The Art of Effective Visualization of Multi-dimensional Data - A hands-on Approach
Descriptive Analytics is one of the core components of any analysis life-cycle pertaining to a data science project or even specific research. Data aggregation, summarization and visualization are some of the main pillars supporting this area of data analysis. However, dealing with multi-dimensional datasets with typically more than two attributes start causing problems, since our medium of data analysis and communication is typically restricted to two dimensions. We will explore some effective strategies of visualizing data in multiple dimensions (ranging from 1-D up to 6-D) using a hands-on approach with Python and popular open-source visualization libraries like matplotlib and seaborn. We will also do a brief coverage on excellent R visualization libraries like ggplot if we have time.
BONUS: We will also look at ways to visualize unstructured data with several dimensions including text, images and audio!
Outline/Structure of the Tutorial
The talk is usually a 90 minutes session but we will be covering it in the scheduled 45 minute session focusing on the main aspects of effective data visualization with the grammar of graphics, leveraging popular open-source frameworks in Python and also as a bonus cover visualization in unstructured data including text, audio and images.
Note: All the code and resources will be shared and open-sourced for your benefit! So you don't need to take extensive notes and can focus on the presentation\talk.
- What is Data Visualization?
- Why Data Visualization?
- Why Effective Data Visualization
- Effective Multi-dimensional Data Visualization
- Whirlwind tour of the grammar of graphics
- Visualization tools and frameworks
- General tools & frameworks
- Python visualization frameworks
- R visualization frameworks
- Visualizing Structured Data
- Univariate analysis and visualizations
- Multivariate analysis and visualizations
- Visualizing from 1-D up to 6-D
- BONUS: Visualizing Unstructured Data
- Final words
- Take a glance at the major data visulization frameworks
- Get a clear understanding of univariate and multi-variate visualization
- Learn effective strategies for visualizing data using the grammar of graphics
- Get a clear perspective on which visualization techniques work best based on specific scenarios
- Strategies for visualizing structured and unstructured data with actual examples
Data Enthusiasts, BI Developers, Data Scientists, Data Analysts
Prerequisites for Attendees
Knowledge of Python basics and data visualization techniques might be good but not essential since we will cover them during this session.
schedule Submitted 2 years ago
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