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



# --------------
#Code starts here
age = census[:, 0]
max_age = np.max(age)
min_age = np.min(age)
age_mean = np.mean(age)
age_std = np.std(age)


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

race_t = [len_0, len_1, len_2, len_3, len_4]
minority = min(race_t)
print(minority)
minority_race = race_t.index(minority)
print(minority_race)


# --------------
#Code starts here
senior_citizens = census[census[:, 0]>60]

working_hours = census[:, 6][census[:, 0]>60]

working_hours_sum = sum(working_hours)
senior_citizens_len = len(senior_citizens)
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]

pay_high = census[:, 7][census[:, 1]>10]
pay_low = census[:, 7][census[:, 1]<=10]

avg_pay_high = np.mean(pay_high)
avg_pay_low = np.mean(pay_low)

print(avg_pay_high, avg_pay_low)


