Python Pandas - How to select rows from a DataFrame by integer location

To select rows by integer location in a Pandas DataFrame, use the iloc accessor. The iloc method allows you to select rows and columns by their integer position, starting from 0.

Creating a Sample DataFrame

Let's start by creating a DataFrame to work with ?

import pandas as pd

# Create DataFrame
dataFrame = pd.DataFrame([[10, 15], [20, 25], [30, 35]], 
                        index=['x', 'y', 'z'], 
                        columns=['a', 'b'])

print("DataFrame...")
print(dataFrame)

DataFrame...
    a   b
x  10  15
y  20  25
z  30  35

Selecting a Single Row by Integer Location

Use iloc[index] to select a single row by its integer position ?

import pandas as pd

dataFrame = pd.DataFrame([[10, 15], [20, 25], [30, 35]], 
                        index=['x', 'y', 'z'], 
                        columns=['a', 'b'])

# Select row at integer location 1 (second row)
print("Select row by integer location 1:")
print(dataFrame.iloc[1])

Select row by integer location 1:
a    20
b    25
Name: y, dtype: int64

Selecting Multiple Rows

You can select multiple rows by passing a list of integer positions ?

import pandas as pd

dataFrame = pd.DataFrame([[10, 15], [20, 25], [30, 35]], 
                        index=['x', 'y', 'z'], 
                        columns=['a', 'b'])

# Select rows at positions 0 and 2
print("Select multiple rows by integer location:")
print(dataFrame.iloc[[0, 2]])

Select multiple rows by integer location:
    a   b
x  10  15
z  30  35

Using Slicing with iloc

You can also use slicing to select a range of rows ?

import pandas as pd

dataFrame = pd.DataFrame([[10, 15], [20, 25], [30, 35]], 
                        index=['x', 'y', 'z'], 
                        columns=['a', 'b'])

# Select rows from position 0 to 1 (exclusive of 2)
print("Select rows using slice notation:")
print(dataFrame.iloc[0:2])

Select rows using slice notation:
    a   b
x  10  15
y  20  25

Comparison: iloc vs loc

Conclusion

Use iloc to select rows by integer position in a DataFrame. It supports single row selection, multiple rows with lists, and range selection with slicing notation.