chore(lists): remove cmp_list filter

utils/gradio_utils.py

@@ -232,15 +232,16 @@ def generate_ips_per_subclass(ip_subclasses: str, num_of_ips: int) -> str:
 
 ### GENERATE TOP LISTS ###
 def compute_offer(csv_file, days_lookback, min_sent):
-    cmp_list = ['MSP', 'HOM', 'NTU', 'HCK', 'DDS', 'MNP', 'PSC', 'DTL', 'GVS', 'ANP', 'WDR', 'BSG']
+    # cmp_list = ['MSP', 'HOM', 'NTU', 'HCK', 'DDS', 'MNP', 'PSC', 'DTL', 'GVS', 'ANP', 'WDR', 'BSG']   #1
 
     #raw_df = pd.read_csv('tools/data/30.08.2023.gabriel.sabau.campanii.csv', parse_dates=['Data'])
-    raw_df = pd.read_csv(csv_file.name, parse_dates=['Data'])
+    comcast_df = pd.read_csv(csv_file.name, parse_dates=['Data'])
+    # raw_df = pd.read_csv(csv_file.name, parse_dates=['Data']) #1
 
     cols = ['Campanie', 'Oferta', 'Nume', 'Server', 'User',
         'Lista Custom', 'Data', 'HClicks', 'Clicks', 'Unscribers', 'Openers',
         'Click Open', 'Leads', 'CLike', 'Complains', 'Traps', 'Send']
-    comcast_df = raw_df[raw_df['Nume'].str.contains('|'.join(cmp_list))]
+    # comcast_df = raw_df[raw_df['Nume'].str.contains('|'.join(cmp_list))]  #1
     comcast_df = comcast_df[comcast_df['Domeniu'] == 'Comcast']
     comcast_df = comcast_df[cols]
     comcast_df['Click Open'] = comcast_df['Click Open'].str.replace('%', '').astype(float)