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

warnings.filterwarnings('ignore')
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))

age = census[:,0]

max_age = max(age)
print (max_age)
min_age = min(age)
print (min_age)

x = sum(age)
y = len(age)

age_mean = x/y
print (age_mean)

a = age-(age_mean) 
n = pow(a,2)
b =sum(n)
c =len(n)
m = b/c
age_std = math.sqrt(m)
print (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)
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)

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

minority_race=g.index(min(g))
print (minority_race)

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)

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



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

#Code starts here




