# --------------
# 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.shape)

census = np.concatenate((data, new_record), axis = 0)
print(census.shape)


# --------------
#Code starts here
age = census[: , 0]
max_age = age.max()
print("Maximum Age = ", max_age)
min_age = age.min()
print("Minimum Age = ", min_age)
age_mean = age.mean()
print("Average Age = ", age_mean)   
age_std = age.std()
print("Standard Deviation of Age = ", age_std)


# --------------
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)

citizens_min = [len_0, len_1, len_2, len_3, len_4]
minority_race = citizens_min.index(min(citizens_min))

print(minority_race)



# --------------
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)


# --------------
high = census[census[:, 1]>10]
low =  census[census[:, 1]<=10]

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

print("High", avg_pay_high)
print("Low", avg_pay_low)

if avg_pay_high > avg_pay_low:
    print('Better Education Leads to Better Pay')
else:
    print('There is no such guarantee')


