Is Google CoLab a valid replacement for Anaconda/miniconda?

Hello!

I am in the process of starting my first coding project off Codecademy and am not sure about the set up process.
I would rather just use Google CoLabs to code in because I find it much easier to work with vs locally installing Miniconda; however, I am concerned that CoLabs will not be enough…
In general, how do the two platforms mentioned above compare? Is CoLabs more limited in terms of libraries? What might be some reasons for choosing one over the other? Is there anything else I should know before getting started?

Thanks for your help!

It’s not really a matter of validity. An accurate comparison would be Colab vs. Jupyter Notebook.

Colab is based off of Jupyter but hosted in the cloud. All libraries are already there, and, if you come across one that isn’t, you can just pip install it. With Colab, you don’t have to install anything; you just add the app to your Google Drive.

I primarily use Colab and like it a lot. It’s quite powerful. (and no, I don’t work for Google. lol).
If you ever get stuck Colab is well-documented. Plus, there are code snippets in the left pane of any notebook should you ever get stuck. There are a few ways to import CSV files to it as well (which is what most CC projects will require you to do). A basic google search will bring up a few articles about how to do so. You can also push your notebooks directly to GitHub from the notebook itself via the option in the File menu drop down.
If you ever get stuck, just ask me here.

If you’re more comfortable using Colab, I say use that. :slight_smile:

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Hey @lisalisaj. Thank you very much for the detailed response!
When you say that 'An accurate comparison would be Colab vs. Jupyter Notebook’, are you suggesting that comparing CoLab to Miniconda - as I was- is kinda like comparing apples to oranges? If so, how are they distinct? Also, in terms of them being distinct, how is it then that you consider CoLab as a replacement for locally downloading Miniconda?

Thanks again!!

Miniconda3 is an Python package installer/ manager— a mini version of Conda—that you can use to install Python and it’s dependencies on Windows, Mac and Linux machines.
(I assume you have Python installed? What OS do you have?)

Colab is an app that’s based on Jupyter Notebook (looks similar to it too) where you can write and execute Python code in your web browser (you can do machine learning with it too.)
See: https://colab.research.google.com/notebooks/intro.ipynb
Also: https://docs.conda.io/en/latest/miniconda.html

And here:
https://docs.conda.io/projects/conda/en/latest/user-guide/install/download.html#anaconda-or-miniconda

I downloaded Anaconda and used Navigator to access Jupyter a long time ago. But, I don’t really use Jupyter much anymore to do data science or data analysis.

Yes, I have installed python 3 and am running MacOS big sur.
And thank you for those useful links!

What I am getting is that, similar to Miniconda, CoLabs also includes dependencies so that you can code entirely in the browser - and this is why it could be used as an alternative to Conda. Is my understanding right?

Also, data science! Very cool! Do you use CoLab for this? Or what other ‘tools’ do you consider?

Colab isn’t an alternative to Miniconda or Conda. Colab is an app where you can write and execute Python code. Miniconda is an installer/package management system where you install Python & its dependencies (libraries, etc) on your machine. Here’s an article that discusses the differences between Conda, Anaconda and Miniconda.

Add Colab to your Google Drive. Once you do, create a new notebook…from there you can import your Python libraries that you’ll need for your project, import csv files do your EDA, hypothesis testing, etc. Ex:

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Okay, I see now! Thank you for sticking with me through this, lol. I am very new to the whole thing and am slowing starting to connect the dots.

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It’s okay. There are a lot of dots to connect! :slight_smile:

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