# --------------
import numpy as np 

data = np.genfromtxt(path, delimiter=",", skip_header=1)
print("\nData: \n\n", data)
print("\nType of data: \n\n", type(data))

new_record=[[50,  9,  4,  1,  0,  0, 40,  0]]
print(new_record)
census = np.concatenate((data, new_record), axis = 0)
print(census)

age = np.array(census[:,0])
print(age)

# Max of age                                     
max_age = np.max(age)
print(max_age)

# Min of age
min_age = np.min(age)
print(min_age)

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

# Standard Deviation of age
age_std = np.std(age)
print(round((age_std),2))

# Subsetting arrays

race_0 = census[census[:,2]==0]
print(race_0)

race_1 = census[census[:,2]==1]
print(race_1)

race_2 = census[census[:,2]==2]
print(race_2)

race_3 = census[census[:,2]==3]
print(race_3)

race_4 = census[census[:,2]==4]
print(race_4)

# Length of subset arrays

len_0 = len(race_0)
print(len_0)

len_1 = len(race_1)
print(len_1)

len_2 = len(race_2)
print(len_2)

len_3 = len(race_3)
print(len_3)

len_4 = len(race_4)
print(len_4)

if len(race_0) < len(race_1) and len(race_0) < len(race_2) and len(race_0) < len(race_3) and len(race_0) < len(race_4):
   minority_race = 0
   print(minority_race)
elif len(race_1) < len(race_0) and len(race_1) < len(race_2) and len(race_1) < len(race_3) and len(race_1) < len(race_4):
   minority_race = 1
   print(minority_race)
elif len(race_2) < len(race_0) and len(race_2) < len(race_1) and len(race_2) < len(race_3) and len(race_2) < len(race_4):
   minority_race = 2
   print(minority_race)
elif len(race_3) < len(race_0) and len(race_3) < len(race_1) and len(race_3) < len(race_2) and len(race_3) < len(race_4):
   minority_race = 3
   print(minority_race)
elif len(race_4) < len(race_0) and len(race_4) < len(race_1) and len(race_4) < len(race_2) and len(race_4) < len(race_3):
   minority_race = 4
   print(minority_race)


senior_citizens = census[census[:,0]>60]
print(senior_citizens)

working_hours_sum = sum(senior_citizens[:,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)


high = census[census[:,1]>10]
print(high)

low = census[census[:,1]<=10]
print(low)

avg_pay_high = np.mean(high[:,7])
print(avg_pay_high)

avg_pay_low = np.mean(low[:,7])
print(avg_pay_low)


np.array_equal(avg_pay_high, avg_pay_low)



