iPython and Jupyter are important tools for data scientists like us. They let you experiment with code and play around with data extremely quickly - far faster than trying to write and run files. You can think of them as a much more powerful version of a command line or REPL, if you're familiar with that. It's also very similar to Mathematica.
Jupyter is an app that runs iPython, which is an interactive version of regular old Python. For the purposes of this tutorial, we'll say iPython because it's better-known than Jupyter. For most uses, the terms are interchangeable.
Python is one of the premier languages for data science and extremely useful for other tasks like web development.
We'll be using Python in this tutorial, so if you aren't familiar, use this tutorial!
If you're using a Mac, get Homebrew. Fire up your terminal (also known as a command line or command prompt) and run the following command to install iPython:
brew install python
Now, install pip:
sudo easy_install pip
Once you have Python, run:
python2 -m pip install --upgrade pip
python2 -m pip install jupyter
(From https://jupyter.org/install)
Don't use python for this on Macs - that's the crappy pre-installed version of Python that comes with macOS. Instead, use python2, which was installed by Homebrew.
Still have problems? Call us over.
To get your first taste of iPython, clone this repository onto your computer.
Then run:
jupyter notebook
In your terminal.
You'll see a web browser window open with a list of your files. Open up Bootcamp.ipynb and follow along.
- If you'll be installing packages, be sure you make a virtual environment first. Here's how to do that.
- We recommend installing a few other packages, which will probably come in hands. Run
pip2 install pandasandpip2 install numpyto get 2 useful packages.
