# --------------
import numpy as np
new_record=[[50,  9,  4,  1,  0,  0, 40,  0]]
data=np.genfromtxt(path,delimiter=",",skip_header=1)
print(data.shape)
census=np.concatenate((data,new_record),axis=0)
print(census.shape)




# --------------
age=census[:,0]
max_age=max(age)
min_age=min(age)
age_mean=age.mean(axis=0)
age_std=np.std(age)
print(max_age)
print(min_age)
print(age_mean)
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)
len_1=len(race_1)
len_2=len(race_2)
len_3=len(race_3)
len_4=len(race_4)
print("Race_0:",len_0)
print("Race_1:",len_1)
print("Race_2:",len_2)
print("Race_3:",len_3)
print("Race_4:",len_4)
race_list=[len_0,len_1,len_2,len_3,len_4]
minority_race=race_list.index(min(race_list))




# --------------
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)


# --------------
high=census[census[:,1]>10]
low=census[census[:,1]<=10]
avg_pay_high=np.mean(high[:,7])
avg_pay_low=np.mean(low[:,7])
print(avg_pay_high)
print(avg_pay_low)



