Filtering Rows and Selecting Columns (The Right Way)

📰 Dev.to · Akhilesh

Learn the efficient way to filter rows and select columns in pandas DataFrames for better data analysis

intermediate Published 26 Apr 2026

Action Steps

Import the pandas library using 'import pandas as pd'
Create a sample DataFrame using 'df = pd.DataFrame({'column1': [1, 2, 3], 'column2': [4, 5, 6]})'
Select a column using 'df['column1']'
Filter rows using conditional statements like 'df[df['column1'] > 2]'
Use the 'loc' indexer to select rows and columns like 'df.loc[:, 'column1']'

Who Needs to Know This

Data scientists and analysts can benefit from this lesson to improve their data manipulation skills, while software engineers can apply these techniques to data-intensive applications

Key Insight

💡 Using the 'loc' indexer is a flexible and efficient way to select rows and columns in pandas DataFrames