text: # --------------
  # Importing header files
  import numpy as np
  import warnings
  
  warnings.filterwarnings('ignore')
  
  #New record
  new_record=[[50,  9,  4,  1,  0,  0, 40,  0]]
  new_record=np.asarray(new_record)
  #Reading file
  data = np.genfromtxt(path, delimiter=",", skip_header=1)
  #Code starts here
  census=np.concatenate((data,new_record))
  age=census[:,0]
  max_age=age.max()
  min_age=age.min()
  age_mean=age.mean()
  age_std=age.std()
  race=census[:,2]
  race_0=race[race==0]
  race_1=race[race==1]
  race_2=race[race==2]
  race_3=race[race==3]
  race_4=race[race==4]
  len_0=race_0.size
  len_1=race_1.size
  len_2=race_2.size
  len_3=race_3.size
  len_4=race_4.size
  a=[len_0,len_1,len_2,len_3,len_4]
  minority_race=a.index(min(a))
  senior_citizens=age[age>60]
  work=census[:,6]
  working_hours_sum=work[age>60]
  avg_working_hours=working_hours_sum.mean()
  working_hours_sum=work[age>60].sum()
  edu=census[:,1]
  high=edu[edu>10]
  low=edu[edu<=10]
  salary=census[:,7]
  avg_pay_high=salary[edu>10].mean()
  avg_pay_low=salary[edu<=10].mean()
  print("%0.2f\n%0.2f"%(avg_pay_high,avg_pay_low))
  
  
  
  
  
  