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Introduction to the Python Jupyter Notebook

The Jupyter Notebook

The Jupyter Notebook

The Jupyter Notebook is an open-source web-based application that you can use to create and share documents that contain live code, equations, visualisations, and text. It is widely used within the Python community as it allows an easy-to-follow visual and real-time implementation. It is particularly effective at sharing code. Let’s look at how it works

Anaconda allows to

  • Install/upgrade packages
  • Without Administrator privileges
  • Without breaking other projects

Please go to Anaconda Installers to download Anaconda.

As an example, follow the following steps

  • Start ‘Anaconda Navigator’
  • Click on ‘Environments’ tab
  • Check the packages in the ‘base (root)’ environment
  • Check that ‘seaborn’ is installed and current (version 0.9.0 or later)

Anaconda This image depicts the main Anaconda navigator, which allows choosing different options. For example, you can open a Python editor, the command prompt, as well as the configuration settings. These can be used to update all the components.

Creating a New Environment

  • The ‘base (root)’ Environment requires Administrator privileges
  • If you need to install/upgrade packages, you need to createyour own new Environment

As an exercise, create the following as depicted in the figure

  • Name: Visualisation
  • Packages: Python 3.6
  • Install the ‘seaborn’ package (and dependencies)

Anaconda anaconda. This image depicts some of the options provided by the Anaconda navigator

Jupyter Notebook

Jupyter Notebook is a browser-based, interactive Python IDE, especially suitable for

  • Prototyping
  • Creating documents with interactive code and illustrations
  • Developing standalone applications

Do the following steps (as per figure):

  • From the Home tab in your Visualisation Environment, install Jupyter Notebook (once)
  • Launch Jupyter Notebook in your preferred browser

Anaconda. This image depicts how to launch the Jupiter Notebook, which is a web-based Python IDE.

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Introduction to Python for Big Data Analytics

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