- Filter rows:
df[df["marks"] > 70] - Combine conditions with
&(and) and|(or), each in parentheses. df.query("marks > 70")is a readable alternative.- Sort:
df.sort_values("marks", ascending=False)
Pandas Filtering & Sorting
Boolean filters and sort_values.
✍️ 3 exercises + code challenge in this lessonKey Takeaways: Pandas Filtering & Sorting
Mastering Pandas Filtering & Sorting helps you write clean and reliable Pandas code. Follow standard conventions, test edge cases, and keep logic simple. Try running the code example below and complete the exercises to build confidence.
Pandas Filtering & Sorting Code Example
Pandasimport pandas as pd
df = pd.DataFrame({
"name": ["Ali", "Sara", "Usman", "Hina"],
"dept": ["IT", "HR", "IT", "Sales"],
"salary": [120000, 95000, 110000, 88000],
})
print(df[df["salary"] > 100000])
print(df[(df["dept"] == "IT") & (df["salary"] < 115000)])
print(df.sort_values("salary", ascending=False)["name"].tolist())Output
name dept salary
0 Ali IT 120000
2 Usman IT 110000
name dept salary
2 Usman IT 110000
['Ali', 'Usman', 'Sara', 'Hina']
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Pandas Filtering & Sorting Practice Exercises
Check what you learned in “Pandas Filtering & Sorting”.
/ 3 solved
Fill in the blank
Sort by salary, highest first.
df.sort_values("salary", ascending=)
✓ Correct!
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Multiple choice
How do you combine two filter conditions with AND?
✓ Correct!
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Code challenge
Print the names of people in the IT department as a list.
Write the code in the live editor. Your answer is checked automatically.
✓ Solved
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