https://github.com/amitkaps/dsvis

Data Visualisation for Data Science
https://github.com/amitkaps/dsvis

data-science data-visualization interactive multi-dimensional python r

Last synced: about 6 hours ago
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Data Visualisation for Data Science

• Host: GitHub
• URL: https://github.com/amitkaps/dsvis
• Owner: amitkaps
• License: mit
• Created: 2017-08-26T08:35:44.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2017-08-27T11:48:32.000Z (about 7 years ago)
• Last Synced: 2024-04-15T00:35:58.890Z (7 months ago)
• Topics: data-science, data-visualization, interactive, multi-dimensional, python, r
• Language: Jupyter Notebook
• Size: 5.3 MB
• Stars: 3
• Watchers: 4
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Data Visualisation for Data Science

Visualisation plays a key component during the entire data science process - in exploratory data analysis, model visualisation as well as in communicating the results through a narrative or a dashboard. The goal of this workshop is to help you gain a deeper understanding on the art and science of data visualisation.

**Structure of the workshop**

- Intro to visualization

  - Understand Exploratory Data Analysis (EDA)

  - Role of model visualisation 

  - Communicating insights using visualisation

- The Grammar of Graphics

  - Visualizing single & dual variables

  - Visualizing categorical data

- Visualizing Multi-Dimensional Data

  - Using aesthetics and facets for more than two variables

  - Using matrix view, parallel coordinates for more than two variables

- Communicating with graphs

  - Graphical perception and critique

  - Understand color, scales, labeling and annotation

  - Theming and publication ready graphics

- Interactive graphics

  - Creating interactive graphs for the web

  - Allowing interactive data-model manipulation

- Visualizing geo-spatial data

- Creating Interactive Data Dashboards

- Model Visualization

**Broad Schedule for the workshop**  

0930 - 1000: Installation   

1000 - 1130: Session 1: Grammar of Graphs, 1D & 2D Vis  

1130 - 1145: Tea Break  

1145 - 1330: Session 2: Multi Dimensional Visualisation  

1330 - 1415: Lunch  

1415 - 1500: Project Discussion  

1500 - 1600: Session 3: Interactive Data Visualisation  

1600 - 1615: TeaBreak  

1615 - 1800: Session 4: Model Visualisation