R and Python coding with Prython

Name: R and Python coding with Prython
Rating: 4.1 (24 reviews)

Learn how to use the newest R/Python IDE (integrated development environment) for data science, analytics and ML

Created byFrancisco Juretig

Last updated 11/2020

English

What you'll learn

Learn how to use Prython for coding both R and Python projects
Design complex data science projects in Prython

Course content

2 sections • 8 lectures • 29m total length

Introduction8:12
Prython is a new R/Python IDE that allows you to place your code in panels, connect them, and run. It's ideal anyone doing data science, analytics, or data processing in Python or R. It runs on your local computer, and is free to use. It is specially useful for those who want to test lots of variations of their code, or want to organise their projects in a much cleaner way than Jupiter or RStudio. In this course we will review how to setup some R/Python projects, both for data processing and ML/AI.
Installing3:12
Here we will review how to install Prython in Windows. After we do that, we will configure the Python and R kernels, and at that point we will be able to start using it. At the end of this video we will try re-running one of Prython's available projects.

Panels6:28
In this video we will do an in-depth review of panels in Prython. How to use the three available run modes, how to open the code editor, and how to connect our panels and run everything together. We will learn how to keep track of dataframes and the changes made to them in our code.
Consoles3:19
Consoles can be attached to any panel, allowing us to run code line by line. This is useful both for reviewing the values for any object/variable, and also to modify those variables or test some code. For example, if we are creating a pandas dataframe in a complex code; and we then want to change it without re-running everything in order to test something, we can just attach a console and test our change there. Consoles work both for Python and R.
Markers2:04
Prython projects can get really big, and navigating thru the canvas can be quite hard. One option is to create markers that can be clicked in order to get redirected. These markers appear on the left lower side of the screen
Linkedpanels2:54
Linked panels can be used to copy and replicate the contents of panels. This allows us to test multiple changes to our code whilst keeping track of all the results
Extra tools for organising our projects2:44
In this video we will use frames and brackets to group panels sharing similar functionality. Also, we will learn how to insert notes where we can keep track of our comments.
Exporting1:05
In this video, we will learn how to export our code so we can re-run it in Python or R outside of Prython.

Requirements

Know some Python and/or R
Basic knowledge about data science and analytics

Description

In this course we will learn how to use Prython, which offers a different way of coding than existing R/Python IDEs. It allows us to drop our code into panels that we place and connect in a canvas. In a normal IDE your code will run linearly from start to end, making it really hard to create sub-experiments/tests, and also to organise your project clearly. In Prython each panel accepts multiple IN and OUT connections, effectively transforming it into a 2D Jupiter notebook. It also has a wide array of tools that complement this canvas functionality: such as displaying dataframes next to the panels that modified them, allowing you to freeze your outputs, attaching consoles, navigation markers, etc.

We assume that the student is already familiar with R or Python, and some familiarity with matplotlib, scikit-learn,or keras would be beneficial as well.

Who this course is for:

Python and R practitioners with a focus on data science
ML engineers
Statisticians, engineers, and economists designing statistical models

R and Python coding with Prython

What you'll learn

Explore related topics

Course content

Introduction2 lectures • 11min

Core Prython components6 lectures • 19min

Requirements

Description

Who this course is for: