Update pages/comps_data.py

pages/comps_data.py

@@ -8,8 +8,32 @@ import seaborn as sns
 from datetime import datetime, timedelta
 
 def main():
-    df6 = pd.read_csv("market_underwriting_pred.csv", encoding='utf-8')
-    df6.insert(loc=0, column='Select rows', value=[False]*len(df6))
+    data = {
+        "favorite": [True, False, False, True, True, False, False, True],
+        'Address': ['B', 'B', 'B', 'B', 'B',
+                'B', 'B', 'B'
+                ],
+        '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': [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(data)
+    df5.insert(loc=0, column='Select rows', value=[False]*len(df5))
 
     st.set_page_config(initial_sidebar_state="collapsed", layout="wide")
     
@@ -126,37 +150,11 @@ def main():
     if option == ":rainbow[On]":  
         col_3_1, col_3_2, col_3_3  = st.columns([5,1,5]) 
         with col_3_1: 
-            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': [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(data)
-            df5.insert(loc=0, column='Select rows', value=[False]*len(df5))
             st.write('Additional comps')
             st.data_editor(
                 df5,
                 column_config={
-                    "favorite": st.column_config.CheckboxColumn(
+                    "Select rows": st.column_config.CheckboxColumn(
                         "Your favorite?",
                         help="Select your **favorite** widgets",
                         default=False,