create DataFrame
    df_data =  pd.DataFrame(data)
    
    
    # df_data_checkbox = df_data.copy()
    # df_data_checkbox.insert(loc=0, column='Select rows', value=[False]*len(df_data))
    
    
    filtered_data2 = df_data[['Address', 'Market', 'Sub-market', 'Lease Date', 'LSF', 'RSF', 'Rent (NNN)', 'Year Built', 'Office %', 'Clear Height', 'Doors (drive in / Dock)', 'Lease Term ', 'Rent (Gross)']]
    filtered_data = pd.concat([filtered_data2])
    
    # Display the filtered data
    col_1_1, col_1_2 = st.columns([2, 1])
    with col_1_1:
        st.write('Comps list:')
        display_df = st.table(filtered_data)
    with col_1_2:
        # Create a map object
        m = folium.Map(width=500, height=440, location=(df_data['latitude'].mean(), df_data['longitude'].mean()), zoom_start=10)
        
        # Add markers to the map
        all_markers = folium.FeatureGroup(name='All Markers')
        active_markers = folium.FeatureGroup(name='Active Markers', show=False)
        inactive_markers = folium.FeatureGroup(name='Inactive Markers', show=False)
        
        
        for index, row in df_data.iterrows():
            status_color = 'green' if index%2==0 else 'red'
            html_content = f"""
            <div style="
                display: inline-block;
                background-color: white;
                border: 2px solid black;
                border-radius: 50%;
                width: 20px;
                height: 20px;
                text-align: center;
                line-height: 20px;
                font-size: 8pt;
                color: {status_color};
            ">{index}</div>
            """
        
            # Create a DivIcon with custom HTML content
            icon = folium.DivIcon(html=html_content)
            marker = folium.Marker([row['latitude'], row['longitude']], popup=row['Address'], icon=icon).add_to(m)
            
        
        # Add layer control to toggle marker visibility
        folium.LayerControl().add_to(m)
        
        polygon_coords = [ [np.random.uniform(40.7, 40.8, size=6)[i], np.random.uniform(-74.0, -73.9, size=6)[i]] for i in range(6)]
        
        # Create a polygon object
        polygon = folium.Polygon(locations=polygon_coords, color='blue', fill=True, fill_color='blue', fill_opacity=0.3)
        
        # Add the tag to the polygon 
        popup_text = "This is my polygon"
        popup = folium.Popup(popup_text, parse_html=True)
        polygon.add_child(popup)
        
        # Add the polygon to the map
        m.add_child(polygon)
        
            
        # Render the map
        folium_static(m)
    col_2_1, col_2_2, col_2_3  = st.columns([4, 4, 1])
    with col_2_1:
        option = st.radio("Add comps:", (":rainbow[On]", ":rainbow[Off]"), horizontal=True,  index=1)
             
    with col_2_2:
        if st.button("Predictions"):
            st.switch_page("pages/market_rent_estimation.py")
    with col_2_3:
        if st.button("Rexy"):
            st.switch_page("pages/rexy.py")
    

    if option == ":rainbow[On]":  
        col_3_1, col_3_2, col_3_3  = st.columns([5,1,5]) 
        with col_3_1: 
            data5 = {
                "favorite": [False]*8,
                'Address': ['B', 'B', 'B', 'B', 'B', 'B', 'B', 'B'],
                'latitude': [40.7]*8,  # Assuming latitude range between 40.7 and 40.8
                'longitude': [-74.0]*8,  # Assuming longitude range between -74.0 and -73.9
                'Match score': [12, 12, 12, 12, 12, 12, 12, 12],
                'Market': ["M2", "M2", "M2", "M2", "M2", "M2", "M2", "M2"],
                'Sub-market': ["S2", "S2", "S2", "S2", "S2", "S2", "S2", "S2"],
                'Lease Date': ["2024/1/1", "2024/1/1", "2024/1/1", "2024/1/1", "2024/1/1", "2024/1/1", "2024/1/1", "2024/1/1"],
                'LSF': [20000, 30000, 20000, 30000, 20000, 30000, 50000, 35000],
                'RSF': [20000, 30000, 20000, 30000, 20000, 30000, 50000, 35000],
                'Rent (NNN)': [11, 11, 11, 12, 12, 12, 12, 15],
                'Year Built': [2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019],
                'Office %': [20, 20, 20, 20, 20, 20, 20, 20],
                'Clear Height':[19, 18, 19, 18, 17, 19, 19, 18],
                'Doors (drive in / Dock)': [2, 2, 2, 2, 2, 2, 2, 2],
                'Lease Term ': [60, 60, 60, 60, 60, 60, 60, 60],
                'Rent (Gross)': [11, 11, 11, 12, 12, 12, 12, 15],
                'TIs ': [1, 1, 1, 1, 1, 1,  1, 1]
            }
            
            # Create DataFrame
            df5 =  pd.DataFrame(data5)
            # df5.insert(loc=0, column='Select rows', value=[False]*len(df5))
            st.write('Additional comps')
            test = st.data_editor(
                df5,
                column_config={
                    "favorite": st.column_config.CheckboxColumn(
                        "Your favorite?",
                        help="Select your **favorite** widgets",
                        default=False,
                    )
                },
                disabled=['Address','latitude','longitude','Match score','Market','Sub-market','Lease Date','LSF',
                'RSF','Rent (NNN)','Year Built','Office %','Clear Height','Doors (drive in / Dock)','Lease Term ','Rent (Gross)','TIs '],
                hide_index=True,
            )
        with col_3_2: 
            if st.button("Add comps", help="Click to add more comps"):
                filtered_data1 = pd.concat([filtered_data, test.drop(columns=['favorite'])])
                # filtered_data.update(test.drop(columns=['favorite']))
                display_df.table(filtered_data1)
        with col_3_3:
            st.write('Filter definition')
            
            range_1 = st.slider('Lease date', min_value=0, max_value=36, 
                        value=(12))
            range_2 = st.slider('Location in mi', min_value=0, max_value=50, 
                        value=(12))            
            range_3 = st.slider('LSF', min_value=0, max_value=500000, step = 1000,
                        value=(20000, 200000))
            range_4 = st.slider('Clear height', min_value=0, max_value=50, 
                        value=(15, 30))
            range_5 = st.slider('Year built', min_value=1960, max_value=2024, 
                        value=(1999, 2010))
            range_5 = st.slider('Far %', min_value=0, max_value=100, 
                        value=50)
            range_6 = st.slider('Office %', min_value=0, max_value=100, 
                        value=30)
            range_7 = st.slider('Docl doors & Drive-in', min_value=0, max_value=20, 
                        value=3)
            st.button("Apply filter", key="submit_button", help="Click to submit")


if __name__ == "__main__":
    main()