Guide: Setup Your System

Guide: Setup Your System

As you begin your journey as a Data Scientist, it is important to get familiar with tools on your own system in addition to tools in your web browser. There are several major advantages to running code locally:

  • You can use datasets on your computer (without needing to uploading them online),
  • You are not restricted to the compute time or memory limits on web-based notebooks,
  • You keep your code and data secure by not having it on a cloud platform,
  • and more!

We will present small examples using online notebook environments, but labs and projects will be done on your own machine.

Jupyter Notebooks on Visual Studio Code

The current best free tool for Python notebooks is Visual Studio Code by Microsoft (free and open source, and an industry-standard tool used by millions of programmers daily):

Installing the Jupyter Plugin

Once you have installed VS Code, you will need the python and jupyter plugin to run Jupyter notebooks. Both of these plugins are built by Microsoft and are also free and open-source:

  • In Visual Studio Code, find the left panel and select the icon with multiple square boxes that is labeled "Extensions" if you hover over it.
Extension button found in Visual Studio Code (found on the left side of VS Code interface)
  • In the "Extensions" window, search for python and find the Python plugin by Microsoft and install it:
Python Extension for Visual Studio Code
  • In the same "Extensions" window, search for jupyter and find the Python plugin by Microsoft and install it as well:
Jupyter Extension for Visual Studio Code

Finalizing Configuration

Once you have the python and jupyter extensions installed, make sure you can run a Python notebook!

  • In Visual Studio Code, press Ctrl (Cmd on OS X) + Shift + P to open the "command palette". Start to type jupyter and then select Jupyter: Create New Blank Notebook.

  • In your notebook write print("Hello world") and press Shift + Enter.

  • Follow any instructions to install necessary libraries and modules. (NOTE: they may appear in the bottom-right area of your screen!)

  • You have a notebook successfully running if you see a check mark and Hello world printed out for you after the cell:

Successful execution of "Hello World" in a Jupyter Notebook within Visual Studio Code