Pandas & Data Analysis·Pandas from first Series to analysis project

Selecting and filtering

Use loc, iloc and boolean masks to select exactly the rows you mean.

Beginner 13 min read Lesson 5 of 300 Challenge included

What you will be able to do

Use df.loc[rows, columns] for label selection.
Use df.iloc for positional selection.
Wrap each condition in parentheses.
Use .isin for membership tests.

In plain English

loc selects by label, iloc selects by position and a boolean mask selects by condition. Use .loc for assignment. Combine conditions with & and |, wrapped in parentheses.

filter.pyPython

import pandas as pd

df = pd.DataFrame({
    'course': ['HTML', 'CSS', 'SQL', 'CSS'],
    'minutes': [12, 18, 9, 22],
})

long_css = df[(df['course'] == 'CSS') & (df['minutes'] >= 20)]
print(long_css)
print(df.loc[df['minutes'].idxmax()])

Your turn

Filter with two conditions

Easy

Select rows where course is CSS and minutes are at least 15.

PYTHON · starter

df[df['course'] == 'CSS']

Check your understanding before moving on.

Knowledge checkQuestion 1

Which accessor selects by label?

Select an answer to continue

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Lesson 5 of 300 · 0% of course