# --------------
# Importing header files
import numpy as np
import warnings

warnings.filterwarnings('ignore')

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

#Reading file
data = np.genfromtxt(path, delimiter=",", skip_header=1)

#Code starts here

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

#create new array 'age'
age=census[:,[0]]

#print max_age & min_age
max_age=np.max(age)
print(max_age)
min_age=np.min(age)
print(min_age)

#print mean of age
age_mean=np.mean(age).round(2)
print(age_mean)

#print standard deviation of age
age_std=np.std(age).round(2)
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)

race_list=[len_0,len_1,len_2,len_3,len_4]
min_c = min(race_list)

minority_race = race_list.index(min_c)

print(minority_race)

senior_citizens=census[census[:,0]>60]
working_hours_sum=senior_citizens.sum(axis=0)[6]
print(working_hours_sum)
senior_citizens_len=len(senior_citizens)

avg_working_hours=working_hours_sum/senior_citizens_len
print(avg_working_hours.round(2))

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

avg_pay_high=np.mean(high[:,7])
print(avg_pay_high.round(2))
avg_pay_low=np.mean(low[:,7])
print(avg_pay_low.round(2))
'''
high=census[census[:,1]>10]
low=census[census[:,1]<=10]

avg_pay_high=high.mean(axis=0)[7]
print('%.2f'%avg_pay_high)

avg_pay_low=low.mean(axis=0)[7]
print('%.2f'%avg_pay_low)

'''


