Python Pandas - How to select multiple rows from a DataFrame

To select multiple rows from a DataFrame, you can use various methods including slicing with the : operator, loc[] for label-based selection, and iloc[] for position-based selection.

Creating a DataFrame

First, let's create a sample DataFrame to work with ?

import pandas as pd

# Create DataFrame
dataFrame = pd.DataFrame([[10, 15], [20, 25], [30, 35], [40, 45]],
                        index=['w', 'x', 'y', 'z'],
                        columns=['a', 'b'])

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

DataFrame...
    a   b
w  10  15
x  20  25
y  30  35
z  40  45

Using Slicing with : Operator

Select multiple rows using integer positions with the slice operator ?

import pandas as pd

dataFrame = pd.DataFrame([[10, 15], [20, 25], [30, 35], [40, 45]],
                        index=['w', 'x', 'y', 'z'],
                        columns=['a', 'b'])

# Select first two rows (positions 0 and 1)
print("Select multiple rows using slicing...")
print(dataFrame[0:2])

Select multiple rows using slicing...
    a   b
w  10  15
x  20  25

Using loc[] for Label-Based Selection

Use loc[] to select rows by their index labels ?

import pandas as pd

dataFrame = pd.DataFrame([[10, 15], [20, 25], [30, 35], [40, 45]],
                        index=['w', 'x', 'y', 'z'],
                        columns=['a', 'b'])

# Select multiple rows by label
print("Select rows 'x' to 'z' using loc...")
print(dataFrame.loc['x':'z'])

# Select specific rows by labels
print("\nSelect specific rows by labels...")
print(dataFrame.loc[['w', 'z']])

Select rows 'x' to 'z' using loc...
    a   b
x  20  25
y  30  35
z  40  45

Select specific rows by labels...
    a   b
w  10  15
z  40  45

Using iloc[] for Position-Based Selection

Use iloc[] to select rows by their integer positions ?

import pandas as pd

dataFrame = pd.DataFrame([[10, 15], [20, 25], [30, 35], [40, 45]],
                        index=['w', 'x', 'y', 'z'],
                        columns=['a', 'b'])

# Select rows by integer positions
print("Select rows at positions 1 to 3 using iloc...")
print(dataFrame.iloc[1:3])

# Select specific rows by positions
print("\nSelect rows at positions 0 and 3...")
print(dataFrame.iloc[[0, 3]])

Select rows at positions 1 to 3 using iloc...
    a   b
x  20  25
y  30  35

Select rows at positions 0 and 3...
    a   b
w  10  15
z  40  45

Comparison of Methods

Conclusion

Use slicing [start:end] for simple row selection, loc[] for label-based selection, and iloc[] for position-based selection. Choose the method that best fits your data indexing needs.