Python 3.7 Programming for Data Analysis: With Live Projects For Absolute Beginners

What’s New in Python 3.7
Python 3.7 is a general-purpose programming language. Python comes with a standard library that hosts a large number of useful libraries and modules that can be leveraged to solve various problems. Besides the standard library, thousands of third-party libraries are readily available on the Internet, encouraging open source and active development. The official repository for hosting third-party libraries and utilities for enhancing development in Python is the Python Package Index (PyPI). Access it at PyPI – the Python Package Index and check out the various packages. Currently, there are over 80,000 packages you can install and start using.

Python was designed keeping in mind the fact that simple and beautiful code is more elegant and easy to use rather than doing premature optimization and writing hard-to-interpret code. Python’s standard libraries are power-packed with a wide variety of capabilities and features ranging from low-level hardware interfacing to handling files and working with text data.
Table of Contents
1.What’s New in Python 3.7
2.Python 3.7 Syntax Concepts
3.Classes and Magic Methods
4.An Introduction to Data Analysis
5.The panda's Library
6.Generators in Python
7.Text Analysis Techniques using Python
8.Automating with Python
9.Maximizing Your Code’s Performance
10.Attribute Access, Properties, and Descriptors
11.Designing with Descriptors
12.Searching and Reading Local Files
13.Continuous Delivery
14.Interactive Debugger in Python
15.File Sharing in Python 3.7
16.Comprehensions in Python 3.7
17.Facade Pattern in Python 3.7
18.How to Write a Unit Test?
19.Using Microservices with Python 3.7
20.NumPy with Python 3.7
21.Implement Web-based Discussion Forum
22.Live Project in Finance Module
23.Pylint a Python package

How to Use This Book
Python, being a general and multipurpose programming language, can be used to build applications and systems for different domains and solve diverse real-world problems. This book is for Students, Teachers, data scientists, experts and professionals, and researchers in academia who want to understand the understanding of latest Python 3.7 programming and Data Analysis with live project.
Python and Data Analysis
The main argument of this book is to develop all the concepts of data analysis by treating them in terms of Python. The Python programming language is widely used in scientific circles because of its large number of libraries that provide a complete set of tools for analysis and data manipulation. Python can handle text data very well, and this has led to several popular libraries like nltk, gensim, and pattern for NLP, information retrieval, and text analytics. You can also apply standard machine learning algorithms to solve problems related to text analytics.

It is widely used in several other domains including artificial intelligence (AI), game development, robotics, Internet of Things (IoT), computer vision, media processing, and network and system monitoring, just to name a few. To read some of the widespread success stories achieved with Python in different diverse domains like arts, science, computer science, education, and others, enthusiastic programmers and researchers can check out Welcome to Python.org success/.
Python is generally utilized in the everyday activities of Google, NASA, New York Stock Exchange and our preferred video sharing site, YouTube. Not simply in the business top dogs, Python is widely utilized even in business, government and non-government associations as well.