If you want to learn how to program but dont know where to start, this is the right book and the right language for you. From the first page, our self-paced approach will help you build competence and confidence in your programming skills. And Python is the best language ever for learning how to program because of its simplicity and breadthtwo features that are hard to find in a single language. But this isnt just a book for beginners! Our self-paced approach also works for experienced programmers, helping you learn Python faster and better than youve ever learned a language before. By the time youre through, you will have mastered the key Python skills that are needed on the job, including those for object-oriented, database, and GUI programming. To make all of this possible, section 1 presents an 8-chapter course that will get anyone off to a great start with Python. Section 2 builds on that base by presenting the other essential skills that every Python programmer should have. Section 3 shows you how to develop object-oriented programs, a critical skillset in todays world. And section 4 shows you how to apply all of the skills that youve already learned as you build database and GUI programs for the real world.

Data is collected everywhere these days, in massive quantities. But data alone does not do you much good. That is why data analysis -- making sense of the data -- has become a must-have skill in the fields of business, science, and social science. But it is a tough skill to acquire. The concepts are challenging, and too many books and online tutorials treat only parts of the total skillset needed. Now, though, this book draws all the essential skills together and presents them in a clear and example-packed way. So you will soon be applying your programming skills to complex data analysis problems, more easily than you ever thought possible. In terms of content, this book gets you started the right way by using Pandas for data analysis and Seaborn for data visualisation, with JupyterLab as your IDE. Then, it helps you master descriptive analysis by teaching you how to get, clean, prepare, and analyse data, including time-series data. Next, it gets you started with predictive analysis by showing you how to use linear regression models to predict unknown and future values. And to tie everything together, it gives you 4 real-world case studies that show you how to apply your new skills to political, environmental, social, and sports analysis. At the end, you will have a solid set of the professional skills that can lead to all sorts of new career opportunities. Sound too good to be true? Download a sample chapter for free from the Murach website and see for yourself how this book can turn you into the data analyst that companies are looking for.

In the beginning, C++ was a hard language to learn because it required programmers to master low-level techniques to work with memory. Over the years, C++ has evolved to provide higher-level techniques that make it much easier to write effective code. But most C++ books havent evolved with the language. Until now. Now, this book uses modern C++ to get you off to a fast start, and then builds out your coding and OOP skills to the professional level. At that point, it also covers older techniques so youll be able to maintain the vast amount of legacy code thats out there, as well as work with embedded systems that dont support the newer techniques.

If you know how to program in Java, this is the first book you should buy for learning how to develop Android apps the way the pros do; it'll save you a lot of time and frustration.

PHP and MySQL are two of today's most popular, open-source tools for server-side programming. That means there's a continuing demand for web developers who know how to use PHP and MySQL at the professional level. And with this book, you can become one of them! In fact, in just the first 6 chapters, you will create a database-driven website that implements the MVC pattern, the way the best professionals do. Then, the rest of the book lets you build on that base to develop a full set of professional skills.

This practical, hands-on tutorial/reference/guide to MySQL is perfect for beginners, but it also works for experienced developers who are not getting the most from MySQL. As you would expect, this book shows how to code all of the essential SQL statements for creating and working with a MySQL database. But beyond that, this book also shows how to design a database, including how to use the graphical MySQL Workbench to create an EER model. It shows how to take advantage of relatively new MySQL features such as foreign keys, transactions, stored procedures, stored functions, triggers, and events. It even presents a starting set of skills for a database administrator (DBA), including how to secure and back up databases. And like all Murach books, it uses the distinctive "paired pages" format, which breaks the material into manageable skills to speed up both learning and reference. A great help for MySQL users at any level.

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples

This textbook grew out of notes for the ECE143 Programming for Data Analysis class that the author has been teaching at University of California, San Diego, which is a requirement for both graduate and undergraduate degrees in Machine Learning and Data Science. This book is ideal for readers with some Python programming experience. The book covers key language concepts that must be understood to program effectively, especially for data analysis applications. Certain low-level language features are discussed in detail, especially Python memory management and data structures. Using Python effectively means taking advantage of its vast ecosystem. The book discusses Python package management and how to use third-party modules as well as how to structure your own Python modules. The section on object-oriented programming explains features of the language that facilitate common programming patterns. After developing the key Python language features, the book moves on to third-party modules that are foundational for effective data analysis, starting with Numpy. The book develops key Numpy concepts and discusses internal Numpy array data structures and memory usage. Then, the author moves onto Pandas and details its many features for data processing and alignment. Because strong visualizations are important for communicating data analysis, key modules such as Matplotlib are developed in detail, along with web-based options such as Bokeh, Holoviews, Altair, and Plotly. The text is sprinkled with many tricks-of-the-trade that help avoid common pitfalls. The author explains the internal logic embodied in the Python language so that readers can get into the Python mindset and make better design choices in their codes, which is especially helpful for newcomers to both Python and data analysis. To get the most out of this book, open a Python interpreter and type along with the many code samples.

"Focusing on Python 3.6 and higher, this concise handbook focuses on the essential core of the language, with updated code examples to illuminate how Python works and how to structure programs that can be more easily explained, tested, and debugged. Throughout, Beazley reflects all he's learned teaching Python to scientists, engineers, and developers, and pushing the envelope of what makes Python tick."--Page 4 of cover.