Python Data Analytics

Programming Languages Project

ISBN 10: 1704066530 / ISBN 13: 9781704066530

Verlag: Independently Published, 2019

Beschreibung

Bestandsnummer des Verkäufers LU-9781704066530

Bibliografische Details

• Titel: Python Data Analytics
• Verlag: Independently Published
• Erscheinungsjahr: 2019
• Sprache: Englisch
• ISBN-10: 1704066530
• ISBN-13: 9781704066530
• Einband: Paperback
• Zustand: New

Über diesen Titel

Inhaltsangabe

Have you been collecting data on your industry, your product, or your customers, and now you are not sure what do to with it?

Do you know that collecting this information is important and that there is likely to be some really valuable insights inside of that data, but you don’t even know where to begin with extracting that data?

Wouldn’t it be nice to have a  present model  that could go through all of the information, and provide you with the answers, predictions, and insights?

This is exactly what data analytics is going to be able to help you out with! This is an amazing process that is simple to do, though it takes some time and some serious dedication to complete. The good news is, once you are able to put all of the parts together and see what is hidden in this data, it can provide you with so many benefits. From providing better customer service to beating out the competition and making decisions that are backed by data, you can’t go wrong with adding data analytics into your business.

This guidebook is going to take some time to discuss what data analytics is all about, and why your business needs to have this process implemented into it as soon as possible. Some of the topics that we will discuss inside this guidebook to help put you on the fast track to seeing results with your data analysis include:

• What is a data analysis and why is it so important?
• Why do so many companies want to jump on board with everything a data analysis has to offer?
• A look at Big Data and where it fits in the picture
• What the Python coding language is all about, the benefits of using this coding language, and how it fits into the world of data science.
• Some of the best coding libraries that you can do to help with your own data analysis, including SciPy, NumPy, Pandas, and more!
• A few examples of coding that you can do to complete a data analysis
• Tips and tricks that can make your Python data analysis even better and more successful than before.

When you are ready to work with data analysis, and you want to use the Python coding language, with all of its great scientific and technical libraries to make it all happen, check out this guidebook and learn how to perform your very own Python Data Analytics today!