You've learned to find duplicates with .duplicated()
, remove them with .drop_duplicates()
, and fix data types with .astype()
. Now let's practice combining these skills for complete data cleaning.
These techniques often work together to transform messy data into analysis-ready datasets.
Engagement Message
Ready to practice your data cleaning workflow?
Type
Fill In The Blanks
Markdown With Blanks
You have a sales dataset with potential duplicates. Fill in the blanks to check for and remove duplicate orders.
Suggested Answers
- duplicated
- sum
- drop_duplicates
Type
Multiple Choice
Practice Question
You check a DataFrame's data types and see:
Which columns likely need data type conversion?
A. product_id and category B. price and quantity C. product_id and price D. quantity and category
Suggested Answers
- A
- B
- C - Correct
- D
Type
Sort Into Boxes
