From understanding modern documentation, to learning how to choose between competing projects, today a successful software professional needs to know allot more than merely how use a programming language. So when a student recently asked for additional practice exercises, we thought that we would define the projects using the type of documentation that professional software developers are most likely to encounter in-the-field.From creating a simple "Hex Dumper" and "Big Banner" tool, to creating and reporting on dictionaries loaded with data, the exercises in this book have been designed so as to provide a gentle, evolutionary, real-world educational experience. Designed for beginners, students enrolled in our other Python training opportunities will also enjoy these activities. Be it on-line or in-person, we should note that our Python training has been taught to thousands of new software developers. This book includes instructions on how every purchaser can receive a free coupon to the Author's on-line video training. For students who have never programmed before - or need a review of the basics, this book also contains instructions on how each and every reader can register to receive unlimited, lifetime access to a free copy of our on-line Video Training, "Python 1000."
Introduction to Python Programming for Business and Social Science Applications
Would you like to gather big datasets, analyze them, and visualize the results, all in one program? If this describes you, then Introduction to Python Programming for Business and Social Science Applications is the book for you. Authors Frederick Kaefer and Paul Kaefer walk you through each step of the Python package installation and analysis process, with frequent exercises throughout so you can immediately try out the functions you’ve learned. Written in straightforward language for those with no programming background, this book will teach you how to use Python for your research and data analysis. Instead of teaching you the principles and practices of programming as a whole, this application-oriented text focuses on only what you need to know to research and answer social science questions. The text features two types of examples, one set from the General Social Survey and one set from a large taxi trip dataset from a major metropolitan area, to help readers understand the possibilities of working with Python. Chapters on installing and working within a programming environment, basic skills, and necessary commands will get you up and running quickly, while chapters on programming logic, data input and output, and data frames help you establish the basic framework for conducting analyses. Further chapters on web scraping, statistical analysis, machine learning, and data visualization help you apply your skills to your research. More advanced information on developing graphical user interfaces (GUIs) help you create functional data products using Python to inform general users of data who don’t work within Python. First there was IBM® SPSS®, then there was R, and now there′s Python. Statistical software is getting more aggressive - let authors Frederick Kaefer and Paul Kaefer help you tame it with Introduction to Python Programming for Business and Social Science Applications.
Your Python code may run correctly, but you need it to run faster. Updated for Python 3, this expanded edition shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By exploring the fundamental theory behind design choices, High Performance Python helps you gain a deeper understanding of Python’s implementation. How do you take advantage of multicore architectures or clusters? Or build a system that scales up and down without losing reliability? Experienced Python programmers will learn concrete solutions to many issues, along with war stories from companies that use high-performance Python for social media analytics, productionized machine learning, and more. Get a better grasp of NumPy, Cython, and profilers Learn how Python abstracts the underlying computer architecture Use profiling to find bottlenecks in CPU time and memory usage Write efficient programs by choosing appropriate data structures Speed up matrix and vector computations Use tools to compile Python down to machine code Manage multiple I/O and computational operations concurrently Convert multiprocessing code to run on local or remote clusters Deploy code faster using tools like Docker
Learn how to develop your own applications to monitor or control instrumentation hardware. Whether you need to acquire data from a device or automate its functions, this practical book shows you how to use Python's rapid development capabilities to build interfaces that include everything from software to wiring. You get step-by-step instructions, clear examples, and hands-on tips for interfacing a PC to a variety of devices. Use the book's hardware survey to identify the interface type for your particular device, and then follow detailed examples to develop an interface with Python and C. Organized by interface type, data processing activities, and user interface implementations, this book is for anyone who works with instrumentation, robotics, data acquisition, or process control. Understand how to define the scope of an application and determine the algorithms necessary, and why it's important Learn how to use industry-standard interfaces such as RS-232, RS-485, and GPIB Create low-level extension modules in C to interface Python with a variety of hardware and test instruments Explore the console, curses, TkInter, and wxPython for graphical and text-based user interfaces Use open source software tools and libraries to reduce costs and avoid implementing functionality from scratch
Learn software engineering and coding best practices to write Python code right and error free. In this book you’ll see how to properly debug, organize, test, and maintain your code, all of which leads to better, more efficient coding. Software engineering is difficult. Programs of any substantial length are inherently prone to errors of all kinds. The development cycle is full of traps unknown to the apprentice developer. Yet, in Python textbooks little attention is paid to this aspect of getting your code to run. At most, there is a chapter on debugging or unit testing in your average basic Python book. However, the proportion of time spent on getting your code to run is much higher in the real world. Pro Python Best Practices aims to solve this problem. What You'll Learn Learn common debugging techniques that help you find and eliminate errors Gain techniques to detect bugs more easily discover best="" practices="" to="" prevent="" bugscarry="" out="" automated="" testing="" discover="" problems="" fasteruse="" maintain="" a="" project="" over="" long="" timeLearn techniques to keep your project under controlbr/uldivbWho This Book Is For/bbr/divdivbr/divdivExperienced Python coders from web development, big data, and more./divdivbr/divdivdiv/div
PREFACE This is the First Edition of a Simplified Course in computer science for Class XI and XII in your hands. Since the CBSE syllabus for computer science has many changes, this edition is the outcome for the same. This book is aimed at providing a thorough base and understanding in various latest trends in Information Technology. This book covers Python 3.x, the world class professional programming language. Class, Inheritance, Overloading, Boolean algebra, SQL, Python with SQL and Concept of Network. The first edition of this book lays the foundation for further studies by covering the aspects in elaborative yet simple language. The book has been divided in five Units. Unit I - Beginners of Python (Chapter 1-4) discuss various major and important terms in programming of Python such as, Data types, Function (UDF and Built-in) and statement controls(if, while, for etc.). Unit II – Together with Python (Chapter 5 – 7) introduces different terms of Python like, Array and List, Tuple and it Method, and Dictionary and it Methods. Unit III – OOPs with Python (chapter 8 – 14) covers various terms such as Class, Inheritance, Overloading, Multithreading and Exception Handling in details. It also discussed how OOPs are implemented in Python. Unit IV – Data Structure (Chapter 15- 16) introduces various data structure, their purposes and functions along with their implementation in Python. It provides details information about Stack, Queue, and Boolean algebra. Unit V - Programming with SQL in Python (Chapter 17 – 22) covers various file handling method. Different file operation, Database management system terms, programming with SQL, implement SQL in Python for development of back end program. We have worked our best to keep the presentation of this book short, simple, and catchy. Our goal is that by the end of each chapter, you feel confident about the contents and enjoy yourself doing so. Any suggestion for improvement of this book is welcome.
Our 1000+ Software Engineering Questions and Answers focuses on all areas of Software Engineering subject covering 100+ topics in Software Engineering. These topics are chosen from a collection of most authoritative and best reference books on Software Engineering. One should spend 1 hour daily for 15 days to learn and assimilate Software Engineering comprehensively. This way of systematic learning will prepare anyone easily towards Software Engineering interviews, online tests, Examinations and Certifications. Highlights- Ø 1000+ Basic and Hard Core High level Multiple Choice Questions & Answers in Software Engineering with Explanations. Ø Prepare anyone easily towards Software Engineering interviews, online tests, Government Examinations and certifications. Ø Every MCQ set focuses on a specific topic in Software Engineering. Ø Specially designed for IBPS IT, SBI IT, RRB IT, GATE CSE, UGC NET CS, PROGRAMMER and other IT & Computer Science related Exams. Who should Practice these Software Engineering Questions? Ø Anyone wishing to sharpen their skills on Software Engineering. Ø Anyone preparing for aptitude test in Software Engineering. Ø Anyone preparing for interviews (campus/off-campus walk-in interviews) Ø Anyone preparing for entrance examinations and other competitive examinations. Ø All – Experienced, Freshers and Students.