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Data Visualization Guide.

Data Visualization Guide.

          
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About the Book

INTRODUCTION.
Wondering how to deal with big data? Have you ever wondered how to use these datasets to identify hidden patterns and make informed decisions? Do you know where we get this information from? Wondering what to do with incomplete or incorrect records? If you answered yes to any of these questions, you've come to the right place.
Many companies gather information from a variety of sources. This information can be in many different formats and must be collected, processed, and refined to be interpreted. A variety of data recovery tools are available to get information from a variety of places. These tools also help with cleaning and handling techniques.
You can use this information to make smarter opinions and ameliorate your company's effectiveness and styles. Every company needs to find a way to interpret and dissect large data sets. To do this, you need to know the different libraries and functions used to enhance your dataset. Because numerous data professionals use Python as their primary programming language, we give a brief preface to numerous simple Python libraries and features.

Still, this book is for you, If you are a budding critic or just want to edge your generalities. All the basics to help you become a data critic or scientist.
In this book, you will:
*Learn what data mining is and how it can be used in different industries.
*Explore the different tools used for data mining.
*Learn what data analytics is and why it's important.
*Understand how to prepare data for analysis. data visualization.
And so on and so on!
So what are you waiting for? Get a copy of this book now.


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Product Details
  • ISBN-13: 9798378861880
  • Publisher: Amazon Digital Services LLC - Kdp
  • Publisher Imprint: Independently Published
  • Height: 229 mm
  • No of Pages: 28
  • Spine Width: 2 mm
  • Weight: 50 gr
  • ISBN-10: 8378861880
  • Publisher Date: 24 Feb 2023
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Sub Title: Comprehensive, Large-scale Guide to Data Extraction And visualization.
  • Width: 152 mm


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