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Data Analysis with Polars
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Data Analysis with Polars
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Feb 2025
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Get up and running with Polars to perform effective data analysis with Rust
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Data Analysis with Polars
Get up and running with Polars to perform effective data analysis with Rust
Description
Discover the power of Polars, the lightning-fast DataFrame library, for fast data manipulation and analysis. This comprehensive guide provides you with in-depth insights into Polars: its interface, how Polars works behind the scenes, and how to use it in practical applications. You'll start with the fundamentals of Polars, such as reading and writing files and databases, and transforming data. Next, you’ll progress to advanced topics such as window functions, time-series analysis, text transformations, processing larger-than-memory datasets, and testing data pipelines. You'll also learn how to leverage SQL with Polars. The second section of the book guides you through five case studies step by step, allowing you to apply your learning to business problems. Through the real-life case studies, you'll find out how to perform financial and marketing analyses, such as price-volume-mix analysis, market basket analysis, customer segmentation, product recommendations, and text analysis. By the end of this book, you'll have gained the knowledge and skills you need to advance your Python data analysis skills using Polars and take your career to the next level.
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Feb 2025
AI Assistant AI Assistant Coming Soon Coming Soon
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Author Luca Zanna
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Guerrilla Data Analysis Using Microsoft Excel
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Guerrilla Data Analysis Using Microsoft Excel
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Sep 2024
EBook 277 pages
Overcoming Crap Data and Excel Skirmishes
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Guerrilla Data Analysis Using Microsoft Excel
Overcoming Crap Data and Excel Skirmishes
Description
Unlock Microsoft Excel's hidden potential with this dynamic guide designed for data professionals and enthusiasts. You'll start by reviewing Excel basics before advancing to powerful tools like Excel Tables, Pivot Tables, and Power Query. Each chapter enhances your ability to analyze and visualize data efficiently, from complex lookups and dynamic arrays to essential data validation techniques that ensure accuracy and integrity in your spreadsheets. As you progress, you'll learn how to protect your work with advanced sheet protection methods and collaboration tools for seamless teamwork. The book also covers sophisticated functions like INDIRECT, OFFSET, and LET, preparing you to tackle complex data challenges. Additionally, you'll receive critical advice on avoiding the pitfalls of machine learning-driven features and maintaining clean, organized data. By the end of the guide, you'll have mastered Excel's advanced capabilities, empowering you to streamline workflows, optimize data processes, and make confident, data-driven decisions. This guide is your comprehensive resource for transforming your approach to data analysis with Excel.
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Sep 2024 277 pages
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Author MrExcel's Holy Macro! Books
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Exploratory Data Analysis with Python Cookbook
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Exploratory Data Analysis with Python Cookbook
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Jun 2023
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8 (5)
Paperback 382 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8 (5)
Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data
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  • 9781803246130 eBook €20.98
  • 9781803231105 Paperback €37.99
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Exploratory Data Analysis with Python Cookbook
Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data
Description
In today's data-centric world, the ability to extract meaningful insights from vast amounts of data has become a valuable skill across industries. Exploratory Data Analysis (EDA) lies at the heart of this process, enabling us to comprehend, visualize, and derive valuable insights from various forms of data. This book is a comprehensive guide to Exploratory Data Analysis using the Python programming language. It provides practical steps needed to effectively explore, analyze, and visualize structured and unstructured data. It offers hands-on guidance and code for concepts such as generating summary statistics, analyzing single and multiple variables, visualizing data, analyzing text data, handling outliers, handling missing values and automating the EDA process. It is suited for data scientists, data analysts, researchers or curious learners looking to gain essential knowledge and practical steps for analyzing vast amounts of data to uncover insights. Python is an open-source general purpose programming language which is used widely for data science and data analysis given its simplicity and versatility. It offers several libraries which can be used to clean, analyze, and visualize data. In this book, we will explore popular Python libraries such as Pandas, Matplotlib, and Seaborn and provide workable code for analyzing data in Python using these libraries. By the end of this book, you will have gained comprehensive knowledge about EDA and mastered the powerful set of EDA techniques and tools required for analyzing both structured and unstructured data to derive valuable insights.
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Jun 2023 382 pages
AI Assistant AI Assistant
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Author Ayodele Oluleye
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Hands-On Data Analysis with Pandas
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Hands-On Data Analysis with Pandas
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Apr 2021
Full star icon Full star icon Full star icon Full star icon Half star icon 4.6 (14)
Paperback 788 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.6 (14)
A Python data science handbook for data collection, wrangling, analysis, and visualization
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  • 9781800565913 eBook €26.99
  • 9781800563452 Paperback €48.99
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Hands-On Data Analysis with Pandas
A Python data science handbook for data collection, wrangling, analysis, and visualization
Description
Extracting valuable business insights is no longer a ‘nice-to-have’, but an essential skill for anyone who handles data in their enterprise. Hands-On Data Analysis with Pandas is here to help beginners and those who are migrating their skills into data science get up to speed in no time. This book will show you how to analyze your data, get started with machine learning, and work effectively with the Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. This updated edition will equip you with the skills you need to use pandas 1.x to efficiently perform various data manipulation tasks, reliably reproduce analyses, and visualize your data for effective decision making – valuable knowledge that can be applied across multiple domains.
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Apr 2021 788 pages
AI Assistant AI Assistant
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Author Stefanie Molin
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Data Analysis Foundations with Python
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Jun 2024
EBook 551 pages
Master Data Analysis with Python: From Basics to Advanced Techniques
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Data Analysis Foundations with Python
Master Data Analysis with Python: From Basics to Advanced Techniques
Description
Embark on a comprehensive journey through data analysis with Python. Begin with an introduction to data analysis and Python, setting a strong foundation before delving into Python programming basics. Learn to set up your data analysis environment, ensuring you have the necessary tools and libraries at your fingertips. As you progress, gain proficiency in NumPy for numerical operations and Pandas for data manipulation, mastering the skills to handle and transform data efficiently. Proceed to data visualization with Matplotlib and Seaborn, where you'll create insightful visualizations to uncover patterns and trends. Understand the core principles of exploratory data analysis (EDA) and data preprocessing, preparing your data for robust analysis. Explore probability theory and hypothesis testing to make data-driven conclusions and get introduced to the fundamentals of machine learning. Delve into supervised and unsupervised learning techniques, laying the groundwork for predictive modeling. To solidify your knowledge, engage with two practical case studies: sales data analysis and social media sentiment analysis. These real-world applications will demonstrate best practices and provide valuable tips for your data analysis projects.
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Jun 2024 551 pages
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Author Cuantum Technologies LLC
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Data Analysis with R, Second Edition
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Data Analysis with R, Second Edition
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Mar 2018
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.5 (2)
Paperback 570 pages
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.5 (2)
A comprehensive guide to manipulating, analyzing, and visualizing data in R
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  • 9781788397339 eBook €17.99
  • 9781788393720 Paperback €32.99
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Data Analysis with R, Second Edition
A comprehensive guide to manipulating, analyzing, and visualizing data in R
Description
Frequently the tool of choice for academics, R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. Starting with the basics of R and statistical reasoning, this book dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples. Packed with engaging problems and exercises, this book begins with a review of R and its syntax with packages like Rcpp, ggplot2, and dplyr. From there, get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. Solve the difficulties relating to performing data analysis in practice and find solutions to working with messy data, large data, communicating results, and facilitating reproducibility. This book is engineered to be an invaluable resource through many stages of anyone’s career as a data analyst.
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Mar 2018 570 pages
AI Assistant AI Assistant
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Python Data Analysis
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Python Data Analysis
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Feb 2021
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5 (13)
Paperback 478 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5 (13)
Perform data collection, data processing, wrangling, visualization, and model building using Python
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  • 9781789953459 eBook €15.99
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Python Data Analysis
Perform data collection, data processing, wrangling, visualization, and model building using Python
Description
Data analysis enables you to generate value from small and big data by discovering new patterns and trends, and Python is one of the most popular tools for analyzing a wide variety of data. With this book, you’ll get up and running using Python for data analysis by exploring the different phases and methodologies used in data analysis and learning how to use modern libraries from the Python ecosystem to create efficient data pipelines. Starting with the essential statistical and data analysis fundamentals using Python, you’ll perform complex data analysis and modeling, data manipulation, data cleaning, and data visualization using easy-to-follow examples. You’ll then understand how to conduct time series analysis and signal processing using ARMA models. As you advance, you’ll get to grips with smart processing and data analytics using machine learning algorithms such as regression, classification, Principal Component Analysis (PCA), and clustering. In the concluding chapters, you’ll work on real-world examples to analyze textual and image data using natural language processing (NLP) and image analytics techniques, respectively. Finally, the book will demonstrate parallel computing using Dask. By the end of this data analysis book, you’ll be equipped with the skills you need to prepare data for analysis and create meaningful data visualizations for forecasting values from data.
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Feb 2021 478 pages
AI Assistant AI Assistant
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Author Navlani
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eBook €15.99 €23.99
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Practical Data Analysis Using Jupyter Notebook
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Practical Data Analysis Using Jupyter Notebook
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Jun 2020
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.9 (9)
Paperback 322 pages
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.9 (9)
Learn how to speak the language of data by extracting useful and actionable insights using Python
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  • 9781838825096 eBook €15.99
  • 9781838826031 Paperback €29.99
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Practical Data Analysis Using Jupyter Notebook
Learn how to speak the language of data by extracting useful and actionable insights using Python
Description
Data literacy is the ability to read, analyze, work with, and argue using data. Data analysis is the process of cleaning and modeling your data to discover useful information. This book combines these two concepts by sharing proven techniques and hands-on examples so that you can learn how to communicate effectively using data. After introducing you to the basics of data analysis using Jupyter Notebook and Python, the book will take you through the fundamentals of data. Packed with practical examples, this guide will teach you how to clean, wrangle, analyze, and visualize data to gain useful insights, and you'll discover how to answer questions using data with easy-to-follow steps. Later chapters teach you about storytelling with data using charts, such as histograms and scatter plots. As you advance, you'll understand how to work with unstructured data using natural language processing (NLP) techniques to perform sentiment analysis. All the knowledge you gain will help you discover key patterns and trends in data using real-world examples. In addition to this, you will learn how to handle data of varying complexity to perform efficient data analysis using modern Python libraries. By the end of this book, you'll have gained the practical skills you need to analyze data with confidence.
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Jun 2020 322 pages
AI Assistant AI Assistant
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Authors
Author Marc Wintjen
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Kibana 8.x – A Quick Start Guide to Data Analysis
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Kibana 8.x – A Quick Start Guide to Data Analysis
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Feb 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (3)
Paperback 198 pages
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (3)
Learn about data exploration, visualization, and dashboard building with Kibana
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  • 9781803244051 eBook €13.99
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Kibana 8.x – A Quick Start Guide to Data Analysis
Learn about data exploration, visualization, and dashboard building with Kibana
Description
Unleash the full potential of Kibana—an indispensable tool for data analysts to seamlessly explore vast datasets, uncover key insights, identify trends and anomalies, and share results. This book guides you through its user-friendly interface, interactive visualizations, and robust features, including real-time data monitoring and advanced analytics, showing you how Kibana revolutionizes your approach to navigating and analyzing complex datasets. Starting with the foundational steps of installing, configuring, and running Kibana, this book progresses systematically to explain the search and data visualization capabilities for data stored in the Elasticsearch cluster. You’ll then delve into the practical details of creating data views and optimizing spaces to better organize the analysis environment. As you advance, you'll get to grips with using the discover interface and learn how to build different types of extensive visualizations using Lens. By the end of this book, you’ll have a complete understanding of how Kibana works, helping you leverage its capabilities to build an analytics and visualization solution from scratch for your data-driven use case.
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Feb 2024 198 pages
AI Assistant AI Assistant
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Author Shah
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Hands-On Exploratory Data Analysis with Python
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Hands-On Exploratory Data Analysis with Python
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Mar 2020
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.5 (2)
Paperback 352 pages
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.5 (2)
Perform EDA techniques to understand, summarize, and investigate your data
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  • 9781789535624 eBook €32.99
  • 9781789537253 Paperback €59.99
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Hands-On Exploratory Data Analysis with Python
Perform EDA techniques to understand, summarize, and investigate your data
Description
Exploratory Data Analysis (EDA) is an approach to data analysis that involves the application of diverse techniques to gain insights into a dataset. This book will help you gain practical knowledge of the main pillars of EDA - data cleaning, data preparation, data exploration, and data visualization. You’ll start by performing EDA using open source datasets and perform simple to advanced analyses to turn data into meaningful insights. You’ll then learn various descriptive statistical techniques to describe the basic characteristics of data and progress to performing EDA on time-series data. As you advance, you’ll learn how to implement EDA techniques for model development and evaluation and build predictive models to visualize results. Using Python for data analysis, you’ll work with real-world datasets, understand data, summarize its characteristics, and visualize it for business intelligence. By the end of this EDA book, you’ll have developed the skills required to carry out a preliminary investigation on any dataset, yield insights into data, present your results with visual aids, and build a model that correctly predicts future outcomes.
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Mar 2020 352 pages
AI Assistant AI Assistant
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Author Kumar Mukhiya
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Mastering Data analysis with R
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Mastering Data analysis with R
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Sep 2015
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5 (2)
Paperback 396 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5 (2)
Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization
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  • 9781783982035 eBook €24.99
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Mastering Data analysis with R
Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization
Description
Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization About This Book Handle your data with precision and care for optimal business intelligence Restructure and transform your data to inform decision-making Packed with practical advice and tips to help you get to grips with data mining Who This Book Is For If you are a data scientist or R developer who wants to explore and optimize your use of R’s advanced features and tools, this is the book for you. A basic knowledge of R is required, along with an understanding of database logic. What You Will Learn Connect to and load data from R’s range of powerful databases Successfully fetch and parse structured and unstructured data Transform and restructure your data with efficient R packages Define and build complex statistical models with glm Develop and train machine learning algorithms Visualize social networks and graph data Deploy supervised and unsupervised classification algorithms Discover how to visualize spatial data with R In Detail R is an essential language for sharp and successful data analysis. Its numerous features and ease of use make it a powerful way of mining, managing, and interpreting large sets of data. In a world where understanding big data has become key, by mastering R you will be able to deal with your data effectively and efficiently. This book will give you the guidance you need to build and develop your knowledge and expertise. Bridging the gap between theory and practice, this book will help you to understand and use data for a competitive advantage. Beginning with taking you through essential data mining and management tasks such as munging, fetching, cleaning, and restructuring, the book then explores different model designs and the core components of effective analysis. You will then discover how to optimize your use of machine learning algorithms for classification and recommendation systems beside the traditional and more recent statistical methods. Style and approach Covering the essential tasks and skills within data science, Mastering Data Analysis provides you with solutions to the challenges of data science. Each section gives you a theoretical overview before demonstrating how to put the theory to work with real-world use cases and hands-on examples.
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Sep 2015 396 pages
AI Assistant AI Assistant
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Author Daróczi
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Hands-On Data Analysis with Pandas
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Hands-On Data Analysis with Pandas
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Jul 2019
Full star icon Full star icon Full star icon Full star icon Half star icon 4.7 (11)
Paperback 740 pages
Full star icon Full star icon Full star icon Full star icon Half star icon 4.7 (11)
Efficiently perform data collection, wrangling, analysis, and visualization using Python
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  • 9781789612806 eBook €20.98
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Hands-On Data Analysis with Pandas
Efficiently perform data collection, wrangling, analysis, and visualization using Python
Description
Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. By the end of this book, you will be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets.
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Jul 2019 740 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Author Stefanie Molin
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Data Analysis with Python
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Data Analysis with Python
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Dec 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1)
Paperback 490 pages
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1)
A Modern Approach
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  • 9781789958195 eBook €17.99
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Data Analysis with Python
A Modern Approach
Description
Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects. Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you’re likely to meet in today. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence.
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Dec 2018 490 pages
AI Assistant AI Assistant
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Author David Taieb
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Hands-On Exploratory Data Analysis with R
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Hands-On Exploratory Data Analysis with R
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May 2019
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.3 (3)
Paperback 266 pages
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.3 (3)
Become an expert in exploratory data analysis using R packages
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  • 9781789802085 eBook €13.98
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Hands-On Exploratory Data Analysis with R
Become an expert in exploratory data analysis using R packages
Description
Hands-On Exploratory Data Analysis with R will help you build a strong foundation in data analysis and get well-versed with elementary ways to analyze data. You will learn how to understand your data and summarize its characteristics. You'll also study the structure of your data, and you'll explore graphical and numerical techniques using the R language. This book covers the entire exploratory data analysis (EDA) process—data collection, generating statistics, distribution, and invalidating the hypothesis. As you progress through the book, you will set up a data analysis environment with tools such as ggplot2, knitr, and R Markdown, using DOE Scatter Plot and SML2010 for multifactor, optimization, and regression data problems. By the end of this book, you will be able to successfully carry out a preliminary investigation on any dataset, uncover hidden insights, and present your results in a business context.
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May 2019 266 pages
AI Assistant AI Assistant
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Author Radhika Datar
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Hands-On SAS for Data Analysis
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Sep 2019
Paperback 346 pages
A practical guide to performing effective queries, data visualization, and reporting techniques
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Hands-On SAS for Data Analysis
A practical guide to performing effective queries, data visualization, and reporting techniques
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SAS is one of the leading enterprise tools in the world today when it comes to data management and analysis. It enables the fast and easy processing of data and helps you gain valuable business insights for effective decision-making. This book will serve as a comprehensive guide that will prepare you for the SAS certification exam. After a quick overview of the SAS architecture and components, the book will take you through the different approaches to importing and reading data from different sources using SAS. You will then cover SAS Base and 4GL, understanding data management and analysis, along with exploring SAS functions for data manipulation and transformation. Next, you'll discover SQL procedures and get up to speed on creating and validating queries. In the concluding chapters, you'll learn all about data visualization, right from creating bar charts and sample geographic maps through to assigning patterns and formats. In addition to this, the book will focus on macro programming and its advanced aspects. By the end of this book, you will be well versed in SAS programming and have the skills you need to easily handle and manage your data-related problems in SAS.
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Sep 2019 346 pages
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Author Gulati
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Getting Started with Haskell Data Analysis
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Oct 2018
Paperback 160 pages
Put your data analysis techniques to work and generate publication-ready visualizations
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Getting Started with Haskell Data Analysis
Put your data analysis techniques to work and generate publication-ready visualizations
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Every business and organization that collects data is capable of tapping into its own data to gain insights how to improve. Haskell is a purely functional and lazy programming language, well-suited to handling large data analysis problems. This book will take you through the more difficult problems of data analysis in a hands-on manner. This book will help you get up-to-speed with the basics of data analysis and approaches in the Haskell language. You'll learn about statistical computing, file formats (CSV and SQLite3), descriptive statistics, charts, and progress to more advanced concepts such as understanding the importance of normal distribution. While mathematics is a big part of data analysis, we've tried to keep this course simple and approachable so that you can apply what you learn to the real world. By the end of this book, you will have a thorough understanding of data analysis, and the different ways of analyzing data. You will have a mastery of all the tools and techniques in Haskell for effective data analysis.
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Oct 2018 160 pages
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Author Church
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Master SQL for Data Analysis
Master SQL for Data Analysis
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Jan 2023
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Let's learn SQL from A to Z and implement it in our data analysis projects
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Master SQL for Data Analysis
Let's learn SQL from A to Z and implement it in our data analysis projects
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SQL is a popular language for extracting, stacking, and querying data from databases. Master SQL to explore, filter, and aggregate almost any raw data into multiple dimensions of valuable input. Level 1 teaches SQL from scratch to let you understand SQL and data analysis and is designed to jumpstart your knowledge of SQL and perform various data analysis tasks. You will learn SQL terminologies, databases, and syntax. You will create and load databases, schemas and tables, analyze data using filtering conditions and search patterns, count distinct values across dataset attributes, group rows, calculate using aggregation functions, and use aliases for columns and tables. Level 2 directly continues from topics explored in Level 1. It covers more advanced SQL tools and capabilities. You will combine data from multiple sources, break complex queries into subqueries, transform and classify data, analyze data with window functions, create views and CTEs, and explore SQL to the core. You will work on quizzes and exercises to practice and sharpen your understanding of the learning objectives. Upon completion, you will comprehensively acquire knowledge about SQL syntax, queries and subqueries, perform data analysis tasks independently, and garner thorough understanding of SQL, and use it in your data visualization and analysis. All resources are available at: https://github.com/PacktPublishing/Master-SQL-for-Data-Analysis
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Published : Jan 2023
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Python Data Analysis
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Python Data Analysis
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Oct 2014
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Paperback 348 pages
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Learn how to apply powerful data analysis techniques with popular open source Python modules
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Python Data Analysis
Learn how to apply powerful data analysis techniques with popular open source Python modules
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This book is for programmers, scientists, and engineers who have knowledge of the Python language and know the basics of data science. It is for those who wish to learn different data analysis methods using Python and its libraries. This book contains all the basic ingredients you need to become an expert data analyst.
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Oct 2014 348 pages
AI Assistant AI Assistant
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Author Idris
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Practical Data Analysis
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Sep 2016
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Paperback 338 pages
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Pandas, MongoDB, Apache Spark, and more
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Practical Data Analysis
Pandas, MongoDB, Apache Spark, and more
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Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you’ll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark.
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Sep 2016 338 pages
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Author Dr. Sampath Kumar
Author Cuesta
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Python Data Analysis, Second Edition
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Python Data Analysis, Second Edition
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Mar 2017
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Paperback 330 pages
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Data manipulation and complex data analysis with Python
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Python Data Analysis, Second Edition
Data manipulation and complex data analysis with Python
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Data analysis techniques generate useful insights from small and large volumes of data. Python, with its strong set of libraries, has become a popular platform to conduct various data analysis and predictive modeling tasks. With this book, you will learn how to process and manipulate data with Python for complex analysis and modeling. We learn data manipulations such as aggregating, concatenating, appending, cleaning, and handling missing values, with NumPy and Pandas. The book covers how to store and retrieve data from various data sources such as SQL and NoSQL, CSV fies, and HDF5. We learn how to visualize data using visualization libraries, along with advanced topics such as signal processing, time series, textual data analysis, machine learning, and social media analysis. The book covers a plethora of Python modules, such as matplotlib, statsmodels, scikit-learn, and NLTK. It also covers using Python with external environments such as R, Fortran, C/C++, and Boost libraries.
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Mar 2017 330 pages
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Java Data Analysis
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Java Data Analysis
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Sep 2017
Paperback 412 pages
Data mining, big data analysis, NoSQL, and data visualization
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Java Data Analysis
Data mining, big data analysis, NoSQL, and data visualization
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Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the aim of discovering useful information. Java is one of the most popular languages to perform your data analysis tasks. This book will help you learn the tools and techniques in Java to conduct data analysis without any hassle. After getting a quick overview of what data science is and the steps involved in the process, you’ll learn the statistical data analysis techniques and implement them using the popular Java APIs and libraries. Through practical examples, you will also learn the machine learning concepts such as classification and regression. In the process, you’ll familiarize yourself with tools such as Rapidminer and WEKA and see how these Java-based tools can be used effectively for analysis. You will also learn how to analyze text and other types of multimedia. Learn to work with relational, NoSQL, and time-series data. This book will also show you how you can utilize different Java-based libraries to create insightful and easy to understand plots and graphs. By the end of this book, you will have a solid understanding of the various data analysis techniques, and how to implement them using Java.
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Sep 2017 412 pages
AI Assistant AI Assistant
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Author John R. Hubbard
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The Data Analysis Workshop
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Jul 2020
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Paperback 626 pages
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Solve business problems with state-of-the-art data analysis models, developing expert data analysis skills along the way
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The Data Analysis Workshop
Solve business problems with state-of-the-art data analysis models, developing expert data analysis skills along the way
Description
Businesses today operate online and generate data almost continuously. While not all data in its raw form may seem useful, if processed and analyzed correctly, it can provide you with valuable hidden insights. The Data Analysis Workshop will help you learn how to discover these hidden patterns in your data, to analyze them, and leverage the results to help transform your business. The book begins by taking you through the use case of a bike rental shop. You'll be shown how to correlate data, plot histograms, and analyze temporal features. As you progress, you’ll learn how to plot data for a hydraulic system using the Seaborn and Matplotlib libraries, and explore a variety of use cases that show you how to join and merge databases, prepare data for analysis, and handle imbalanced data. By the end of the book, you'll have learned different data analysis techniques, including hypothesis testing, correlation, and null-value imputation, and will have become a confident data analyst.
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Jul 2020 626 pages
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Author Gururajan Govindan
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Practical Data Analysis
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Oct 2013
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Paperback 360 pages
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For small businesses, analyzing the information contained in their data using open source technology could be game-changing. All you need is some basic programming and mathematical skills to do just that.
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Practical Data Analysis
For small businesses, analyzing the information contained in their data using open source technology could be game-changing. All you need is some basic programming and mathematical skills to do just that.
Description
Plenty of small businesses face big amounts of data but lack the internal skills to support quantitative analysis. Understanding how to harness the power of data analysis using the latest open source technology can lead them to providing better customer service, the visualization of customer needs, or even the ability to obtain fresh insights about the performance of previous products. Practical Data Analysis is a book ideal for home and small business users who want to slice and dice the data they have on hand with minimum hassle.Practical Data Analysis is a hands-on guide to understanding the nature of your data and turn it into insight. It will introduce you to the use of machine learning techniques, social networks analytics, and econometrics to help your clients get insights about the pool of data they have at hand. Performing data preparation and processing over several kinds of data such as text, images, graphs, documents, and time series will also be covered.Practical Data Analysis presents a detailed exploration of the current work in data analysis through self-contained projects. First you will explore the basics of data preparation and transformation through OpenRefine. Then you will get started with exploratory data analysis using the D3js visualization framework. You will also be introduced to some of the machine learning techniques such as, classification, regression, and clusterization through practical projects such as spam classification, predicting gold prices, and finding clusters in your Facebook friends' network. You will learn how to solve problems in text classification, simulation, time series forecast, social media, and MapReduce through detailed projects. Finally you will work with large amounts of Twitter data using MapReduce to perform a sentiment analysis implemented in Python and MongoDB. Practical Data Analysis contains a combination of carefully selected algorithms and data scrubbing that enables you to turn your data into insight.
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Oct 2013 360 pages
AI Assistant AI Assistant
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Author Hector Cuesta
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Mastering Clojure Data Analysis
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Mastering Clojure Data Analysis
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May 2014
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Paperback 340 pages
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If you'd like to apply your Clojure skills to performing data analysis, this is the book for you. The example based approach aids fast learning and covers basic to advanced topics. Get deeper into your data.
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Mastering Clojure Data Analysis
If you'd like to apply your Clojure skills to performing data analysis, this is the book for you. The example based approach aids fast learning and covers basic to advanced topics. Get deeper into your data.
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May 2014 340 pages
AI Assistant AI Assistant
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Author Eric Richard Rochester
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Haskell Data Analysis cookbook
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Jun 2014
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Paperback 334 pages
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Explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes
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Haskell Data Analysis cookbook
Explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes
Description
Step-by-step recipes filled with practical code samples and engaging examples demonstrate Haskell in practice, and then the concepts behind the code. This book shows functional developers and analysts how to leverage their existing knowledge of Haskell specifically for high-quality data analysis. A good understanding of data sets and functional programming is assumed.
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Jun 2014 334 pages
AI Assistant AI Assistant
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Author Nishant Shukla
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Mastering Python Data Analysis
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Mastering Python Data Analysis
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Jun 2016
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Paperback 284 pages
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Become an expert at using Python for advanced statistical analysis of data using real-world examples
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Mastering Python Data Analysis
Become an expert at using Python for advanced statistical analysis of data using real-world examples
Description
Python, a multi-paradigm programming language, has become the language of choice for data scientists for data analysis, visualization, and machine learning. Ever imagined how to become an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your data? Well, look no further, this is the book you want! Through this comprehensive guide, you will explore data and present results and conclusions from statistical analysis in a meaningful way. You’ll be able to quickly and accurately perform the hands-on sorting, reduction, and subsequent analysis, and fully appreciate how data analysis methods can support business decision-making. You’ll start off by learning about the tools available for data analysis in Python and will then explore the statistical models that are used to identify patterns in data. Gradually, you’ll move on to review statistical inference using Python, Pandas, and SciPy. After that, we’ll focus on performing regression using computational tools and you’ll get to understand the problem of identifying clusters in data in an algorithmic way. Finally, we delve into advanced techniques to quantify cause and effect using Bayesian methods and you’ll discover how to use Python’s tools for supervised machine learning.
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Jun 2016 284 pages
AI Assistant AI Assistant
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Clojure Data Analysis Cookbook - Second Edition
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Clojure Data Analysis Cookbook - Second Edition
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Jan 2015
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Paperback 372 pages
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Dive into data analysis with Clojure through over 100 practical recipes for every stage of the analysis and collection process
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Clojure Data Analysis Cookbook - Second Edition
Dive into data analysis with Clojure through over 100 practical recipes for every stage of the analysis and collection process
Description
This book is for those with a basic knowledge of Clojure, who are looking to push the language to excel with data analysis.
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Jan 2015 372 pages
AI Assistant AI Assistant
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Author Rochester
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Scala Data Analysis Cookbook (new)
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Scala Data Analysis Cookbook (new)
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Oct 2015
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Paperback 254 pages
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Navigate the world of data analysis, visualization, and machine learning with over 100 hands-on Scala recipes
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  • 9781784394998 eBook €20.98
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Scala Data Analysis Cookbook (new)
Navigate the world of data analysis, visualization, and machine learning with over 100 hands-on Scala recipes
Description
This book will introduce you to the most popular Scala tools, libraries, and frameworks through practical recipes around loading, manipulating, and preparing your data. It will also help you explore and make sense of your data using stunning and insightfulvisualizations, and machine learning toolkits. Starting with introductory recipes on utilizing the Breeze and Spark libraries, get to grips withhow to import data from a host of possible sources and how to pre-process numerical, string, and date data. Next, you’ll get an understanding of concepts that will help you visualize data using the Apache Zeppelin and Bokeh bindings in Scala, enabling exploratory data analysis. iscover how to program quintessential machine learning algorithms using Spark ML library. Work through steps to scale your machine learning models and deploy them into a standalone cluster, EC2, YARN, and Mesos. Finally dip into the powerful options presented by Spark Streaming, and machine learning for streaming data, as well as utilizing Spark GraphX.
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Oct 2015 254 pages
AI Assistant AI Assistant
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Author Manivannan
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Python Data Analysis Cookbook
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Python Data Analysis Cookbook
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Jul 2016
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Paperback 462 pages
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Clean, scrape, analyze, and visualize data with the power of Python!
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  • 9781785283857 eBook €22.99
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Python Data Analysis Cookbook
Clean, scrape, analyze, and visualize data with the power of Python!
Description
Data analysis is a rapidly evolving field and Python is a multi-paradigm programming language suitable for object-oriented application development and functional design patterns. As Python offers a range of tools and libraries for all purposes, it has slowly evolved as the primary language for data science, including topics on: data analysis, visualization, and machine learning. Python Data Analysis Cookbook focuses on reproducibility and creating production-ready systems. You will start with recipes that set the foundation for data analysis with libraries such as matplotlib, NumPy, and pandas. You will learn to create visualizations by choosing color maps and palettes then dive into statistical data analysis using distribution algorithms and correlations. You’ll then help you find your way around different data and numerical problems, get to grips with Spark and HDFS, and then set up migration scripts for web mining. In this book, you will dive deeper into recipes on spectral analysis, smoothing, and bootstrapping methods. Moving on, you will learn to rank stocks and check market efficiency, then work with metrics and clusters. You will achieve parallelism to improve system performance by using multiple threads and speeding up your code. By the end of the book, you will be capable of handling various data analysis techniques in Python and devising solutions for problem scenarios.
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Jul 2016 462 pages
AI Assistant AI Assistant
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Author Idris
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Getting Started with Python Data Analysis
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Getting Started with Python Data Analysis
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Nov 2015
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Paperback 188 pages
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Learn to use powerful Python libraries for effective data processing and analysis
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Getting Started with Python Data Analysis
Learn to use powerful Python libraries for effective data processing and analysis
Description
Data analysis is the process of applying logical and analytical reasoning to study each component of data. Python is a multi-domain, high-level, programming language. It’s often used as a scripting language because of its forgiving syntax and operability with a wide variety of different eco-systems. Python has powerful standard libraries or toolkits such as Pylearn2 and Hebel, which offers a fast, reliable, cross-platform environment for data analysis. With this book, we will get you started with Python data analysis and show you what its advantages are. The book starts by introducing the principles of data analysis and supported libraries, along with NumPy basics for statistic and data processing. Next it provides an overview of the Pandas package and uses its powerful features to solve data processing problems. Moving on, the book takes you through a brief overview of the Matplotlib API and some common plotting functions for DataFrame such as plot. Next, it will teach you to manipulate the time and data structure, and load and store data in a file or database using Python packages. The book will also teach you how to apply powerful packages in Python to process raw data into pure and helpful data using examples. Finally, the book gives you a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or build helpful products, such as recommendations and predictions using scikit-learn.
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Nov 2015 188 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Author Vo.T.H
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Data Analysis with R
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Data Analysis with R
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Dec 2015
Full star icon Full star icon Full star icon Full star icon Half star icon 4.4 (15)
Paperback 388 pages
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Data Analysis with R
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Description
Frequently the tool of choice for academics, R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. With over 7,000 user contributed packages, it’s easy to find support for the latest and greatest algorithms and techniques. Starting with the basics of R and statistical reasoning, Data Analysis with R dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples. Packed with engaging problems and exercises, this book begins with a review of R and its syntax. From there, get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. Solve the difficulties relating to performing data analysis in practice and find solutions to working with “messy data”, large data, communicating results, and facilitating reproducibility. This book is engineered to be an invaluable resource through many stages of anyone’s career as a data analyst.
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Dec 2015 388 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Author Fischetti
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Data Analysis with IBM SPSS Statistics
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Data Analysis with IBM SPSS Statistics
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Sep 2017
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9 (7)
Paperback 446 pages
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Implementing data modeling, descriptive statistics and ANOVA
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  • 9781787280700 eBook €27.98
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Data Analysis with IBM SPSS Statistics
Implementing data modeling, descriptive statistics and ANOVA
Description
SPSS Statistics is a software package used for logical batched and non-batched statistical analysis. Analytical tools such as SPSS can readily provide even a novice user with an overwhelming amount of information and a broad range of options for analyzing patterns in the data. The journey starts with installing and configuring SPSS Statistics for first use and exploring the data to understand its potential (as well as its limitations). Use the right statistical analysis technique such as regression, classification and more, and analyze your data in the best possible manner. Work with graphs and charts to visualize your findings. With this information in hand, the discovery of patterns within the data can be undertaken. Finally, the high level objective of developing predictive models that can be applied to other situations will be addressed. By the end of this book, you will have a firm understanding of the various statistical analysis techniques offered by SPSS Statistics, and be able to master its use for data analysis with ease.
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Sep 2017 446 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Author Ken Stehlik-Barry
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Hands-On Data Analysis with Scala
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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Hands-On Data Analysis with Scala
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May 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (3)
Paperback 298 pages
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Perform data collection, processing, manipulation, and visualization with Scala
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  • 9781789344264 eBook €20.98
  • 9781789346114 Paperback €36.99
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Hands-On Data Analysis with Scala
Perform data collection, processing, manipulation, and visualization with Scala
Description
Efficient business decisions with an accurate sense of business data helps in delivering better performance across products and services. This book helps you to leverage the popular Scala libraries and tools for performing core data analysis tasks with ease. The book begins with a quick overview of the building blocks of a standard data analysis process. You will learn to perform basic tasks like Extraction, Staging, Validation, Cleaning, and Shaping of datasets. You will later deep dive into the data exploration and visualization areas of the data analysis life cycle. You will make use of popular Scala libraries like Saddle, Breeze, Vegas, and PredictionIO for processing your datasets. You will learn statistical methods for deriving meaningful insights from data. You will also learn to create applications for Apache Spark 2.x on complex data analysis, in real-time. You will discover traditional machine learning techniques for doing data analysis. Furthermore, you will also be introduced to neural networks and deep learning from a data analysis standpoint. By the end of this book, you will be capable of handling large sets of structured and unstructured data, perform exploratory analysis, and building efficient Scala applications for discovering and delivering insights
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May 2019 298 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Gupta
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BIRT 2.6 Data Analysis and Reporting
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
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BIRT 2.6 Data Analysis and Reporting
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Jul 2010
Paperback 360 pages
Create, Design, Format, and Deploy Reports with the world's most popular Eclipse-based Business Intelligence and Reporting Tool
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  • 9781849511674 eBook €19.99
  • 9781849511667 Paperback €37.99
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BIRT 2.6 Data Analysis and Reporting
Create, Design, Format, and Deploy Reports with the world's most popular Eclipse-based Business Intelligence and Reporting Tool
Description
BIRT is an Eclipse-based open source reporting system for web applications based on Java and Java EE. To address a wide range of reporting needs within a typical application, ranging from operational or enterprise reporting to multi-dimensional online analytical processing (OLAP), you need to know BIRT from head to toe. If you wish to start making reports easily and quickly, and also want to be up-to-date with the latest developments in BIRT, then this book is for you. It will guide you from scratch to develop reports using the Eclipse BIRT project. You will learn how to connect to data, use report items to display and format data, and use scripting to build advanced reports and charts.The book steers you through each step of report setup, to creating, designing, formatting, and deploying reports with data from a wide range of data sources. Its focus is on familiarizing you with the most visible and familiar product built with the BIRT framework – the BIRT Report Designer. It starts by introducing the concepts of business intelligence and open source software, and different installation methods. It will introduce you to the various visual report elements that can be used to design BIRT reports, such as the Palette and Grid components. You will learn the details of the data components of BIRT (the Data Source and the Data Set), different types of source data that BIRT supports such as XML files, flat text files, and databases, and the creation of all of the elements while connecting to Data Sources in reports and Report Projects. By the end of the book, you will be able to enhance the presentation of your report using Charts, Hyperlinks, and Drill Through. You will also be able to take advantage of the scripting capabilities that BIRT has to offer with Expressions and Event Handlers and successfully deploy BIRT reports.The book includes a case study at the end along with a real-world example that runs throughout the book.
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Jul 2010 360 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author John Ward
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Data Analysis with STATA
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
AI Assistant
Data Analysis with STATA
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Oct 2015
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.2 (5)
Paperback 176 pages
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Explore the big data field and learn how to perform data analytics and predictive modelling in STATA
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  • 9781782173182 eBook €15.99
  • 9781782173175 Paperback €29.99
€15.99 €23.99
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Data Analysis with STATA
Explore the big data field and learn how to perform data analytics and predictive modelling in STATA
Description
STATA is an integrated software package that provides you with everything you need for data analysis, data management, and graphics. STATA also provides you with a platform to efficiently perform simulation, regression analysis (linear and multiple) [and custom programming. This book covers data management, graphs visualization, and programming in STATA. Starting with an introduction to STATA and data analytics you’ll move on to STATA programming and data management. Next, the book takes you through data visualization and all the important statistical tests in STATA. Linear and logistic regression in STATA is also covered. As you progress through the book, you will explore a few analyses, including the survey analysis, time series analysis, and survival analysis in STATA. You’ll also discover different types of statistical modelling techniques and learn how to implement these techniques in STATA.
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Oct 2015 176 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Kothari
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Instant jQuery Flot Visual Data Analysis
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
AI Assistant
Instant jQuery Flot Visual Data Analysis
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Oct 2013
Full star icon Full star icon Full star icon Full star icon Empty star icon 4 (1)
Paperback 70 pages
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Visualize and analyze your data with the jQuery Flot plotting library using real-world examples
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  • 9781783280667 eBook €10.99
  • 9781783280650 Paperback €19.99
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Instant jQuery Flot Visual Data Analysis
Visualize and analyze your data with the jQuery Flot plotting library using real-world examples
Description
Data visualization and analysis is a crucial skill in many software projects. Flot uses jQuery and HTML5 to add easy and powerful visualization capabilities to any web application. Flot produces beautiful visualizations with a minimal amount of code. It is also highly configurable, extensible, and includes many plugins out of the box. A practical guide to take you through the basics of using Flot to visualize your data; the book describes Flot's functionality in dedicated sections that include code, screenshots, and detailed explanations so that you can learn to produce charts in minutes. As you progress though this book, it will guide you through real-world examples to show you how to use statistical techniques with Flot for interactive data visualization and analysis. Starting with the very basics, you will learn exactly what you need to do to display the simplest chart using Flot. This step-by-step guide takes you through Flot's many features and settings until you can finally master the techniques you'll need to apply Flot to your application's data. You'll learn to create basic point, line, and bar charts and to use Flot's stack, pie, and time plugins to create specialized chart types. Along with learning to display complex data with multiple customizable axes you will learn to make your charts interactive with Flot's crosshair plugin. Finally, this book will guide you through learning statistical techniques via the jStat JavaScript library to analyse data; along with Flot's errorbars and fillbetween plugins to display error margins and data percentiles. Instant jQuery Flot Visual Data Analysis will give you a head start so that you can add data visualization features to your applications with ease.
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Oct 2013 70 pages
AI Assistant AI Assistant
AI Assistant: Features our revolutionary AI Assistant technology which lets you interact with our Books to enhance your learning
Authors
Author Brian Peiris
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eBook €10.99 €15.99
Paperback €19.99
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