Data Visualization With Seaborn

Test how well you can create insightful plots with Seaborn.

1. What is the primary Python library that Seaborn is built on top of?
2. Which Seaborn function is used to create a histogram?
3. Which of the following are categorical plots in Seaborn?
4. Seaborn can directly plot data from a NumPy array without using a Pandas DataFrame.
5. What does the 'hue' parameter in Seaborn plots typically represent? (Answer with a single term: a type of variable)
6. Which Seaborn theme is the default when initializing the library?
7. Which parameters can be used to customize the appearance of data points in a Seaborn scatterplot?
8. The sns.regplot() function automatically fits and displays a linear regression line by default.
9. What is the exact name of the Seaborn function used to create a line plot?
10. What type of distribution does a sns.boxplot() primarily visualize?
11. Which of these are Seaborn functions used to manage color palettes?
12. Seaborn's sns.lmplot() is designed to create simple line plots without statistical modeling.
13. What does 'KDE' stand for in the context of a Seaborn KDE plot? (Full phrase)
14. Which parameter is commonly used in Seaborn functions to specify the input DataFrame?
15. Which Seaborn plots are classified as statistical data visualizations?
16. You can set the figure size directly in Seaborn plotting functions using the 'figsize' parameter.
17. Name the primary data structure (from a Python library) used to organize data for Seaborn plots (abbreviation accepted).
18. Which Seaborn function is used to create a violin plot?
19. Which of the following are Seaborn figure-level functions?
20. Seaborn plotting functions include a built-in 'title' parameter to set plot titles.
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