Packt - Data Wrangling with Python 3.x

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Packt - Data Wrangling with Python 3.x
English | Size: 1.17 GB
Category: Programming

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.

Packt - Data Wrangling with Python 3.x
English | Size: 1.17 GB
Category: Programming

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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