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RADVisualizer

As the human race stepped into the infromation age, Data explosion has been one of the biggest things that occured in the past few decades. It came as no surprise that the Data Scientist role has been considered the sexiest job of the 21st century. The number of roles in the field have reached all time highs. Yet, there is still a dire need for good data scientists in the community. At this moment, one has to ask Why hasn't such abundance of data and the massive interest in data science projects among the community sufficed to solve the need for data scientists? We believe the answer is simple. Most of the data science roles in the industry require a strong background in statistics coupled with a strong background in programming using Python, R, Java etc. This implies that a majority of people might be unable to match the required skillset! Consider the statisticians who do not have a background in coding or Business Intelligence majors who could identify some key patterns which could go unnoticed from the usual CS/ECE developers for instance.

Shiny DataScience is a web application which is built with just solving this goal in mind. We believe bridging the gap between the non-coder and data science.

The application provides a set of unique and helpful features that we believe could help a lot of people join the Data Science realm. The user can upload data files on the web app and receive a quick summary of the data,visualize it and also run machine learning models and more without writing a single Line of Code! The intention is far from discouraging people from learning Programming. On the contrary, we would like to provide an interactive learning experience through the application. This is the primary reason why we have a code-block which displays the code used to generate the plot/run an algorithm for every tool on the web app. This is just the opposite way a Notebook works. Usually, the user writes the code and then observes its output. Here, we let the user generate the output using a GUI and then display the back end code which is generated dynamically based on custom user inputs. We aim at creating a GUI which provides a comprehensive set of options avaialable from the packages so the user can have a truly unique and complete learning experience.

[PROJECT FEATURES]

Developing a customer-centric and customer-driven product was the main goal of the team for Shiny Data Science. This has led us develop some features which we believe will not only ensure user growth, but also benefit the entire community and ecosystem of the application. Features include :

  1. Simple and intuituve UI for the beginner data scientist created with JavaScript and Shiny.
  2. A quick overview of the data at the finger tips of the user with a set of popular data visualizations and machine learning tools.
  3. Uses an innovative way to teach users by first letting them generate visualizations and then make them understand the code
  4. Uses R for data processing which is one of the most popular languages among the data science community.
  5. Its open-source, duh!

*We are aware we have a long way to go to create a complete project. But it is the need of the hour to develop and promote open-soruce tools aimed for beginners interested in data science to assist them in effectively using data technologies. Shiny DataScience is here to help the current open-source community and more importantly, ensure it's growth to all corners of the world.

BUILD/INSTALLATION INSTRUCTIONS

The packages can be installed from CRAN:

  • install.packages(shiny)
  • install.packages(ggplot2)
  • install.packages(shinydashboard)
  • install.packages(colourpicker)
  • install.packages(leaflet)
  • install.packages(dplyr)

Contributor Guide

Contributer Guide

License

Released under the GPL-3 License.