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

# Path of the file has been stored in variable called 'path'

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

#Code starts here
data = np.genfromtxt(path, delimiter=",", skip_header=1)
print("\nData: \n\n",data)
print("\nType of data: \n\n",type(data))
census = np.concatenate((new_record,data))
print(census)


# --------------
#Code starts here
age = np.array(census[:,0])
#print(len(age))
max_age = np.amax(age)
print(max_age)
min_age = np.amin(age)
print(min_age)
age_mean = np.mean(age)
print(age_mean)
age_std = np.std(age)
print(age_std)


# --------------
#Code starts here

#Creating new subsets based on 'Age'
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]


#Finding the length of the above created subsets
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)

#Printing the length of the above created subsets
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)

#Storing the different race lengths with appropriate indexes
race_list=[len_0, len_1,len_2, len_3, len_4]

#Storing the race with minimum length into a variable 
minority_race=race_list.index(min(race_list))

#Code ends here


# --------------
#Code starts here
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)
print(senior_citizens_len)
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]
print(high,low)
avg_pay_high = high.mean(axis=0)[7]
print(avg_pay_high)
avg_pay_low = low.mean(axis=0)[7]
print(avg_pay_low)
print(avg_pay_high>avg_pay_low)


