You've learned how to check DataFrame shape with .shape and inspect column details with .info(). These are your primary tools for understanding your data's structure and quality.
Let's practice using these tools together to become a data inspection expert.
Engagement Message
Ready to sharpen your detective skills?
Type
Multiple Choice
Practice Question
You've loaded a DataFrame called sales_df and run sales_df.shape. The output is (2500, 6). What does this tell you?
A. The DataFrame has 2500 columns and 6 rows B. The DataFrame has 2500 rows and 6 columns C. The DataFrame has 2500 total data points D. The DataFrame uses 2500 MB of memory
Suggested Answers
- A
- B - Correct
- C
- D
Type
Swipe Left or Right
Practice Question
Match each data type with what it typically represents by swiping left or right.
Labels
- Left Label: Numeric Data Types
- Right Label: Text Data Type
Left Label Items
- int64: whole numbers like age or quantity
- float64: decimal numbers like price or rating
- Numbers you can calculate with
- Data types good for mathematical operations
Right Label Items
