Hello, I need help and please number it so l know which line to put the answer on, and please write it down the whole thing because, so I would know what to keep and don't keep please. Could you please show me in your code how you number and write it down? I am having a hard time. Thank you

Project lab06.py immigration.csv INDUSTRIES = ['Agriculture', 'Business services', 'Construction', ' Leisure/hospitality', 'Manufacturing' ] def read_file (fp) : ""Docstring"In return None # temporary return value so main runs 11 12 def get_totals (L) : 13 " "Docstring""" 14 return None, None # temporary return value so main runs 15 16 17 def get_industry_counts (L) : 18 "Docstring"un 19 return None # temporary return value so main runs 20 21 22 def get_largest_states (L) : 23 "Docstring"" 24 return None # temporary return value so main runs 25 26 27 def main( ) : 28 fp = open ("immigration.csv") 29 L = read_file(fp) 30 31 us_pop, total_pop = get_totals(L) 32 if us_pop and total_pop: # if their values are not None print("\ Data on Illegal Immigration\ ") print ("Summative:", us_pop) 35 print ("Total , total_pop) 36 states = get_largest_states (L) if states: # if their value is not None 39 print("\ States with large immigrant populations") 40 for state in states: state = state. replace ('\ ' , ' ') print (state) 43 44 counters = get_industry_counts (L) 45 if counters: # if their value is not None 46 print ("\ Industries with largest immigrant populations by state") 47 print("{:24s} {:10s}". format("industry", "count") ) 48 for tup in counters: 49 print ("{:24s} {:2d}". format(tup[0], tup[1])) 50 51 52 if __name__ == "__main__": 53 main() 100% (2:1) Terminal codio@felixego-meterradio: ~/workspaces immigration.csv Alabama, "55, 000" , 1. 2%, 34%, 3.3%, 59%, 13%, "-15,000", 1. 7%, Construction, Construction, Service, Farming Alaska, "5,000", 1. 0%, 13%, 0.5%, 23%, 43%, Not sig. , 1. 7%, Manufacturing, Manufacturing, Production, Production Arizona, "275, 000", 3.9%, 28%, 10. 7%, 78%, 13%, "-220, 000", 5. 7%, Business services, Agriculture, Service, Farming Arkansas, "55, 000" , 1. 9%, 41%, 6.3%, 64%, 15%, "-10,000", 2. 8%, Manufacturing, Construction, Service, Construction California, "2, 200, 060", 5.6%, 20%, 13. 3%, 69%, 10%, "-550, 000", 8.6%, Leisure/hospitality, Agriculture, Service, Farming colorado, "190, 000", 3.4%, 34%, 10. 6%, 70%, 14%, Not sig. , 4.6%, Construction, Construction, Service, Construction Connecticut, "120, 060", 3.5%, 23%, 6.9%, 14%, 21%, Not sig. , 4.9%, Business services, Construction, Service, Construction Delaware, "30,000", 3.0%, 31%, 7. 0%, 38%, 29%, Not sig. , 4.2%, Construction, Construction, Service, Farming "District of Columbia", "25,000", 3. 8%%, 28%%, 9.0%, 5%, 21%, Not sig. , 4.7%, Leisure/hospitality, Construction, Service, Construction Florida, "775,000", 3. 8%, 18%, 7. 1%, 15%, 29%, "-240,000", 5.6%, Construction, Agriculture, Service, Farming Georgia, "400, 000", 3. 8%, 36%, 8. 6%, 49%, 17%, Not sig. , 5.4%, Construction, Construction, Service, Construction lawaii, "45,000" , 3.3%, 17%%, 7. 0%, 6%,34%, Not sig. , 4.5%, Leisure/hospitality, Agriculture, Service, Farming Idaho, "35, 000" , 2.2%, 37%%, 5. 7%, 79%, 19%, Not sig. , 3.1%, Agriculture, Agriculture, Service, Farming Illinois, "400, 000", 3.2%, 22%, 7. 8%, 71%, 11%, "-140, 090", 4.8%, Manufacturing, Manufacturing, Service, Production Indiana, "100,000", 1. 5%, 29%, 4.2%, 59%, 23%, Not sig. , 2. 1%, Manufacturing, Agriculture, Service, Farming towa, "50, 000", 1. 7%, 31%, 4. 2%, 56%, 26%%, Not sig. , 2.2%%, Manufacturing, Manufacturing, Production, Farming ansas, "75, 000", 2. 6%%, 35%, 7. 6%, 69%, 16%, Not sig. , 3. 7%, Manufacturing, Construction, Service, Construction Kentucky, "35, 000", 0. 8%, 22%, 1. 6%, 48%, 24%, Not sig. , 1. 1%, Construction, Agriculture, Service, Farming ouisiana, "70, 090", 1. 5%, 36%, 2. 7%%, 28%, 23%, "15,000", 2.0%, Construction, Construction, Construction, Construction Maine, "