MISSION 145

Histograms and Box Plots

In the last mission, we learned how to create bar plots in Python to compare the average user rating a movie received from four movie review sites. We also learned how to create scatter plots to explore how ratings on one site compared with ratings on another site. We ended the mission with the observations that user ratings from Metacritic and Rotten Tomatoes spanned a larger range (1.0 to 5.0), while those from Fandango and IMDB typically spanned a smaller range (2.5 to 5 and 2 to 5 respectively).

In this mission, we'll learn how to visualize the distributions of user ratings using histograms and box plots. As we do that, we'll continue working on our own investigation of whether Fandango’s movie review ratings might be biased, based on the investigation conducted by FiveThirtyEight.

As with every mission at Dataquest, you'll be given an opportunity to practice each concept using our code editor with built-in answer checking to ensure that you've mastered a concept before moving on to this next.

Objectives

  • How to create a histogram and box plot.
  • How to compare multiple graphs to each other.

Mission Outline

1. Introduction
2. Frequency Distribution
3. Binning
4. Histogram In Matplotlib
5. Comparing histograms
6. Quartiles
7. Box Plot
8. Multiple Box Plots
9. Next steps
10. Takeaways

exploratory-data-visualization

Course Info:

Beginner

The median completion time for this course is 7.02 hours. View details

This course is requires a basic subscription and includes four missions and one guided project.  It is the fourth course in the Data Analyst in Python path and Data Scientist in Python path.

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