What is a Jupyter Notebook?
Jupyter Notebook (formerly IPython Notebooks) is a web-based interactive computational environment.
By default Jupyter Notebook ships with the IPython kernel.
Wait... What is a Kernel?
A 'kernel' is a program that runs and introspects the user's code. IPython includes a kernel for Python code.
Jupyter Notebook can connect to many kernels to allow programming in many languages.
Project Jupyter's name is a reference to the three core programming languages supported by Jupyter, which are Julia, Python and R, and also an homage to Galileo's notebooks recording the discovery of the moons of Jupiter.
Why do Data Scientists use the Jupyter Notebook?
Jupyter Notebook is a super-powerful tool for Data Scientists as it allows them to interactively write code, document their code with comments, perform data visualizations on the go and produce a reusable document - called a notebook that can be easily shared with others.
And because Jupyter Notebook runs via a web browser, the notebook itself could be hosted on a local machine or on a remote server.
How can I get started with Jupyter Notebook?
Like already mentioned, since the Jupyter Notebook can be installed on a remote server, it has become a popular user interface for cloud computing, and major cloud providers have adopted the Jupyter Notebook or derivative tools as a frontend interface for cloud users.
Project Jupyter itself allows you to try Jupyter out right away without installing anything.
Just select your language of choice and you will get a temporary Jupyter server just for you.
So let's get started with using Python on Jupyter Notebook:
Step 1: Visit https://jupyter.org/try
Step 2: Click on Try Jupyter with Python
Step 3: Wait till the temporary server is set up.
You will be redirected to a pre-populated Notebook called Index.ipynb.
Step 4: Go to File -> New Notebook -> Python 3 and Create a New Python 3 Notebook
Step 5: Copy and paste the code snippet below into the first cell of the Untitled notebook
import pandas as pd wine_csv_url = 'https://docs.google.com/spreadsheets/d/e/2PACX-1vRXEsWuHw6pj3zWvWJKSqva2PSsaIEVQVXgILSFxQpcQaPejmwKk3AM0bEXNIyEPyCMV7kFPSIc6chm/pub?gid=0&single=true&output=csv' wine_data = pd.read_csv(wine_csv_url) wine_data.head()
The New Python 3 Untitled Notebook
Step 6: Run the code by clicking on the Play button and wait for the output to get printed right inside your notebook.
Yes, it's that simple!
I would recommend this way of using the Jupyter Notebook with Python for learners who are very new to the Data Science field and don't want to get bogged down with details of the installation stuff and setting up the Python environment on their local machines.
This way, you'll be able try out the basics of Python programming using just a web browser and get started quickly with the fundamentals of Data Science.
Hope this post helped you achieve that goal.
In later posts, I'll write about how you can install and run Jupyter on your local machine and have your .ipynb files saved permanently so that they can be reused.