title	layout	weight	hidden
Visualizations in Matplotlib	post	10	true

​ ​ Course: Data Science
Mod: 1
Topic: Visualizations in Matplotlib
Amount of time: 1.5 hours
Author: Alison.
​​Ported from the ds-lesson-starters-repo here.

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Lesson Summary:

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Topic:

Visualizations in Matplotlib

Learn.co material:

https://github.com/learn-co-curriculum/dsc-more-practice-with-matplotlib-lab-data-science https://github.com/learn-co-curriculum/dsc-1-01-23-visualizing-data https://github.com/learn-co-curriculum/dsc-1-01-24-visualizing-data-lab

Prerequisite knowledge/ Prework:

• Python data structures (lists, dictionaries)
• Pandas

Learning goals for this lesson:

• Explain and understand different types plots and their use cases
• Identify and adjust the anatomy of a matplotlib plot
• Explain the difference between plot types and justify their use cases:
  • barplots
  • histogram
  • scatter plot
  • pie char
• Visualize data using the matplotlib library in python

Misconceptions:

Materials

• Slides (link here)
• Working files accessible to students (link here)

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Lesson Outline:

Step: Problem
Time: 5 min

Goal/Scenario:
Same animal shelter dataset!! Those poor animals!

Learning Goals in sequence:

• Explain and understand different types plots and their use cases
• Identify and adjust the anatomy of a matplotlib plot
• Explain the difference between plot types and justify their use cases:
  • barplots
  • histogram
  • scatter plot
  • pie char
• Visualize data using the matplotlib library in python

Step: Activation
Time: 5 min

Discussion prompts:

• why are visualizations important?

Step: Learning Goal 1: Explain and understand different types plots and their use cases
Time: 17 min

Demonstrate: 10 min

Application: 3 min

Informal assessment: 2 min

Step: Learning Goal 2: Identify and adjust the anatomy of a matplotlib plot
Time: 16 min

Demonstrate: 15 min

• Introduce syntax for labelling and styling in Matplotlib
• Show examples of how we can change colors and styles of lines/graphs/labels

Application: 3 min

• Students add labels and styles to their existing visualizations

Informal assessment: 2 min
"Quick fist of five check, how confident do we feel about moving on? zero is not at all comfortable. five is ready to go."

• follow up with those students who do not feel confident

Step: Learning Goal 3: Explain the difference between plot types and justify their use cases
Time: 25 min

Synthesis: 1 min

Application: 18 min

Step: Integration: Visualize data using the matplotlib library in python

Step: Assessment:
Time: 5 min

• Have selected pairs of students share their findings

Step: Reflection:
Time: 1 min

• What are your takeaways from learning about visualizations?