Projects for the course SCC0652 Computational Visualization using concepts like data processing, data visualization and interactive visualization.
Authors: Afonso Henrique, Afonso-H-P-Garcia
Breno Lívio, brenoslivio
Vitor Gratiere Torres, vitorgt
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The projects are intended for the course SCC0652 - Computational Visualization, at ICMC - USP, 2nd semester of 2020. The subjects treated were:
'Introduction: scientific, information, and software visualization. Problems and limitations of visualization. Using the computer to data analysis. Basic techniques of visualization: techniques classification and data. Organization and data types in visualization. Volume visualization techniques. Surface-based volume visualization techniques. Direct volume rendering techniques. Comparison between direct volume rendering and surface-based techniques. Vector visualization. Multidimensional data visualization: registers, text, temporal series, images and other. Attribute and instance based mapping techniques. Dimensionality reduction and its application on visualization. Associations and examples of visualization with data mining (visual data mining). Graph and tree based visualization. Visualization systems. Introduction to a visualization system. Examples and practice.'
For more information about the course check here.
Considering the course subject, we chose a Pokémon dataset to use the proper visualization techniques.
The projects are Jupyter Notebooks divided in three subjects studied throughout the course:
Choosing the Pokémon dataset, we had to process the data, cleaning, adding relevant information for the dataset. We joined a dataset from Kaggle with data scrapped from Pokémon Database.
With the data processed, we made all the different kind of visualizations with the intent of understanding the dataset even more. Notable visualizations made were Boxplot, Violin Plot, correlation heatmap for Pearson and Spearman, Scatter plot, Pairplot and Word cloud.
Finally, the last project make the visualization interactive, allowing the user explore the dataset with proper input from the keyboard and mouse. Graphs like boxplot, violin plot, scatter plot. Beyond that, we created a functional Pokédex with ipywidgets. (Important: Widgets aren't rendered properly with nbviewer).
You can check the complete documentation (Brazilian Portuguese) for the projects here.
To get a local copy up and running follow these simple steps.
Python 3.8 or greater, Jupyter Notebook. There are some libraries you may need to install for importing like ipywidgets, matplotlib and etc.
- Clone the repo
git clone https://github.com/brenoslivio/SCC0652_Computational_Visualization.git
- Simply run Jupyter Notebook to open the projects.
Distributed under the MIT License. See LICENSE for more information.