Key Error: nan when applying KNN classifier - python-3.x

Question

I am trying to test my KNN classifier against some data that I sourced from UCI's Machine Learning Repository. When running the classifier I keep getting the same KeyError
train_set[i[-1]].append(i[:-1])
KeyError: NaN
I am not sure why this keeps happening because if I comment out the classifier and just print the first 10 lines or so, the data shows up fine with no corruption or duplication of any kind.
Here is a link to the data that I am using, I just simply downloaded it and added the column ID's (note: in this link the column ID's have not been added)
Here is what some of the code looks like:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import style
import warnings
from math import sqrt
from collections import Counter
import pandas as pd
import random
style.use('fivethirtyeight')
def k_nearest_neighbors(data, predict, k=3):
if len(data) >= k:
warnings.warn('K is set to a value less than total voting groups!')
distances = []
for group in data:
for features in data[group]:
euclidean_distance = np.linalg.norm(np.array(features)-np.array(predict))
distances.append([euclidean_distance,group])
votes = [i[1] for i in sorted(distances)[:k]]
vote_result = Counter(votes).most_common(1)[0][0]
return vote_result
df = pd.read_csv('breast-cancer-wisconsin.data.txt')
df.replace('?',-99999, inplace=True)
df.drop(['id'], 1, inplace=True)
full_data = df.astype(float).values.tolist()
random.shuffle(full_data)
test_size = 0.2
train_set = {2:[], 4:[]}
test_set = {2:[], 4:[]}
train_data = full_data[:-int(test_size*len(full_data))]
test_data = full_data[-int(test_size*len(full_data)):]
for i in train_data:
train_set[i[-1]].append(i[:-1])
for i in test_data:
test_set[i[-1]].append(i[:-1])
correct = 0
total = 0
for group in test_set:
for data in test_set[group]:
vote = k_nearest_neighbors(train_set, data, k=5)
if group == vote:
correct += 1
total += 1
print('Accuracy:', correct/total)
I am completely stumped as to why this KeyError keeps showing up, (it also happens on the
test_set[i[-1]].append(i[:-1]) line as well.
I tried looking for people who experienced similar issues but have since found nobody with the same issue as me. As always any assistance is greatly appreciated, thank you.

Answer 1

I figured out that the error was caused by a spacing issue. When typing in the classes for the data after I downloaded it, I forgot to input the classes on their own line. I instead typed my classes right in front of the first data point causing the error to occur.