Get Started with ixamBee
Start learning 50% faster. Sign in now
Get Started with ixamBee
Start learning 50% faster. Sign in nowExplanation: Seaborn is a powerful Python library built on Matplotlib, designed specifically for statistical visualization. It simplifies creating complex plots like violin plots, heatmaps, and pair plots, which are essential for understanding relationships, distributions, and correlations in data. Seaborn’s high-level interface and themes make it easier to create visually appealing plots suitable for data storytelling. For instance, a heatmap generated with Seaborn provides immediate insights into correlations between variables, a crucial aspect of exploratory data analysis. Option A: NumPy handles numerical operations and array processing but does not focus on visualization. Option B: While pandas is excellent for data manipulation, its plotting capabilities are basic. Option C: Matplotlib provides general-purpose plotting but lacks the simplicity and aesthetics of Seaborn for statistical plots. Option E: SciPy focuses on advanced scientific computation, not visualization.
Select the number that can replace the question mark (?) in the following series.
Select the number which can be placed in the column of question mark sign.
Find the missing number.
20, 30, 42, 56, 72, ?
Study the given matric carefully and select the number from among the given options that can replace the question mark (?) in it.
What will come in the place of question mark?
Select the missing number from the given responses:
Find the missing number.
. 
Select the number from among the given options that can replace the question mark (?) in the following table.
Find the missing number.
Study the given pattern carefully and select the number that can replace the question mark (?) in it.
