Iloc Giving 'IndexError: Single Positional Indexer Is Out-Of-Bounds'

I am trying to encode some information to read into a Machine Learning model using the following

import numpy as np

import pandas as pd

import matplotlib.pyplot as py

Dataset = pd.read_csv('filename.csv', sep = ',')
X = Dataset.iloc[:,:-1].values
Y = Dataset.iloc[:,18].values
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
labelencoder_X = LabelEncoder()
X[:, 0] = labelencoder_X.fit_transform(X[:, 0])
onehotencoder = OneHotEncoder(categorical_features = [0])
X = onehotencoder.fit_transform(X).toarray()
however, I am getting an error that reads
runfile('C:/Users/name/Desktop/Machine Learning/Data preprocessing      template.py', wdir='C:/Users/taylorr2/Desktop/Machine Learning')
Traceback (most recent call last):
  File "", line 1, in 
    runfile('C:/Users/name/Desktop/Machine Learning/Data preprocessing  template.py', wdir='C:/Users/taylorr2/Desktop/Machine Learning')
IndexError: single positional indexer is out-of-bounds
I read a question on here regarding the same error and have tried
import numpy as np
import pandas as pd
import matplotlib.pyplot as py
Dataset = pd.read_csv('filename.csv', sep = ',')
table = Dataset.find(id='AlerId')
rows = table.find_all('tr')[1:]
data = [[cell.text for cell in row.find_all('td')] for row in rows]
Dataset1 = pd.DataFrame(data=data, columns=columns)
X = Dataset1.iloc[:,:-1].values
Y = Dataset1.iloc[:,18].values
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
labelencoder_X = LabelEncoder()
X[:, 0] = labelencoder_X.fit_transform(X[:, 0])
onehotencoder = OneHotEncoder(categorical_features = [0])
X = onehotencoder.fit_transform(X).toarray()
However, I think this might have just confused me more and now am in even more of a state.
Any suggestions?