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

7.3K Asked by DrucillaTutt in Python , Asked on Apr 15, 2021

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?

Answered by Drucilla Tutt

The code indexerror: single positional indexer is out-of-bounds, shows that you misunderstood iloc function. The value before the colon(:) is the index of rows and the after ‘:’ represents the index of columns.

As stated above by you, You have less than 19 features in your dataset. But you are passing the index value of the 19th feature. That’s why this error is there.

You should change the value according to the number of features in your datasets.

This code in which error is caused by:

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

Hope this answer helps.

Your Answer

Answer (1)

Ranjana

The "IndexError: Single positional indexer is out-of-bounds" error typically occurs when using the iloc method in Python's pandas library to access elements of a DataFrame using an index that is out of range. Here are some common reasons why you might encounter this error and how to resolve it:

Invalid Index Value: Ensure that the index value you're using with iloc is within the valid range of the DataFrame's index. Remember that Python uses zero-based indexing, so valid index values range from 0 to len(df) - 1, where df is your DataFrame.

Empty DataFrame: If your DataFrame is empty (i.e., it has zero rows), attempting to access any element using iloc will result in this error. Make sure your DataFrame contains data before using iloc.

Incorrect Column or Row Index: Double-check that you're specifying the correct index for either the rows or columns depending on how you're using iloc. For example, if you're accessing a row, ensure the index value corresponds to the row number, and if you're accessing a column, ensure the index value corresponds to the column number.

Multi-dimensional Indexing: If you're trying to access elements of a DataFrame with multi-dimensional indexing using iloc, ensure that the index values provided are within the bounds of both dimensions.

Indexing beyond DataFrame Shape: Avoid attempting to access elements beyond the shape of the DataFrame. For example, if you have a DataFrame with dimensions n rows by m columns, attempting to access element (n+1, m) or (n, m+1) using iloc will result in this error.

Here's an example of how you might use iloc correctly to access DataFrame elements:

import pandas as pd

# Create a sample DataFrame

df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})

# Accessing a specific element by row and column index

element = df.iloc[0, 1]  # Accesses the element in the first row, second column

print(element)

Ensure that you're following these guidelines when using iloc to access elements in your DataFrame, and verify that the index values you're providing are valid for the size and shape of your DataFrame.

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