Else or elif condition executed every time in python code in the nested dictionary-CodePudding

I am trying to execute below code wherein I want to insert a key in the dictionary with a particular value on a condition where tos is greater than or less than the value of position key in the dictionary. But in the output I see the else or elif condition executed every time.

def convert_csv_to_dataframe_and_then_convert_csv_data_to_dictionary(tos):
    data = pd.read_csv(
        r"C:\Users\ppathar\Documents\Ingestion files\L3_Ingestion_scenario_files\own_stakes_detail_eq_update.txt",
        sep='|')
    #print(data)
    recs = data.to_dict(orient="index");
    # print(recs)
    # print(recs[0]['FACTSET_ENTITY_ID'])

    for i in recs:

        #pd.Series(recs[i]['FACTSET_ENTITY_ID'],recs[i]['FSYM_ID'],recs[i]['POSITION'])
        print(recs[i]['POSITION'])
        if int(recs[i]['POSITION'])>tos:
            recs[i]['is_valid']=True
        elif int(recs[i]['POSITION'])<tos:
            recs[i]['is_valid'] = False
    print(recs)


convert_csv_to_dataframe_and_then_convert_csv_data_to_dictionary(6508861232)

Below is the output.

{
  0: {'FSET_ENTITY_ID': 'PRATIO-A', 
  'FSYM_ID': 'VVGJM-S', 
  'POSITION': 650886123, 
  'INDIRECT_OPTIONS': 760000, 
  'REPORT_DATE': '2022-11-03', 
  'SOURCE_CODE': 'A', 
  'COMMENTS': 'INCLUDES CARL AN CRT. INDIRECT REPRESENTS WARRANTS.', 
  'CURRENT_FLAG': 1, 
  'is_valid': False}, 

  1: {'FACTSET_ENTITY_ID': 'PRATIO-B', 
  'FSM_ID': 'VVG1JM-S', 
  'POSITION': 650886121, 
  'INDIRECT_OPTIONS': 0, 
  'REPORT_DATE': '2022-11-03', 
  'SOURCE_CODE': 'H', 
  'COMMENTS': 'RESONA BANK LTD/ID135336(408000)', 
  'CURRENT_FLAG': 1, 
  'is_valid': False}
}

I have passed tos as 6508861232 which is greater than 650886123 and the other position key value in the dictionary but the is_valid is not added as True in the dictionary. Am I missing something in the code?

CodePudding user response：

Your code is working fine:

if int(recs[i]['POSITION'])>tos:
    recs[i]['is_valid']=True 
elif int(recs[i]['POSITION'])<tos:
    recs[i]['is_valid'] = False

In both the cases int(recs[i]['POSITION'])<tos, thus recs[i]['is_valid'] = False

You might want to change the positions of True and False to get desired behavior as:

if int(recs[i]['POSITION'])>tos:
    recs[i]['is_valid'] = False 
elif int(recs[i]['POSITION'])<tos:
    recs[i]['is_valid'] = True

CodePudding user response：

Both the numbers (values of 'POSITION') in your dataframe have 9 digits. The tos has 10 digits.

So the output you got is correct.