<reponame>kumudsagar82/ga-learner-dsmp-repo
# --------------
# Importing header files
import numpy as np

# Path of the file has been stored in variable called 'path'
data=np.genfromtxt(path,delimiter=",", skip_header=1)
print(data)
#New record
new_record=[[50,  9,  4,  1,  0,  0, 40,  0]]
census=np.concatenate((data,new_record))


#Code starts here



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

len_1=len(race_1)

len_2=len(race_2)
len_3=len(race_3)
len_4=len(race_4)

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

def minimum(a, n):
     min1= a.index(min(a)) 
     return min1

minority_race=minimum(b, len(b))  
print(minority_race)  

    








# --------------

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

working_hours_sum=senior_citizens.sum(axis=0)[6]
senior_citizens_len=len(senior_citizens)
avg_working_hours=np.divide(working_hours_sum,senior_citizens_len)
print(avg_working_hours)


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

#Code starts here
print(high)
avg_pay_high=np.mean(high[:,7])
avg_pay_low=np.mean(low[:,7])
np.equal(avg_pay_high,avg_pay_low)


