# --------------
# Importing header files
import numpy as np
import pandas as pd
# Path of the file has been stored in variable called 'path'
print(path)

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

#Code starts here
census = np.array([])
data=np.genfromtxt(path, delimiter=",", skip_header=1)
census = np.concatenate((data , new_record))


# --------------
#Code starts here
import numpy as np
#age is taken from 'census' array.
age = census[:,0]

#maximum no.o of age from age array
max_age = age.max()
print(max_age)
#minimum no.o of age from age array
min_age = age.min()
print(min_age)
#Average no.o of age from age array
age_mean = np.mean(age)
print(age_mean)

#standard deviation of the age  
age_std = np.std(age)
print(age_std)





# --------------
#Code starts here
import numpy as np 
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)

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

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






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


# --------------
#Code starts here
high = census[census[:,1]>10]
low = census[census[:,1]<=10]
avg_pay_high = high.mean(axis=0)[7]
avg_pay_low = low.mean(axis=0)[7]
avg_pay_high,avg_pay_low.mean()


