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#Automatic Data Visualization

The goal of the project was to design heuristic rules to automatically visualize various types of data. It combines statistical analysis, unsupervised/clustering methods along with the wide variety of visualization techniques Wolfram Language has to offer.

'A picture is worth a thousand words' - While trying to obtain information from large volumes of data, it is useful to visualize it in a meaningful way. However, the greatest challenge is to find the appropriate tool to visualize the underlying data. In this project, we have explored the various kinds of data visualization tools the Wolfram Language offers, and have come up with automatic rules to infer the data type and decide automatically the exact plot type to use for the data. As the Wolfram Data Repository offers a large amount of curated data, we used examples from there.

As large volumes of data imply a high number of visualization methods, there are way more informative visualization techniques that can be explored further.

https://datarepository.wolframcloud.com/

automated visualization data analysis wolfram data repository

As mentioned above the function was primarily written for data objects of the Wolfram Data Repository. When applying the function to data it should give you an nice overview and hopefully helps to reduce time to understand the underlying data, to find relationships, and to get the information searched.

A package was created to easily access the function and getting use of its functionality.

Load it: Needs[autoWiz`] and make sure that the package is in the same directory as your notebook (type SetDirectory[NotebookDirectory[]]) use it by call MainFunction[ResourceObject["xx"], int] where xx refers to a data object of the Wolfram Data Repository and int is the sample size (if you are not putting something inside here 10 is set as default variable).