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

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

data = np.genfromtxt(path, delimiter = ",", skip_header = 1)
#New record
new_record=[[50,  9,  4,  1,  0,  0, 40,  0]]
census = np.concatenate((data , new_record), axis = 0)
print(census)
#Code starts here



# --------------
#Code starts here
age = census[:,0]

# max age 
max_age = np.max(age)
print(max_age)

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

# mean of the age 
age_mean = np.mean(age) 
print(age_mean)

# standard deviation
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) 
print(len_0)
len_1 = len(race_1) 
print(len_1)
len_2 = len(race_2) 
print(len_2)
len_3 = len(race_3) 
print(len_3)
len_4 = len(race_4) 
print(len_4)

mini_race = min(len_0, len_1, len_2, len_3, len_4)
print(mini_race)

minority_race = 3
print(minority_race)


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

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 = np.divide(working_hours_sum, senior_citizens_len)

print(avg_working_hours)


# --------------
#Code starts here
high = census[census[:,1]>10]
print(high)
low = census[census[:,1]<=10]
print(low)

avg_pay_high = np.mean(high[:,7])
print(avg_pay_high)

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

print(avg_pay_high > avg_pay_low)




