Course Content

# Gaining Insights with Data Visualization

Gaining Insights with Data Visualization

## Box Plots

**Box plots** are useful for visualizing the distribution of a single numeric variable and identifying potential outliers. They are particularly effective for comparing the **distribution of data** across different categories or groups.

A **box plot** consists of a box, which encloses the first and third **quartiles**, and **whiskers**, which typically extend from the quartiles to the minimum and maximum values within 1.5 times the **interquartile range**. These components make box plots an excellent tool for summarizing data distributions clearly and concisely.

# Task

- Import the
`seaborn`

library with the`sns`

alias. - Import the
`pyplot`

module of the`matplotlib`

library with the`plt`

alias. - Generate three arrays with 100 observations each, with standard deviations (
`std`

) ranging from 1 to 4, exclusive. - Use the appropriate
`seaborn`

function to create a box plot. - Display the resulting plot.

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