Jupyter Notebook for Data Science: Collaborate, create interactive visualizations, and manipulate big data in the language of your choice.

Drazen Lucanin

$137.99

5 (1 Ratings)

Video Aug 2018 3hrs 11mins 1st Edition

Drazen Lucanin

$137.99

5 (1 Ratings)

Video Aug 2018 3hrs 11mins 1st Edition

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Key benefits

• Understand how to effectively utilize Jupyter Notebook for interactive data analysis in Python
• Get hands-on experience of using popular data science libraries, such as Pandas and matplotlib, to work with real datasets
• Special focus is placed on addressing typical challenges, such as web scraping, dealing with data that isn't perfectly structured, and missing data

Description

This video course will help you get familiar with Jupyter Notebook and all of its features to perform various data science tasks in Python. Jupyter Notebook is a powerful tool for interactive data exploration and visualization and has become the standard tool among data scientists. In the course, we will start from basic data analysis tasks in Jupyter Notebook and work our way up to learn some common scientific Python tools such as pandas, matplotlib, and plotly. We will work with real datasets, such as crime and traffic accidents in New York City, to explore common issues such as data scraping and cleaning. We will create insightful visualizations, showing time-stamped and spatial data. By the end of the course, you will feel confident about approaching a new dataset, cleaning it up, exploring it, and analyzing it in Jupyter Notebook to extract useful information in the form of interactive reports and information-dense data visualizations. All the code and supporting files for this course are available on GitHub at https://github.com/PacktPublishing/Jupyter-Notebook-for-Data-Science This course uses Jupyter 5.4.1, while not the latest version available, it provides relevant and informative content for data science enthusiasts.

Who is this book for?

This course is for developers with a basic understanding of Python and Jupyter Notebook. A basic understanding of math and statistics will come in handy.

What you will learn

Learn how to efficiently use Jupyter Notebook for data manipulation and visualisation
Perform interactive data analysis and visualisation using Jupyter Notebook on real data
Analyse time series data using Pandas
Create interactive widgets where non-technical users can also get involved in the data exploration using the notebooks you create
Scrape websites to build datasets and deal with common challenges like unstructured or missing data
Combine different datasets in a single graph to enable people to compare them visually and gain new insights
Analyse and visualise geographic datasets to create stunning information-rich maps

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