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Data Analysis and Visualization Using Python
Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Python, you will take a closer look at the Python environment and get acquainted with editors such as Jupyter Notebook and Spyder. After going through a primer on Python programming, you will grasp fundamental Python programming techniques used in data science. Moving on to data visualization, you will see how it caters to modern business needs and forms a key factor in decision-making. You will also take a look at some popular data visualization libraries in Python. Shifting focus to data structu...
Python for Data Analysis
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 IPyt...
Python Data Analytics
Python Data Analytics will help you tackle the world of data acquisition and analysis using the power of the Python language. At the heart of this book lies the coverage of pandas, an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. Author Fabio Nelli expertly shows the strength of the Python programming language when applied to processing, managing and retrieving information. Inside, you will see how intuitive and flexible it is to discover and communicate meaningful patterns of data using Python scripts, reporting systems, and data export. This book examines how to go about obtaining, proc...
Learn Data Analysis with Python
Get started using Python in data analysis with this compact practical guide. This book includes three exercises and a case study on getting data in and out of Python code in the right format. Learn Data Analysis with Python also helps you discover meaning in the data using analysis and shows you how to visualize it. Each lesson is, as much as possible, self-contained to allow you to dip in and out of the examples as your needs dictate. If you are already using Python for data analysis, you will find a number of things that you wish you knew how to do in Python. You can then take these techniques and apply them directly to your own projects. If you aren’t using Python for data analysis, thi...
Introduction to Data Science
This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.
Industry 4.0 Key Technological Advances and Design Principles in Engineering, Education, Business, and Social Applications
This book offers an in-depth look at Industry 4.0’s applications and provides a conceptual framework for design principles and easy implementation. The book touches on the impact of Industry 4.0 and also examines the key technological advances and potential economic and technical benefits through case studies featuring real-world implementations. Industry 4.0 Key Technological Advances and Design Principles in Engineering, Education, Business, and Social Applications discusses the impact of Industry 4.0 and workforce transformation. The book examines the key technological advances that support Industry 4.0 and examines their potential economic and technical benefits through case studies. I...
Major Companies of the Arab World 1993/94
This book represents the seventeenth edition of the leading IMPORTANT reference work MAJOR COMPANIES OF THE ARAB WORLD. All company entries have been entered in MAJOR COMPANIES OF THE ARAB WORLD absolutely free of ThiS volume has been completely updated compared to last charge, thus ensuring a totally objective approach to the year's edition. Many new companies have also been included information given. this year. Whilst the publishers have made every effort to ensure that the information in this book was correct at the time of press, no The publishers remain confident that MAJOR COMPANIES responsibility or liability can be accepted for any errors or OF THE ARAB WORLD contains more informati...
Python Scripting for ArcGIS
"Python Scripting for ArcGIS is a guide to help experienced users of ArcGIS for Desktop get started with Python scripting. This book teaches how to write Python code that works with spatial data to automate geoprocessing tasks in ArcGIS. Readers can thuslearn the skill set needed to create custom tools. Key topics in this book include Python language fundamentals, automating geoprocessing tasks,exploring and manipulating spatial data, working with geometries and rasters, map scripting, debugging and error handling, creating functions and classes, and creating and sharing script tools"--
Python Data Analytics
Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn. This revision is fully updated with new content on social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation Author Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapter...
