Data Wrangling with Python 3.x [Video]

Data Wrangling with Python 3.x [Video]

Jamshaid Sohail
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Learn the data life cycle—from acquisition to processing to analysis—in Python
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Video Details

ISBN 13 9781789956597
Course Length 3 hours 35 minutes

Table of Contents

Video Description

You might be working in an organization, or have your own business, where data is being generated continuously (structured or unstructured) and you are looking to develop your skillset so you can jump into the field of Data Science. This hands-on guide shows programmers how to process information.

In this course, you will gather data, prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, and more! This course will equip us with the tools and technologies, also we need to analyze the datasets using Python so that we can confidently jump into the field and enhance our skill set. The best part of this course is the takeaway code templates generated using the real-life dataset.

Towards the end of the course, we will build an intuitive understanding of all the aspects available in Python for Data Wrangling.

All codes and supporting files are placed on GitHub at this link: https://github.com/PacktPublishing/-Data-Wrangling-with-Python-3.x

Style and Approach

This hands-on course demonstrates concepts via slides, to make sure they're explained in simple ways. Throughout the course, we will be using datasets downloaded from the UCI Machine Learning Repository and various sources on the public web for conceptual practical intuition.

In every section, we will be looking into the theoretical concepts related to the section and then jump on practical examples using the number one IDE for Data Science i.e. Spyder IDE.

Each line of code will be explained in detail and the output will be instantly shown in the variable explorer of the IDE.

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What You Will Learn

  • Effectively pre-process data (structured or unstructured) before doing any analysis on the dataset. 
  • Retrieving data from different data sources (CSV, JSON, Excel, PDF) and parse them in Python to give them a meaningful shape.
  • Learn about the amazing data storage places in an industry which are being highly optimized.
  • Perform statistical analysis using in-built Python libraries.
  • Hacks, tips, and techniques that will be invaluable throughout your Data Science career.

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Table of Contents

Video Details

ISBN 139781789956597
Course Length3 hours 35 minutes
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