JUPYTER NOTEBOOK

Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. It is used for data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.

Getting Started

To get started with Jupyter Notebook, you can follow these steps:

• Download and install Anaconda from anaconda.com/products/individual.
• Launch Jupyter Notebook from the Anaconda Navigator or by running the jupyter notebook command in your terminal.
• Create a new notebook by clicking the New button in the upper-right corner and selecting Notebook: Python 3.
• Write code in the code cells and run it using the Run button or by pressing Shift + Enter .
• Save your notebook and share it with others by exporting it as an HTML or PDF file. To save as PDF file follow the steps explained here

Documentation

The Jupyter Notebook documentation is available online at jupyter-notebook.readthedocs. This documentation includes guides, tutorials, and reference material for learning how to use Jupyter Notebook effectively.

• Magic Commands for Jupyter Notebook

Extensions

Jupyter Notebook has a wide range of extensions that can be used to enhance its functionality. These extensions can be found on jupyter-contrib-nbextensions, which is the official extension repository for Jupyter Notebook.

Examples

• Pima Indians Diabetes Analysis
  • Diabetes.csv
  • Pima Indian Diabetes Analysis with MLs (kaggle.com)

Useful Links

• JupySQL which runs SQL in Jupyter/IPython via a %sql and %%sql magics.
  • Example Usage of JupySQL which explains JupySQL with an example.
• LinkedInDumper
  • LinkedInDumper is a Python3 script that dumps employee data from the LinkedIn social networking platform. The results contain firstname, lastname, position (title), location and a user’s profile link.