Learn The `iloc` Property | Fetching Data from DataFrames

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The iloc property in Pandas allows us to access specific parts of a DataFrame using numerical positions.

You can use iloc to access:

A single element;
A single row;
A single column;
A range of rows;
A range of columns;
A range of rows and columns.

General Syntax

DataFrame.iloc[row_position, column_position]

You can also slice:

DataFrame.iloc[start_row:end_row, start_col:end_col]

Example


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import pandas as pd

df = pd.DataFrame({
    'Name': ['Alice', 'Bob', 'Charlie', 'Daisy'],
    'Age': [25, 30, 35, 28],
    'City': ['New York', 'Paris', 'London', 'Berlin']
})

# Single element
print('>> Single Element:\n', df.iloc[1, 2])

# Single row
print('\n>> Single Row:\n', df.iloc[2])

# Single column
print('\n>> Single Column:\n', df.iloc[:, 1])

# Range of rows
print('\n>> Range of Rows:\n', df.iloc[1:3])

# Range of columns
print('\n>> Range of Columns:\n', df.iloc[:, 0:2])

# Range of rows and columns
print('\n>> Range of Rows & Columns:\n', df.iloc[1:3, 0:2])

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Section 3. Chapter 10

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Section 3. Chapter 10