Riex

Purpose of this post is to introduce 'Riex' now that it is available on CRAN and to recognize those who contributed to this effort.

It all started with a visualization project for the Data Science MS degree I'm pursuing at Saint Peter's University. We used Python to retrieve financial data via IEX free API and Databricks / AWS integration to process and create multiple dashboards to accommodate different users' preferences.

It became evident from the beginning of the project that using a both reliable data source and dependable Python library is critical to both performance and user's experience. After experimenting with multiple libraries we decided to use pyEx by Tim Paine. Personally I did appreciate the simplicity and ease of use of the library. From there the idea of an equivalent R package geared toward users who are not coders was born. ??

The idea like many others took a life of its own.. and I have to give credit to Dr. Gilkey and Prof. Supe for their encouragement and support after I expressed my interest in submitting to CRAN. Without their encouragement the package life might have ended in a presentation like some other great ideas we have and they never materialize.

Presentation from Statistical Programming course - Winter 2018

"We're building fairer markets."

IEX

I was fortunate to spend nine months working in the Financial District at a top Financial Services Company.. The experience definitely altered my perception about the industry. Besides the the charm and the unmistakable energy of the area, it was the quality of Leadership and meeting exceptional professionals like Alex Gennaro. His passion for the industry is contagious and he was more like a residing encyclopedia :) .. When I mentioned IEX, he shared the story of the Group and how they started. Thanks to him I got to learn more about high frequency trading ((HFT) and come to appreciate more the group's vision and its impact.

Since then, the idea of an R package became more than just a project and evolved to be more of my contribution to R Community and doing my part to support what I believe is a great initiative.

Submitting to CRAN

Loved every minute of it !!

There is definitely great value in submitting to CRAN specially for professionals like me who are aspiring to become Data Scientists and seeking any opportunity to follow best practices when developing tools / processes that can be used in production environment.

Special Thank you to:

• Hadley Wickham for two essential books that were greatly helpful: R Packages and Advanced R
• Dirk Eddelbuettel for maintaining Finance Task View.
• CRAN volunteers who were responsive and supportive during the submission process.
• The engaged R Community who constantly share knowledge and help each other solving issues and improve.

Riex Related Links:

• Release Announcement including examples for basic functionality
• Latest release on CRAN
• Github - To report bugs, issue , suggestions and for pull requests.