# --------------
# 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)
#print(data)

census = np.concatenate((data, new_record))
print(census)


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

age = np.array(census[:,0])
print(age)
max_age = np.amax(age)
print(max_age)

min_age = np.min(age)
print(min_age)

age_mean = np.mean(age)
print(age_mean)

age_std = np.std(age)
print(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("Citizen in race 0:" + str(len_0))
print("Citizen in race 1:" + str(len_1))
print("Citizen in race 2:" + str(len_2))
print("Citizen in race 3:" + str(len_3))
print("Citizen in race 4:" + str(len_4))

minority_race = 3


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

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

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

senior_citizens_len = len(senior_citizens)
print(senior_citizens_len)

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]
print(avg_pay_high)

avg_pay_low = low.mean(axis=0)[7]
print(avg_pay_low)


