# --------------
# Importing header files
import numpy as np

# Path of the file has been stored in variable called 'path'

#New record
new_record=[[50,  9,  4,  1,  0,  0, 40,  0]]

#Code starts here
data = np.genfromtxt(path, delimiter=",", skip_header=1)
census=np.concatenate((data,new_record),axis=0)


# --------------
#Code starts here
age=census[:,0]
max_age=age.max()
min_age=age.min()
age_mean=age.mean()
age_std=age.std()


# --------------
#Code starts here
race_0=census[census[:,2]==0]
race_1=census[census[:,2]==1]
race_2=census[census[:,2]==2]
race_3=census[census[:,2]==3]
race_4=census[census[:,2]==4]

len_0=len(race_0)
len_1=len(race_1)
len_2=len(race_2)
len_3=len(race_3)
len_4=len(race_4)

print('Race_0: ', len_0)
print('Race_1: ', len_1)
print('Race_2: ', len_2)
print('Race_3: ', len_3)
print('Race_4: ', len_4)

race_list=[len_0, len_1,len_2, len_3, len_4]

minority_race=race_list.index(min(race_list))




# --------------
#Code starts here
senior_citizens=census[census[:,0]>60]

working_hours_sum=senior_citizens.sum(axis=0)[6]

senior_citizens_len=len(senior_citizens)


avg_working_hours=working_hours_sum/senior_citizens_len


print(avg_working_hours)



# --------------
#Code starts here
high=census[census[:,1]>10]
low=census[census[:,1]<=10]
avg_pay_high=high.mean(axis=0)[7]
avg_pay_low=low.mean(axis=0)[7]


