# --------------
# 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)
print(type(data))
#New record
new_record=[[50,  9,  4,  1,  0,  0, 40,  0]]
census=np.concatenate((data,new_record))
print(census)
#Code starts here



# --------------
#Code starts here
age=np.array(census[:,0])
max_age=age.max()
min_age=age.min()
age_mean=age.mean()
age_std=age.std()
print(age)
print(max_age)
print(min_age)
print(age_mean)
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)
lenlst={0:len(race_0),
1:len(race_1),
2:len(race_2),
3:len(race_3),
4:len(race_4)
}
for i in lenlst.keys():
    x=lenlst.get(i)
    if x==min(lenlst.values()):
        minority_race=i
print(minority_race)





# --------------
#Code starts here
senior_citizens=census[census[:,0]>60]
working_hours_sum=senior_citizens[:,6].sum()
senior_citizens_len=senior_citizens[:,6].size
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[:,7].mean()
avg_pay_low=low[:,7].mean()
print(avg_pay_high)
print(avg_pay_low)


