Choosing a coding environment outside of code academy

Hi! I have been learning to code both Python and R using your online platform, but I’m having trouble understanding the wide array of other “environments” you can code in (Rstudio, R, Jupyter Notebooks, Jupyter Labs, Notebooks AI, anaconda, github, google collab, compilers, terminals, interpreters… I’m overwhelmed!!). Are there any articles I can read that can give me a solid comparison/ understanding of all these different options? I don’t even know if “environment” is the right term for what I’m trying to compare, and categorizing the things I’ve listed into different types of tools would even be somewhat useful (though I’m hoping to figure things out in more detail than that).

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Hi, welcome to the forums.

I don’t know R, but I do know that Rstudio is free and it’s an open-source IDE (Integrated Development Environment).

I use both Jupyter Notebook and Google Colab for data analysis and science. More so Colab now b/c there’s no installation and it’s based on Jupyter but is a cloud-based application that you just add to your Google Drive (like Sheets, Meet, Docs, etc.)

Anaconda Navigator is a GUI that allows you to launch Python (& R) packages in a web browser. Their documentation is here:

And, here.

And Colab links here.

Or, you could just go to your Google Drive and click on the “+” and select "New > More > Connect More Apps. It should be in their marketplace.

Are you on a Mac or Windows? (I ask b/c that will determine how you install Jupyter Notebook if you choose to do so).


Thanks for your reply. To be clearer, I understand how to install and even use some of these tools, I am looking for a high level conceptual overview that compares or categorizes them. For instance, you use the word GUI but I don’t know what that is

GUI = Graphical User Interface

What tools you use will depend on what you want to accomplish w/Python or R. What kind of code are you writing? Are you doing machine learning? Predictive analytics? EDA (Exploratory data analysis?) You can do all of that in either Jupyter or Colab. I think it boils down to an individual’s preference what app they want to use.

A basic google search will be able to give you more in depth overviews than what I described above. Look at the Medium blog, “Towards Data Science” or the site Geeksforgeeks for starters.