"Visualization is a fundamentally human activity."
Are you interested in the relationship between the reviews and streams of music? Please have a look at our EDAV project: Review vs. Stream.
What is EDAV
- Exploratory data analysis and visualization (EDAV) is an interdisciplinary field combining
- Computer Science
- Graphic Design
- Subject Expertise
- The task of EDAV is to
- Look for patterns
- Identify outliers
- Make comparisons
- Discover clusters
- The fundamental problem of EDAV is
- Exploration vs. Visualization
- or, Exploratory vs. Explanatory
- Explorations reveal information hidden in the data, which is deep and precise but can be convoluted
- Visualizations offer insight into the data, which can be easily shared but may be misleading and biased
- These two aspects are not mutually exclusive
- Continuous Variable
- Categorical Data
- Dependency Relationship
- Multivariate Continuous Data
- Multivariate Categorical Data
- Time Series
- Spatial Data
- Missing Data
- For Plots Gallery:
- Robbins, Joyce. https://edav.info. 2022.
- Unwin, Antony. Graphical data analysis with R. Chapman and Hall/CRC, 2018.
- For R Garden:
- Wickham, Hadley, and Garrett Grolemund. R for data science: import, tidy, transform, visualize, and model data. O'Reilly Media, Inc., 2017.
- For Git Garden:
- Chacon, Scott, and Ben Straub. Pro Git. Springer Nature, 2014.
- For WebDev Garden
- Robbins, Joyce. D3 for R Users. 2022.
In plain English: A collection of notes. ↩︎