So, it’s advisable that you create a new folder to prevent Jupyter Notebook documents from cluttering the unintended folder. Remember that the folder you select before running the command line will automatically be your home directory once you run the application. To install Jupyter Notebook, run Command Prompt (Windows user) or Terminal window (macOS user). In this guide, we’ll be using the pip package installer, so if you haven’t installed it yet, you can visit the pip documentation for installation steps. If not, you can download the latest version from the Python website. Notably, we assume you’re using Python 3 and have already installed it on your computer. Given that you can set up the Jupyter Notebook in various ways, this article explores one of them. The Jupyter Notebook environment on this open-source application enables you to explain your code line-by-line, thus making it easy for anyone to understand your reasoning. Being an application meant to promote collaboration, it goes without saying that Jupyter Notebook should have tools that facilitate this very function and it does. You can then save the file and send it to anyone with whom you are collaborating.ĭocumenting code: As we detailed earlier, writing quality code entails making it easy to read and understand the context within which you created the code. However, Jupyter Notebooks also promote interactivity in that you can create code, execute it, view the results, and include text-based comments, all using your web browser. Python scraping offers a viable approach as well.Ĭode sharing: Jupyter Notebook is somewhat comparable to cloud services like Pastebin and GitHub, which facilitate code sharing. As we'll detail later, Jupyter Notebook comes in handy and even creates a complete independent ecosystem. Web scraping: Web scraping refers to the automated extraction of data from websites. There are two approaches to including multimedia on your notebooks, namely generating them using a module called IPython.display (this entails writing code) or including the multimedia as an HTML document. Multimedia support: As a web application, Jupyter Notebook supports multimedia. Notably, Jupyter Notebook is structured in such a way that it generates charts immediately below the code that created them. For this reason, you can use this application to generate charts and graphs from code using available modules such as Bokeh, Plotly, and Matplotlib. It's used for a number of operations, including:ĭata visualization: Jupyter Notebook was initially designed for use by data scientists, meaning the data analysis and interpretation is at the center of its operations. Jupyter Notebook was initially designed for use by data scientists What is Jupyter Notebook used for? Importantly, this article is essentially a tutorial on various aspects of the application, including using it for web scraping. This article discusses what Jupyter Notebook is, its uses, how to set it up on your computer, and whether it's ideal for beginners. Although by default, it deploys the IPython kernel that uses Python to execute code, it still supports over 100 programming languages (kernels), including Java, Python, R, MATLAB, SQL, Scala, Julia, and more. In the beginning, the Jupyter Notebook supported the three main computational engines or Jupyter languages, namely Julia, Python, and R, making the word “Jupyter” somewhat of an acronym. Jupyter Notebooks use a notebook kernel to execute the code contained in the environment. Simply put, it's an environment that facilitates literate programming. The notebook application allows you to write code, view it, and execute it within a single user interface, thus making it easy to make changes on the go and immediately see the outcome. Jupyter Notebook is an open-source web-based interactive computing environment with which you can create and send documents containing code, text, equations, graphs, and more.
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