The Fifth Elephant 2019

Gathering of 1000+ practitioners from the data ecosystem

Become Language Agnostic by Combining the Power of R with Python using Reticulate

Submitted by \AbdulMajedRaja (@amrrs) on Apr 15, 2019

Session type: Workshop Status: Rejected

Abstract

Language Wars have always been there for ages and it’s got a new candidate with Data science booming - R vs Python. While the fans are fighting R vs Python, the creators (Hadley Wickham (Chief DS @ RStudio) and Wes McKinney (Creator of Pandas Project)) are working together as Ursa Labs team to create open source data science tools. A similar effort by RStudio has given birth to Reticulate (R Interface to Python) that helps programmers combine R and Python in the same code, session and project and create a new kind of super hero.

Outline

Why R and Python?
Introduction to Reticulate
Python Engine
Code Outline
Sample Use-case explanation
Potential use-cases to create a new super power

Duration of the workshop. - ~2 hours
Background knowledge required to participate in the workshop. What concepts/technologies should participants be familiar with in order to attend the workshop. - Knowledge of R and Python. Use of RStudio and Python installation
Target audience: who should attend the workshop? - Datascientist / Consultant who wants to leverage the power of both R and Python for their Projects
Who should NOT attend this workshop. - This isn’t for someone who wants to learn R or Python or any other Data science Concepts
Why attend this workshop? What will participants learn from attending this workshop? How will they benefit? - Understanding the capability of using Python with R. Learning the technical acumens of it and ideas to incorporate it in their own Workflows.
Detailed workshop plan
- Why R and Python?
* Moving away from R vs Python
* Cases where both the langauges together will help
- Introduction to Reticulate
* What’s about the package reticulate
* How to install reticulate
* Basic Functions
- Python Engine
* Understanding about Python Engine in the local Machine
* Select Different Engine for Reticulate Session
- Code Outline
* Layout/Structure of the Code
* Presence of R
* Presence of Python
* Object Interaction
- Sample Use-case Explanation
* What’s the use-case
* Spacy - Outline
* RMarkdown - Outline
* Combining Spacy and Rmarkdown with Reticuate
* NLP Analysis Report
- Potential use-cases to create a new super power
* Use-cases that audience can take back
Requirements.
- R, RStudio, Python (with Enviroment Path configured)
- reticulate - Package installed
- Github Repo contents
- Necessary Python Packages
- Basic Computer Configuration - Any OS, Basic RAM (~2+ GB)

Requirements

  • Knowledge of R and Python

Speaker bio

Abdul Majed is an Analytics Consultant helping Organizations make sense some out of the massive - often not knowing what to do - data. Married to R (but dating Python). Always amazed by Open Source and its contributors and trying to be one of them.

Organizer @ Bengaluru R user Group (BRUG) Organizer

Contributed to Open source by publishing packages on CRAN and PyPi

Writer @ Towards Data Science and DataScience+

Links

Slides

https://github.com/amrrs/python_plus_r_brug/blob/master/py_plus_r.pdf

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