Slicing DataFrame with .loc in Pandas

Last update on April 09 2025 12:51:14 (UTC/GMT +8 hours)

12. .loc Slicing Based on Row and Column Labels

Write a Pandas program that uses .loc to slice DataFrame based on row and column labels.

Sample Solution :

Python Code :

import pandas as pd

# Create a DataFrame
df = pd.DataFrame({
    'X': [1, 6, 8, 3, 7],
    'Y': [5, 2, 9, 4, 1],
    'Z': [7, 8, 9, 1, 2]
})

# Slice DataFrame using .loc
result = df.loc[1:3, ['X', 'Z']]
print(result)

Output:

   X  Z
1  6  8
2  8  9
3  3  1

Explanation:

• Import pandas library.
• Create a DataFrame.
• Use .loc to slice rows from index 1 to 3 and select columns 'X' and 'Z'.
• Print the results.

For more Practice: Solve these Related Problems:

• Write a Pandas program to slice a DataFrame using .loc by specifying both row and column label ranges.
• Write a Pandas program to extract a block of data from a DataFrame using .loc with label-based slicing.
• Write a Pandas program to select a subset of rows and columns using .loc and then compute a statistical summary of the result.
• Write a Pandas program to use .loc to slice a DataFrame and then plot the selected data using a line chart.

Python-Pandas Code Editor:

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