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Название: Python Data Analytics: The Expert’s Guide to Real-World Solutions
Автор: Travis Booth
Издательство: Amazon Digital Services LLC
Год: 2019
Страниц: 176
Язык: английский
Формат: epub, pdf (conv)
Размер: 10.1 MB

Python Data Analytics at Your Fingertips.

Big data manipulation with Python is one of the hottest topics going around right now but it can be difficult to understand where to begin. If you already have some coding experience then finding a book that strikes the right balance between concepts and practical examples can be difficult.

Python Data Analytics is your ultimate resource to master data manipulation using Python's extensive libraries. Travis Booth, the author of Deep Learning with Python, Linux for Beginners and Python Coding will take you on a deep dive into the world of data analytics using Python from A to Z.

For most people, Python is currently one of the first programming languages they learn instead of the older languages like C. The dynamic shift in Python’s popularity comes down to its intuitiveness, simplicity, and the fact that it is a high-level programming language. A high-level language means that it is as close to normal human languages as possible. From your experience with Python syntax and functions over the years, this is one of the things you probably appreciate about Python. More importantly, there is a budding community of developers, data scientists, and other experts who are constantly working to improve the Python language, and assist one another where necessary.

One of the most important concepts in data analysis that is a big deal in Python is simplicity. Python is a simple language, and this is one of the factors that set it apart from the other languages. Clarity in the definition is a common phenomenon. Other developers who come across your work don’t need to struggle to understand it. This way, it is easier for them to implement it in whichever projects they are working on. Anyone reading your code should never have to struggle with comprehension.

As an expert data analyst, your mastery of Python libraries will be useful from time to time. NumPy, for example, will be useful when working with or implementing linear algebra, working with vectors, random variables, and matrices. With Matplotlib, you can create and visualize data in different ways, making it easier for anyone using the data to understand it in-depth. Pandas offer reliable, fast, and easy to understand data structures that help in data manipulation and computations.

Whether you've had exposure to Python programming previously or if you're searching for a resource that is focused on teaching Python data analysis for beginners, this is the book for you.

Here are some of the topics you will learn аbout:

Data manipulation basics- Procedures and tools
Python libraries for data analysis
Using NumPy for statistical analysis
Testing hypothesis using Python
Data mining and building models
Using SciPy to test hypotheses

and much more!

Join all the people who have integrated data analytics into their skill set. Learn one of the most sought after and relevant skills employers are looking for!

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