Join Charles Kelly for an in-depth discussion in this video Introduction to Jupyter Notebook, part of NumPy Data Science Essential Training.
- [Instructor] Throughout this course, I'll be using Jupyter Interactive Notbooks to explain NumPy, SciPy, SymPy, and Python. What is a Jupyter Notebook? It's an application for creating and sharing documents that contain live code, equations, visualizations, and explanatory text. If you'd like more information, you can go to this website. There are several good tutorials that explain Jupyter Notebooks. You can find these at the Quick Start Guide, and this is at the IPython Jupyter site.
The User Documentation Guide, same site. User Documentation examples, again a different page at the same site, and a professor from Caltech did a good tutorial and you can find it here. There are at least two categories of Notebook users. The first are students and readers and viewers and learners. Within this role, people read a digital book or interact with a live notebook.
The other role is notebook developers. And these are people who create notebooks for students and readers and viewers. A Notebook contains Code cells and Markdown cells. Code cells are executing computer codes such as Python or many other languages. Markdown cells contain documentation or narrative cells. They guide a reader through a notebook. Each of these cells that you've seen so far are narrative or markdown cells.
In contrast, the following cells are live cells or code cells. For example, the first line says: "print (Hello Jupyter World!; You are helping me to learn." You can execute this code by going to the cell, that is clicking your mouse within the cell, and pressing the key combination shift enter. What's going on in the background is that when you launch a Jupyter Notebook, it starts a server.
In this case it's starting a Python server, so you can type any valid Python statement, and the background server will execute the statement. For example, this is an arithmetic expression, five plus seven equals 12 and if I divide by four the answer should be three. Again, I'm pressing the key code combination shift and enter. You can enter any sequence combination of valid Python statements.
For example, import NumPy as np, my first array is equal to numpys arange function with an argumentative of 11. And the final statement is "print {my_first_array}". Again, I'm pressing shift enter and the output of my first array is displayed.
Released
10/7/2016- Using Jupyter Notebook
- Creating NumPy arrays from Python structures
- Slicing arrays
- Using Boolean masking and broadcasting techniques
- Plotting in Jupyter notebooks
- Joining and splitting arrays
- Rearranging array elements
- Creating universal functions
- Finding patterns
- Building magic squares and magic cubes with NumPy and Python
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Video: Introduction to Jupyter Notebook