iloc giving 'IndexError: single positional indexer is out-of-bounds'

It does not help for the solution of the question here, but whoever might come here for the error and not for the example, I had this error IndexError: single positional indexer is out-of-bounds when I tried to find a row in a dataframe2 while looping over the rows of dataframe1, using many criteria in the filter of dataframe2, and adding each found row to a new empty dataframe3 (Do not ask me why!). One of the values in the row was a "nan" value both in dataframe1 and dataframe2. I could not filter anymore nor add a new row.

Solution:

dataframe1.fillna("nan") # or whatever you want as a fill value
dataframe2.fillna("nan")

and the script ran through without the error.

This error is caused by:

Y = Dataset.iloc[:,18].values

Indexing is out of bounds here most probably because there are less than 19 columns in your Dataset, so column 18 does not exist. The following code you provided doesn't use Y at all, so you can just comment out this line for now.

This happens when you index a row/column with a number that is larger than the dimensions of your dataframe. For instance, getting the eleventh column when you have only three.

import pandas as pd

df = pd.DataFrame({'Name': ['Mark', 'Laura', 'Adam', 'Roger', 'Anna'],
                   'City': ['Lisbon', 'Montreal', 'Lisbon', 'Berlin', 'Glasgow'],
                   'Car': ['Tesla', 'Audi', 'Porsche', 'Ford', 'Honda']})

You have 5 rows and three columns:

    Name      City      Car
0   Mark    Lisbon    Tesla
1  Laura  Montreal     Audi
2   Adam    Lisbon  Porsche
3  Roger    Berlin     Ford
4   Anna   Glasgow    Honda

Let's try to index the eleventh column (it doesn't exist):

df.iloc[:, 10] # there is obviously no 11th column

IndexError: single positional indexer is out-of-bounds

If you are a beginner with Python, remember that df.iloc[:, 10] would refer to the eleventh column.