Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Impara Box Plots | Gaining Insights with Data Visualization
Gaining Insights with Data Visualization
course content

Contenuti del Corso

Gaining Insights with Data Visualization

book
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.

Compito

Swipe to start coding

  1. Import the seaborn library with the sns alias.
  2. Import the pyplot module of the matplotlib library with the plt alias.
  3. Generate three arrays with 100 observations each, with standard deviations (std) ranging from 1 to 4, exclusive.
  4. Use the appropriate seaborn function to create a box plot.
  5. Display the resulting plot.

Soluzione

Mark tasks as Completed
Switch to desktopCambia al desktop per esercitarti nel mondo realeContinua da dove ti trovi utilizzando una delle opzioni seguenti
Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 1. Capitolo 2
AVAILABLE TO ULTIMATE ONLY
Siamo spiacenti che qualcosa sia andato storto. Cosa è successo?
some-alt