# --------------
# 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]]
data1 = np.array(new_record)
#Code starts here
data = np.genfromtxt(path, delimiter=",", skip_header=1)
census = np.concatenate((data, data1))
print(census)


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


# --------------
#Code starts here
race_0 = census[census[:, 2] == 0]
len_0 = len(race_0)
race_1 = census[census[:, 2] == 1]
len_1 = len(race_1)
race_2 = census[census[:, 2] == 2]
len_2 = len(race_2)
race_3 = census[census[:, 2] == 3]
len_3 = len(race_3)
race_4 = census[census[:, 2] == 4]
len_4 = len(race_4)

minority_race = np.argmin(np.array([len_0, len_1, len_2, len_3, len_4]))
print(minority_race)


# --------------
#Code starts here
senior_citizens = census[census[:,0]>60]
working_hours_sum = np.sum(senior_citizens[:, 6])
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]
avg_pay_high = np.round(high[:, 7].mean(), 2)
avg_pay_low = np.round(np.mean(low[:, 7]), 2)
print(avg_pay_high, avg_pay_low)




# --------------
# 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]]
data1 = np.array(new_record)
#Code starts here
data = np.genfromtxt(path, delimiter=",", skip_header=1)
census = np.concatenate((data, data1))
print(census)


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


# --------------
#Code starts here
race_0 = census[census[:, 2] == 0]
len_0 = len(race_0)
race_1 = census[census[:, 2] == 1]
len_1 = len(race_1)
race_2 = census[census[:, 2] == 2]
len_2 = len(race_2)
race_3 = census[census[:, 2] == 3]
len_3 = len(race_3)
race_4 = census[census[:, 2] == 4]
len_4 = len(race_4)

minority_race = np.argmin(np.array([len_0, len_1, len_2, len_3, len_4]))
print(minority_race)


# --------------
#Code starts here
senior_citizens = census[census[:,0]>60]
working_hours_sum = np.sum(senior_citizens[:, 6])
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]
avg_pay_high = np.round(high[:, 7].mean(), 2)
avg_pay_low = np.round(np.mean(low[:, 7]), 2)
print(avg_pay_high, avg_pay_low)




# -------------- # Importing header files # Path of the file has been stored in variable called 'path' #New record #Code starts here # -------------- #Code starts here # -------------- #Code starts here # -------------- #Code starts here # -------------- #Code starts here