# --------------
# 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((new_record,data),axis = 0)

print(census.shape)

age = census[:,0]
max_age = np.max(age)
print(max_age)
min_age = np.min(age)
print(min_age)
age_mean = round(np.mean(age),2)
print(age_mean)
age_std = round(np.std(age),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]

minority_race=race_list.index(min(race_list))
print(minority_race)

senior_citizens = census[census[:,0] > 60]
working_hours_sum = np.sum(senior_citizens[:,6])
senior_citizen_len = len(senior_citizens)
avg_working_hours = round(working_hours_sum/senior_citizen_len,2)
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(round(avg_pay_high,2))
print(round(avg_pay_low,2))


