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

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


data = np.genfromtxt(path, delimiter=",",skip_header = 1)

print(data)



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

census = np.concatenate((data,new_record),axis=0)
#Code starts here



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




print(age,max_age,min_age,age_mean,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_1, len_2, len_3, len_4 = len(race_0), len(race_1), len(race_2), len(race_3), len(race_4)

minority_race = 3


# --------------
#Code starts here

senior_citizens = census[census[:,0]>60]
working_hours_sum = senior_citizens[:,6]

working_hours_sum = working_hours_sum.sum()
print(working_hours_sum)
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[:,7].mean()

avg_pay_low = low[:,7].mean()


