Cells in Jupyter Notebook

Jupyter Notebook is a little different than the IDE you might be used to coding in. It is a development environment. For example, you might have coded in Microsoft Visual Studio with C#. Jupyter has cells, or blocks of code that you execute one cell at a time. Cells appear a boxes. We can write our code in these cells and then we execute them and right below the cell, the result of our code is output. To the left of each cell you can see In and Out. This approach encourages a trial and error approach. By the way, the old deprecated name for a Jupyter Notebook is called an IPython notebook. So in case you see those two, just remember that they’re interchangeable.

One great thing about Jupyter Notebook is that you can add formatted text to create sections for documentation. Of course, you can also add comments, just like you can in other languages, like C#, but the ability to use “markdown’ in a notebook is a big advantage. You can even add graphics from the internet by adding links to those graphics. Jupyter can also show charts and graphs that your code generates. These charts and graphs are embedded right into the notebook.

Learn with YouTube

Here is a good YouTube video by Alex the Analyst called Installing Jupyter Notebooks/Anaconda | Python for Beginners. There are other IDEs that you can use, but Jupyter Notebooks is very popular. In the video, Alex starts with going to the website anaconda.com and installing Anaconda. It takes less than 4 GB of space on your hard drive. Once installed it will appear as Anaconda Navigator in your operating system. Run it. Click on the Launch button under Jupyter Notebooks. A new page in your browser should open up. The address will be a localhost address. Alex has a series of YouTube videos called Python for Beginners where the first video is the above mentioned video called Installing Jupyter Notebooks.

Here’s a YouTube video called Jupyter Notebook Complete Beginner Guide 2023 – From Jupyter to Jupyterlab, Google Colab and Kaggle! It’s by Rob Mulla. It’s about 25 minutes long and it was just released in the year 2023.

Learn with Udemy.com

You could take a course at Udemy.com. If you are interested in Data Analytics with Python and pandas, have a look at a course called Data Analysis with Pandas and Python by Boris Paskhaver. Of course, there are other good courses as well as this one.

Other Resources

Here is an external resource describing the Jupyter Notebook user interface components.

Another external resource Project Jupyter Documentation.

In Windows, where are your project files stored. By default they are in C:\Users\username, where the username is your name.

Jupyter 7

Here is some information.