Dataset Visualization with Python 02

Main Idea

Continuation. In this scenario, participants learn how to visualize randomized datasets using Python.

Creator Lana Sattelmaier
Subject Computer science
Length 45 minutes
Pedagogical Approach

Experiential learning, Project-based Learning

Competences

C01 Abstraction

C02 Decomposition

C04 Patterns

C12 Programming

C29 Visualization of Datasets

Grades Grades 7-9
Technologies

Participants will need a computer with internet access, an integrated development environment (IDE) such as Visual Studio Code, and Python installed.

Evaluation

Observe student engagement and proficiency in using the AI tools.

 

Learning Activities

Description Continuation of the Learning Activities builds upon the knowledge and skills acquired, allowing participants to deepen their programming and visualization abilities. The structure promotes active learning and practical application of Python for data visualization within a defined time frame.

LA1: Contextualization (5 minutes)

The instructor briefly recalls the purpose of the previous session:

  • Reviewing the importance of data visualization in Python for analyzing and interpreting randomized datasets.
  • Emphasis on the practical application of programming for creating and customizing visualizations.

LA2: Worksheet (30 minutes)

  • Participants work on the worksheet:
    • Deepening the creation and customization of visualizations for randomized datasets.
    • Using Matplotlib (or Seaborn) to create various visualizations such as scatter plots, histograms, and box plots.
    • Independently modifying the provided code to explore different parameters, data distributions, and scales.
  • Instructor support for questions and encouraging discussions on the interpreted results of the visualizations.

LA3: Presentation and Discussion (10 minutes)

Conclusional Discussion:

  • The instructor moderates a discussion on the developed visualizations and their insights.
  • Reflection on individual challenges and learning progress during the exercise.
 

Materials

Worksheet: Here