Черновик к 5ой лабе

from statistics import mean
import os
import pandas as pd
import numpy as np
import seaborn as sn

def srednee(class_, num_of_priznak):
  priznak = class_.get(num_of_priznak)
  sr = 0
  for i in range(15):
    sr += priznak[i]
  sr /= 15
  sr = round(sr, 2)
  return sr

def stepA(class_, list_of_sr_A, num_of_priznak):
  list = []
  priznak = class_.get(num_of_priznak)
  for i in range(15):
    list.append(round(((priznak[i]-list_of_sr_A[num_of_priznak])**2),2))
  return list

def stepBC(class_1, class_2, list_of_sr_BC, num_of_priznak):
  list = []
  priznakB = class_1.get(num_of_priznak)
  priznakC = class_2.get(num_of_priznak)
  for i in range(15):
    list.append(round(((priznakB[i]-list_of_sr_BC[num_of_priznak])**2),2))
  for i in range(15):
    list.append(round(((priznakC[i]-list_of_sr_BC[num_of_priznak])**2),2))
  return list

def raznica(list1, list2, list3, list4, i):
  a = (((list1[i]-list2[i])**2)/(list3[i]+list4[i]))
  return a

class_A = {0: [18, 13, 11, 15, 16, 19, 17, 12, 13, 11, 15, 16, 19, 17, 13],
           1: [22, 23, 24, 24, 25, 25, 26, 27, 27, 27, 27, 29, 29, 30, 31],
           2: [26, 24, 20, 20, 20 ,20, 28, 28, 22, 24, 26, 24, 22, 20, 26],
           3: [35, 38, 29, 33, 37, 42, 40, 32, 35, 43, 46, 39, 44, 36, 41],
           4: [11, 13, 19, 16, 12, 11, 17, 18, 13, 11, 15, 16, 19, 17, 12],
           5: [5, 6, 9, 8, 6, 5, 8, 9, 6, 5, 7, 8, 9, 8, 6],
           6: [18, 19, 15, 17, 19, 21, 20, 16, 18, 22, 23, 20, 22, 8, 21]}

class_B = {0: [19, 16, 12, 11, 17, 18, 13, 18, 13, 18, 13, 11, 15, 16, 19],
           1: [38, 39, 41, 41, 42, 43, 43, 44, 44, 44, 45, 46, 47, 48, 49],
           2: [22, 26, 22, 28, 22, 20, 24, 26, 28, 20, 26, 24, 20, 20, 20],
           3: [26, 31, 21, 25, 28, 23, 32, 21, 26, 30, 18, 23, 28, 32, 26],
           4: [13, 11, 15, 16, 19, 17, 13, 19, 16, 12, 11, 17, 18, 11, 14],
           5: [6, 5, 7, 8, 9, 8, 6, 9, 8, 6, 5, 8, 9, 5, 7],
           6: [13, 16, 11, 13, 14, 12, 16, 11, 13, 15, 9, 12, 14, 16, 13]}

class_C = {0: [17, 12, 13, 11, 15, 16, 19, 17, 13, 19, 16, 12, 18, 13, 11],
           1: [43, 45, 45, 46, 47, 48, 49, 49, 50, 51, 51, 53, 53, 53, 54],
           2: [20, 28, 28, 22, 24, 26, 24, 22, 20, 26, 22, 26, 22, 28, 22],
           3: [57, 51, 59, 55, 61, 57, 49, 53, 61, 55, 59, 51, 58, 62, 55],
           4: [17, 13, 19, 16, 12, 11, 17, 18, 11, 14, 15, 13, 19, 17, 12],
           5: [8, 6, 9, 8, 6, 5, 8, 9, 5, 7, 7, 6, 9, 8, 6],
           6: [29, 26, 30, 28, 31, 29, 25, 27, 31, 28, 30, 26, 29, 31, 28]}

dataA = pd.DataFrame([[18, 13, 11, 15, 16, 19, 17, 12, 13, 11, 15, 16, 19, 17, 13],
                     [22, 23, 24, 24, 25, 25, 26, 27, 27, 27, 27, 29, 29, 30, 31],
                     [26, 24, 20, 20, 20 ,20, 28, 28, 22, 24, 26, 24, 22, 20, 26],
                     [35, 38, 29, 33, 37, 42, 40, 32, 35, 43, 46, 39, 44, 36, 41],
                     [11, 13, 19, 16, 12, 11, 17, 18, 13, 11, 15, 16, 19, 17, 12],
                     [5, 6, 9, 8, 6, 5, 8, 9, 6, 5, 7, 8, 9, 8, 6],
                     [18, 19, 15, 17, 19, 21, 20, 16, 18, 22, 23, 20, 22, 8, 21]],
               index=['pr1', 'pr2', 'pr3', 'pr4', 'pr5', 'pr6', 'pr7'],
             columns=['1','2','3','4','5','6','7','8','9','10','11','12','13','14','15'])

dataB = pd.DataFrame([[19, 16, 12, 11, 17, 18, 13, 18, 13, 18, 13, 11, 15, 16, 19],
                      [38, 39, 41, 41, 42, 43, 43, 44, 44, 44, 45, 46, 47, 48, 49],
                      [22, 26, 22, 28, 22, 20, 24, 26, 28, 20, 26, 24, 20, 20, 20],
                      [26, 31, 21, 25, 28, 23, 32, 21, 26, 30, 18, 23, 28, 32, 26],
                      [13, 11, 15, 16, 19, 17, 13, 19, 16, 12, 11, 17, 18, 11, 14],
                      [6, 5, 7, 8, 9, 8, 6, 9, 8, 6, 5, 8, 9, 5, 7],
                      [13, 16, 11, 13, 14, 12, 16, 11, 13, 15, 9, 12, 14, 16, 13]],
                index=['pr1', 'pr2', 'pr3', 'pr4', 'pr5', 'pr6', 'pr7'],
              columns=['1','2','3','4','5','6','7','8','9','10','11','12','13','14','15'])

dataC = pd.DataFrame([[17, 12, 13, 11, 15, 16, 19, 17, 13, 19, 16, 12, 18, 13, 11],
                      [43, 45, 45, 46, 47, 48, 49, 49, 50, 51, 51, 53, 53, 53, 54],
                      [20, 28, 28, 22, 24, 26, 24, 22, 20, 26, 22, 26, 22, 28, 22],
                      [57, 51, 59, 55, 61, 57, 49, 53, 61, 55, 59, 51, 58, 62, 55],
                      [17, 13, 19, 16, 12, 11, 17, 18, 11, 14, 15, 13, 19, 17, 12],
                      [8, 6, 9, 8, 6, 5, 8, 9, 5, 7, 7, 6, 9, 8, 6],
                      [29, 26, 30, 28, 31, 29, 25, 27, 31, 28, 30, 26, 29, 31, 28]],
               index=['pr1', 'pr2', 'pr3', 'pr4', 'pr5', 'pr6', 'pr7'],
             columns=['1','2','3','4','5','6','7','8','9','10','11','12','13','14','15'])

list_of_srA = []
list_of_srBC = []
list_of_srA06 = []
list_of_srBC06 = []
itog = []
dataA = dataA.transpose()
dataB = dataB.transpose()
dataC = dataC.transpose()

for i in range(7):
  list_of_srA.append(srednee(class_A, i))

for i in range(7):
  list_of_srBC.append((srednee(class_B, i)+srednee(class_C, i))//2)

for i in range(7):
  list_of_srA06.append(round(mean(stepA(class_A, list_of_srA, i)),2))

for i in range(7):
  list_of_srBC06.append(round(mean(stepBC(class_B, class_C, list_of_srBC, i)),2))

for i in range(7):
  itog.append(round(raznica(list_of_srA, list_of_srBC, list_of_srA06, list_of_srBC06, i),4))
print(itog)

numeric_col = ['pr1','pr2','pr3','pr4', 'pr5', 'pr6', 'pr7']
corr_matrix = dataA.loc[:,numeric_col].corr()
print(corr_matrix)