Python Прогноз

Question

Не могу заставить программу работать. Я хочу, чтобы программа делала прогноз, для какого сорта пшеницы она соответствует в соответствии с вводом пользователя. Однако я снова получаю результат индекса за пределами допустимого диапазона. Я подумал, может быть, это как-то связано с возвратом.

Вот код

import pandas as pd                                                                             
import numpy as np                                                                              
import os                                                                                       
import csv                                                                                      
import sys                                                                                        
from sklearn.model_selection import train_test_split                                              
from sklearn.naive_bayes import GaussianNB                                                         
with open('example.csv', 'r') as csvfile:
readCSV = csv.reader(csvfile, delimiter=',')

next(readCSV)
Wheat_Varietys = []
id = 0
for line in readCSV:
    area = line[0]
    perimiter = line[1]
    compactness = line[2]
    kernel_length = line[3]
    kernel_width = line[4]
    assymetry_coeff = line[5]
    groove_length = line[6]
    Wheat_Variety = line[7]

    Wheat_Varietys.append({ 'id': id,
    'attributes': 
        {
        'area': area,
        'perimiter': perimiter,
        'compactness': compactness,
        'kernel_length': kernel_length,
        'kernel_width': kernel_width,
        'assymetry_coeff': assymetry_coeff,
        'groove_length': groove_length,
        'Wheat_Variety': Wheat_Variety,
    }})
    id+=1                                                                                     
    whatArea = input('What area do you wish to enter?')                                               
    whatPeri = input('What perimiter do you wish to enter?')                                          
    whatComp = input('What compactness do you wish to enter?')                                        
    whatKerL = input('What kernel length do you wish to enter?')                                      
    whatKerW = input('What kernel width do you wish to enter?')                                      
    whatAssym = input('What Assymetry Coefficient do you wish to enter?')                           
    whatGroove = input('What Groove Lenght do you wish to enter?')


    wheat_dataset = pd.read_csv('example.csv')
    wheat_data_cols = wheat_dataset[['area', 'perimeter', 'compactness', 
    'kernel_length', 'kernel_width', 'assymetry_coeff' , 'groove_length']]
    x_train, x_test, y_train, y_test = train_test_split(wheat_data_cols, 
    wheat_dataset['Wheat_Variety'], train_size = 0.8, test_size = 0.2, 
    random_state = 0)
    nb = GaussianNB()
    nb.fit(x_train, y_train)
    def predict_wheat_classification(whatArea, whatPeri, whatComp, whatKerL, 
          whatKerW, whatAssym, whatGroove):
          x_new = np.array([[whatArea, whatPeri, whatComp, whatKerL, whatKerW, 
          whatAssym, whatGroove]])
          prediction = nb.predict(x_new)
       return prediction[0]

    print(predict_wheat_classification(2, 2, 2, 2, 2, 2, 2))

, а вот CSV

example.csv