Python for Data Analysis: Learn the Principles of Data Analysis and Raise Your Programming Iq. Improve Your Machine Learning Experience and Beco (Hardback or Cased Book)

Campbell, Robert

ISBN 10: 1803064420 / ISBN 13: 9781803064420

Edité par Robert Campbell 10/16/2022, 2022

A propos de cet article

Python for Data Analysis: Learn the Principles of Data Analysis and Raise Your Programming Iq. Improve Your Machine Learning Experience and Beco 0.89.

N° de réf. du vendeur BBS-9781803064420

Détails bibliographiques

• Titre: Python for Data Analysis: Learn the Principles of Data Analysis and Raise Your Programming Iq. Improve Your Machine Learning Experience and Beco (Hardback or Cased Book)
• Éditeur: Robert Campbell 10/16/2022
• Date de parution: 2022
• Langue: anglais
• ISBN à 10 chiffres: 1803064420
• ISBN à 13 chiffres: 9781803064420
• Reliure: Hardback or Cased Book
• État de l'article: New
• Type de livre: Book

A propos de ce titre

Synopsis

IF YOU REALLY WANT TO DISCOVER THE SECRETS BEHIND PYTHON DATA SCINCE, THEN KEEP READING...

Data analysis plays an important role in many aspects of life today. From the moment you wake up, you interact with data at different levels. A lot of important decisions are made based on data analytics. Companies need data to help them meet many of their goals. As the population of the world keeps growing, its customer base keeps expanding. In light of this, they must find ways of keeping their customers happy while at the same time meeting their business goals.

Given the nature of competition in the business world, it is not easy to keep customers happy. Competitors keep preying on each other's customers, and those who win have another challenge ahead - how to maintain the customers lest they slide back to their former business partners. This is one area where Data Analysis comes in handy.

This book covers:

• What is Data Analysis
• Python Crash Course
• Data Munging
• Why Data Preprocessing Is Important
• What is Data Wrangling?
• Inheritances to Clean Up the Code
• Reading and writing data
• The Different Types of Data We Can Work With
• The Importance of Data Visualization
• Indexing and selecting arrays
• Common Debugging Tools
• Neural Network and What to Use for?

And much more.

To understand their customers better, companies rely on data. They collect all manner of data at each point of interaction with their customers. Data are useful in several ways. The companies learn more about their customers, thereafter clustering them according to their specific needs. Through such segmentation, the company can attend to the customers' needs better and hope to keep them satisfied for longer.

But data analytics is not just about customers and the profit motive. It is also about governance. Governments are the biggest data consumers all over the world. They collect data about citizens, businesses, and every other entity that they interact with at any given point. This is important information because it helps in a lot of instances.

For planning purposes, governments need accurate data on their population so that funds can be allocated accordingly. Equitable distribution of resources is something that cannot be achieved without proper Data Analysis. Other than planning, there is also the security angle. To protect the country, the government must maintain different databases for different reasons. There are high profile individuals who must be accorded special security detail, top threats who must be monitored at all times, and so forth. To meet the security objective, the government has to obtain and maintain updated data on persons of interest at all times.

There is so much more to Data Analysis than the corporate and government decisions. As a programmer, you are venturing into an industry that is challenging and exciting at the same time. Data doesn't lie unless it is manipulated, in which case you need insane Data Analysis and handling skills. As a data analyst, you will come across many challenges and problems that need solutions that can only be handled through Data Analysis. The way you interact with data can make a big difference, bigger than you can imagine.

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