# --------------
# 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)
census=np.concatenate([data,new_record])


# --------------
#Code starts here
age=census[:,0]
max_age=age.max()
min_age=age.min()
age_mean=age.mean()
age_std=np.std(age)


# --------------
#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)
len=np.array([len_0,len_1,len_2,len_3,len_4])
minority_race=int(np.where(len==np.min(len))[0])



# --------------
#Code starts here
#Subsetting the array based on the age 
senior_citizens=census[census[:,0]>60]

#Calculating the sum of all the values of array
working_hours_sum=senior_citizens.sum(axis=0)[6]

#Finding the length of the array
senior_citizens_len=senior_citizens.shape[0]

#Finding the average working hours
avg_working_hours=working_hours_sum/senior_citizens_len

#Printing the average working hours
print((avg_working_hours))

#Code ends here


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

#Creating an array based on 'education' column
high=census[census[:,1]>10]

#Finding the average pay
avg_pay_high=high[:,7].mean()

#Printing the average pay
print(avg_pay_high)

#Creating an array based on 'education' column
low=census[census[:,1]<=10]

#Finding the average pay
avg_pay_low=low[:,7].mean()

#Printing the average pay
print(avg_pay_low)
#Code ends here


