Statistics And Data Visualisation With Python

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Statistics and Data Visualisation with Python

Author : Jesus Rogel-Salazar
Publisher : CRC Press
ISBN 13 : 1000798380
Total Pages : 554 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Statistics and Data Visualisation with Python by : Jesus Rogel-Salazar

Download or read book Statistics and Data Visualisation with Python written by Jesus Rogel-Salazar and published by CRC Press. This book was released on 2023-01-31 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended to serve as a bridge in statistics for graduates and business practitioners interested in using their skills in the area of data science and analytics as well as statistical analysis in general. On the one hand, the book is intended to be a refresher for readers who have taken some courses in statistics, but who have not necessarily used it in their day-to-day work. On the other hand, the material can be suitable for readers interested in the subject as a first encounter with statistical work in Python. Statistics and Data Visualisation with Python aims to build statistical knowledge from the ground up by enabling the reader to understand the ideas behind inferential statistics and begin to formulate hypotheses that form the foundations for the applications and algorithms in statistical analysis, business analytics, machine learning, and applied machine learning. This book begins with the basics of programming in Python and data analysis, to help construct a solid basis in statistical methods and hypothesis testing, which are useful in many modern applications.

Statistics and Data Visualisation with Python

Author : Jesus Rogel-Salazar
Publisher : CRC Press
ISBN 13 : 1000798402
Total Pages : 581 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Statistics and Data Visualisation with Python by : Jesus Rogel-Salazar

Download or read book Statistics and Data Visualisation with Python written by Jesus Rogel-Salazar and published by CRC Press. This book was released on 2023-01-31 with total page 581 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended to serve as a bridge in statistics for graduates and business practitioners interested in using their skills in the area of data science and analytics as well as statistical analysis in general. On the one hand, the book is intended to be a refresher for readers who have taken some courses in statistics, but who have not necessarily used it in their day-to-day work. On the other hand, the material can be suitable for readers interested in the subject as a first encounter with statistical work in Python. Statistics and Data Visualisation with Python aims to build statistical knowledge from the ground up by enabling the reader to understand the ideas behind inferential statistics and begin to formulate hypotheses that form the foundations for the applications and algorithms in statistical analysis, business analytics, machine learning, and applied machine learning. This book begins with the basics of programming in Python and data analysis, to help construct a solid basis in statistical methods and hypothesis testing, which are useful in many modern applications.

Python Data Science Handbook

Author : Jake VanderPlas
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491912138
Total Pages : 743 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Python Data Science Handbook by : Jake VanderPlas

Download or read book Python Data Science Handbook written by Jake VanderPlas and published by "O'Reilly Media, Inc.". This book was released on 2016-11-21 with total page 743 pages. Available in PDF, EPUB and Kindle. Book excerpt: For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

Python Data Visualization Essentials Guide

Author : Kallur Rahman
Publisher : BPB Publications
ISBN 13 : 9391030076
Total Pages : 319 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Python Data Visualization Essentials Guide by : Kallur Rahman

Download or read book Python Data Visualization Essentials Guide written by Kallur Rahman and published by BPB Publications. This book was released on 2021-07-30 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build your data science skills. Start data visualization Using Python. Right away. Become a good data analyst by creating quality data visualizations using Python. KEY FEATURES ● Exciting coverage on loads of Python libraries, including Matplotlib, Seaborn, Pandas, and Plotly. ● Tons of examples, illustrations, and use-cases to demonstrate visual storytelling of varied datasets. ● Covers a strong fundamental understanding of exploratory data analysis (EDA), statistical modeling, and data mining. DESCRIPTION Data visualization plays a major role in solving data science challenges with various capabilities it offers. This book aims to equip you with a sound knowledge of Python in conjunction with the concepts you need to master to succeed as a data visualization expert. The book starts with a brief introduction to the world of data visualization and talks about why it is important, the history of visualization, and the capabilities it offers. You will learn how to do simple Python-based visualization with examples with progressive complexity of key features. The book starts with Matplotlib and explores the power of data visualization with over 50 examples. It then explores the power of data visualization using one of the popular exploratory data analysis-oriented libraries, Pandas. The book talks about statistically inclined data visualization libraries such as Seaborn. The book also teaches how we can leverage bokeh and Plotly for interactive data visualization. Each chapter is enriched and loaded with 30+ examples that will guide you in learning everything about data visualization and storytelling of mixed datasets. WHAT YOU WILL LEARN ● Learn to work with popular Python libraries and frameworks, including Seaborn, Bokeh, and Plotly. ● Practice your data visualization understanding across numerous datasets and real examples. ● Learn to visualize geospatial and time-series datasets. ● Perform correlation and EDA analysis using Pandas and Matplotlib. ● Get to know storytelling of complex and unstructured data using Bokeh and Pandas. ● Learn best practices in writing clean and short python scripts for a quicker visual summary of datasets. WHO THIS BOOK IS FOR This book is for all data analytics professionals, data scientists, and data mining hobbyists who want to be strong data visualizers by learning all the popular Python data visualization libraries. Prior working knowledge of Python is assumed. TABLE OF CONTENTS 1. Introduction to Data Visualization 2. Why Data Visualization 3. Various Data Visualization Elements and Tools 4. Using Matplotlib with Python 5. Using NumPy and Pandas for Plotting 6. Using Seaborn for Visualization 7. Using Bokeh with Python 8. Using Plotly, Folium, and Other Tools for Data Visualization 9. Hands-on Examples and Exercises, Case Studies, and Further Resources

Interactive Data Visualization with Python

Author : Abha Belorkar
Publisher : Packt Publishing Ltd
ISBN 13 : 1800201060
Total Pages : 362 pages
Book Rating : 4.8/5 (2 download)

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Book Synopsis Interactive Data Visualization with Python by : Abha Belorkar

Download or read book Interactive Data Visualization with Python written by Abha Belorkar and published by Packt Publishing Ltd. This book was released on 2020-04-14 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create your own clear and impactful interactive data visualizations with the powerful data visualization libraries of Python Key FeaturesStudy and use Python interactive libraries, such as Bokeh and PlotlyExplore different visualization principles and understand when to use which oneCreate interactive data visualizations with real-world dataBook Description With so much data being continuously generated, developers, who can present data as impactful and interesting visualizations, are always in demand. Interactive Data Visualization with Python sharpens your data exploration skills, tells you everything there is to know about interactive data visualization in Python. You'll begin by learning how to draw various plots with Matplotlib and Seaborn, the non-interactive data visualization libraries. You'll study different types of visualizations, compare them, and find out how to select a particular type of visualization to suit your requirements. After you get a hang of the various non-interactive visualization libraries, you'll learn the principles of intuitive and persuasive data visualization, and use Bokeh and Plotly to transform your visuals into strong stories. You'll also gain insight into how interactive data and model visualization can optimize the performance of a regression model. By the end of the course, you'll have a new skill set that'll make you the go-to person for transforming data visualizations into engaging and interesting stories. What you will learnExplore and apply different interactive data visualization techniquesManipulate plotting parameters and styles to create appealing plotsCustomize data visualization for different audiencesDesign data visualizations using interactive librariesUse Matplotlib, Seaborn, Altair and Bokeh for drawing appealing plotsCustomize data visualization for different scenariosWho this book is for This book intends to provide a solid training ground for Python developers, data analysts and data scientists to enable them to present critical data insights in a way that best captures the user's attention and imagination. It serves as a simple step-by-step guide that demonstrates the different types and components of visualization, the principles, and techniques of effective interactivity, as well as common pitfalls to avoid when creating interactive data visualizations. Students should have an intermediate level of competency in writing Python code, as well as some familiarity with using libraries such as pandas.

Data Visualization

Author : Kieran Healy
Publisher : Princeton University Press
ISBN 13 : 0691181624
Total Pages : 292 pages
Book Rating : 4.6/5 (911 download)

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Book Synopsis Data Visualization by : Kieran Healy

Download or read book Data Visualization written by Kieran Healy and published by Princeton University Press. This book was released on 2018-12-18 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions

Visualize This

Author : Nathan Yau
Publisher : John Wiley & Sons
ISBN 13 : 1118140265
Total Pages : 431 pages
Book Rating : 4.1/5 (181 download)

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Book Synopsis Visualize This by : Nathan Yau

Download or read book Visualize This written by Nathan Yau and published by John Wiley & Sons. This book was released on 2011-06-13 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical data design tips from a data visualization expert of the modern age Data doesn't decrease; it is ever-increasing and can be overwhelming to organize in a way that makes sense to its intended audience. Wouldn't it be wonderful if we could actually visualize data in such a way that we could maximize its potential and tell a story in a clear, concise manner? Thanks to the creative genius of Nathan Yau, we can. With this full-color book, data visualization guru and author Nathan Yau uses step-by-step tutorials to show you how to visualize and tell stories with data. He explains how to gather, parse, and format data and then design high quality graphics that help you explore and present patterns, outliers, and relationships. Presents a unique approach to visualizing and telling stories with data, from a data visualization expert and the creator of flowingdata.com, Nathan Yau Offers step-by-step tutorials and practical design tips for creating statistical graphics, geographical maps, and information design to find meaning in the numbers Details tools that can be used to visualize data-native graphics for the Web, such as ActionScript, Flash libraries, PHP, and JavaScript and tools to design graphics for print, such as R and Illustrator Contains numerous examples and descriptions of patterns and outliers and explains how to show them Visualize This demonstrates how to explain data visually so that you can present your information in a way that is easy to understand and appealing.

Python: Data Analytics and Visualization

Author : Phuong Vo.T.H
Publisher : Packt Publishing Ltd
ISBN 13 : 1788294858
Total Pages : 866 pages
Book Rating : 4.7/5 (882 download)

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Book Synopsis Python: Data Analytics and Visualization by : Phuong Vo.T.H

Download or read book Python: Data Analytics and Visualization written by Phuong Vo.T.H and published by Packt Publishing Ltd. This book was released on 2017-03-31 with total page 866 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand, evaluate, and visualize data About This Book Learn basic steps of data analysis and how to use Python and its packages A step-by-step guide to predictive modeling including tips, tricks, and best practices Effectively visualize a broad set of analyzed data and generate effective results Who This Book Is For This book is for Python Developers who are keen to get into data analysis and wish to visualize their analyzed data in a more efficient and insightful manner. What You Will Learn Get acquainted with NumPy and use arrays and array-oriented computing in data analysis Process and analyze data using the time-series capabilities of Pandas Understand the statistical and mathematical concepts behind predictive analytics algorithms Data visualization with Matplotlib Interactive plotting with NumPy, Scipy, and MKL functions Build financial models using Monte-Carlo simulations Create directed graphs and multi-graphs Advanced visualization with D3 In Detail You will start the course with an introduction to the principles of data analysis and supported libraries, along with NumPy basics for statistics and data processing. Next, you will overview the Pandas package and use its powerful features to solve data-processing problems. Moving on, you will get a brief overview of the Matplotlib API .Next, you will learn to manipulate time and data structures, and load and store data in a file or database using Python packages. You will learn how to apply powerful packages in Python to process raw data into pure and helpful data using examples. You will also get a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or building helpful products such as recommendations and predictions using Scikit-learn. After this, you will move on to a data analytics specialization—predictive analytics. Social media and IOT have resulted in an avalanche of data. You will get started with predictive analytics using Python. You will see how to create predictive models from data. You will get balanced information on statistical and mathematical concepts, and implement them in Python using libraries such as Pandas, scikit-learn, and NumPy. You'll learn more about the best predictive modeling algorithms such as Linear Regression, Decision Tree, and Logistic Regression. Finally, you will master best practices in predictive modeling. After this, you will get all the practical guidance you need to help you on the journey to effective data visualization. Starting with a chapter on data frameworks, which explains the transformation of data into information and eventually knowledge, this path subsequently cover the complete visualization process using the most popular Python libraries with working examples This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Getting Started with Python Data Analysis, Phuong Vo.T.H &Martin Czygan Learning Predictive Analytics with Python, Ashish Kumar Mastering Python Data Visualization, Kirthi Raman Style and approach The course acts as a step-by-step guide to get you familiar with data analysis and the libraries supported by Python with the help of real-world examples and datasets. It also helps you gain practical insights into predictive modeling by implementing predictive-analytics algorithms on public datasets with Python. The course offers a wealth of practical guidance to help you on this journey to data visualization

The Grammar of Graphics

Author : Leland Wilkinson
Publisher : Springer Science & Business Media
ISBN 13 : 1475731000
Total Pages : 415 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis The Grammar of Graphics by : Leland Wilkinson

Download or read book The Grammar of Graphics written by Leland Wilkinson and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written for statisticians, computer scientists, geographers, research and applied scientists, and others interested in visualizing data, this book presents a unique foundation for producing almost every quantitative graphic found in scientific journals, newspapers, statistical packages, and data visualization systems. It was designed for a distributed computing environment, with special attention given to conserving computer code and system resources. While the tangible result of this work is a Java production graphics library, the text focuses on the deep structures involved in producing quantitative graphics from data. It investigates the rules that underlie pie charts, bar charts, scatterplots, function plots, maps, mosaics, and radar charts. These rules are abstracted from the work of Bertin, Cleveland, Kosslyn, MacEachren, Pinker, Tufte, Tukey, Tobler, and other theorists of quantitative graphics.

Data Visualization with Python

Author : Dr. Pooja
Publisher : BPB Publications
ISBN 13 : 9355515383
Total Pages : 309 pages
Book Rating : 4.3/5 (555 download)

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Book Synopsis Data Visualization with Python by : Dr. Pooja

Download or read book Data Visualization with Python written by Dr. Pooja and published by BPB Publications. This book was released on 2023-07-11 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transforming data into actionable insights using Python KEY FEATURES ● Gain a comprehensive understanding of data visualization and exploratory data analysis (EDA) using Python. ● Discover valuable insights and patterns in data through visual analysis. ● Master the art of effectively communicating complex concepts by creating compelling and impactful data visualizations. DESCRIPTION Python is a popular programming language for data visualization due to its rich ecosystem of libraries and tools. If you're interested in delving into data visualization in Python, this book is an excellent resource to begin your journey. With Matplotlib, you'll master the art of creating a wide range of charts, plots, and graphs. From basic line plots to complex 3D visualizations, you'll learn how to transform raw data into engaging visuals that tell compelling stories. Dive into Seaborn, a high-level library built on top of Matplotlib, and discover how to effortlessly create beautiful and informative statistical visualizations effortlessly. From heatmaps to distribution plots, you'll unleash the full potential of Seaborn in your data analysis endeavors. Lastly, you will learn how to unleash the true potential of Bokeh and create compelling data visualizations that allow users to explore and interact with data dynamically. By the end of the book, you will have acquired the knowledge and skills necessary to create a diverse range of visualizations proficiently. WHAT YOU WILL LEARN ● Utilize Matplotlib, Seaborn, and Bokeh to produce visually captivating visualizations. ● Gain expertise in various types of charts, plots, and graphs. ● Craft visually appealing and informative statistical visualizations. ● Construct interactive and adaptable plots using Bokeh. ● Explore various techniques for conducting Exploratory Data Analysis (EDA). WHO THIS BOOK IS FOR This book caters to a wide audience, including undergraduate and postgraduate students, researchers, data managers, and data analysts. It presents an all-encompassing exploration of data visualization, equipping you with the essential groundwork to progress as a data-driven professional. TABLE OF CONTENTS 1. Understanding Data 2. Data Visualization – Importance 3. Data Visualization Use Cases 4. Data Visualization Tools and Techniques 5. Data Visualization with Matplotlib 6. Data Visualization with Seaborn 7. Data Visualization with Bokeh 8. Exploratory Data Analysis

Hands-on Data Analysis and Visualization with Pandas

Author : PURNA CHANDER RAO. KATHULA
Publisher : BPB Publications
ISBN 13 : 9389845645
Total Pages : 366 pages
Book Rating : 4.3/5 (898 download)

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Book Synopsis Hands-on Data Analysis and Visualization with Pandas by : PURNA CHANDER RAO. KATHULA

Download or read book Hands-on Data Analysis and Visualization with Pandas written by PURNA CHANDER RAO. KATHULA and published by BPB Publications. This book was released on 2020-08-13 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use JupyterLab, Numpy, pandas, Scipy, Matplotlib, and Seaborn for Data science KEY FEATURESÊÊ _ Get familiar with different inbuilt Data structures, Functional programming, and Datetime objects. _ Handling heavy Datasets to optimize the data types for memory management, reading files in chunks, dask, and modin pandas. _ Time-series analysis to find trends, seasonality, and cyclic components. _ Seaborn to build aesthetic plots with high-level interfaces and customized themes. _ Exploratory data analysis with real-time datasets to maximize the insights about data. DESCRIPTIONÊ The book will start with quick introductions to Python and its ecosystem libraries for data science such as JupyterLab, Numpy, Pandas, SciPy, Matplotlib, and Seaborn. This book will help in learning python data structures and essential concepts such as Functions, Lambdas, List comprehensions, Datetime objects, etc. required for data engineering. It also covers an in-depth understanding of Python data science packages where JupyterLab used as an IDE for writing, documenting, and executing the python code, Numpy used for computation of numerical operations, Pandas for cleaning and reorganizing the data, handling large datasets and merging the dataframes to get meaningful insights. You will go through the statistics to understand the relation between the variables using SciPy and building visualization charts using Matplotllib and Seaborn libraries. WHAT WILL YOU LEARNÊ _ Learn about Python data containers, their methods, and attributes. _ Learn Numpy arrays for the computation of numerical data. _ Learn Pandas data structures, DataFrames, and Series. _ Learn statistics measures of central tendency, central limit theorem, confidence intervals, and hypothesis testing. _ A brief understanding of visualization, control, and draw different inbuilt charts to extract important variables, detect outliers, and anomalies using Matplotlib and Seaborn. Ê WHO THIS BOOK IS FORÊ This book is for anyone who wants to use Python for Data Analysis and Visualization. This book is for novices as well as experienced readers with working knowledge of the pandas library. Basic knowledge of Python is a must.Ê TABLE OF CONTENTSÊ 1. Introduction to Data Analysis 2. Jupyter lab 3. Python overview 4. Introduction to Numpy 5. Introduction to PandasÊ 6. Data Analysis 7. Time-Series Analysis 8. Introduction to Statistics 9. Matplotlib 10. Seaborn 11. Exploratory Data Analysis

Data Visualization with Python

Author : Mario Döbler
Publisher :
ISBN 13 : 9781789956467
Total Pages : 368 pages
Book Rating : 4.9/5 (564 download)

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Book Synopsis Data Visualization with Python by : Mario Döbler

Download or read book Data Visualization with Python written by Mario Döbler and published by . This book was released on 2019-02-28 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand, explore, and effectively present data using the powerful data visualization techniques of Python programming. Key Features Study key visualization tools and techniques with real-world data Explore industry-standard plotting libraries, including Matplotlib and Seaborn Breathe life into your visuals with exciting widgets and animations using Bokeh Book Description Data Visualization with Python reviews the spectrum of data visualization and its importance. Designed for beginners, it'll help you learn about statistics by computing mean, median, and variance for certain numbers. In the first few chapters, you'll be able to take a quick tour of key NumPy and Pandas techniques, which include indexing, slicing, iterating, filtering, and grouping. The book keeps pace with your learning needs, introducing you to various visualization libraries. As you work through chapters on Matplotlib and Seaborn, you'll discover how to create visualizations in an easier way. After a lesson on these concepts, you can then brush up on advanced visualization techniques like geoplots and interactive plots. You'll learn how to make sense of geospatial data, create interactive visualizations that can be integrated into any webpage, and take any dataset to build beautiful visualizations. What's more? You'll study how to plot geospatial data on a map using Choropleth plot and understand the basics of Bokeh, extending plots by adding widgets and animating the display of information. By the end of this book, you'll be able to put your learning into practice with an engaging activity, where you can work with a new dataset to create an insightful capstone visualization. What you will learn Understand and use various plot types with Python Explore and work with different plotting libraries Learn to create effective visualizations Improve your Python data wrangling skills Hone your skill set by using tools like Matplotlib, Seaborn, and Bokeh Reinforce your knowledge of various data formats and representations Who this book is for Data Visualization with Python is designed for developers and scientists, who want to get into data science or want to use data visualizations to enrich their personal and professional projects. You do not need any prior experience in data analytics and visualization, however, it'll help you to have some knowledge of Python and familiarity with high school level mathematics. Even though this is a beginner level course on data visualization, experienced developers will be able to improve their Python skills by working with real-world data.

Python for Data Science For Dummies

Author : John Paul Mueller
Publisher : John Wiley & Sons
ISBN 13 : 1119547628
Total Pages : 502 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Python for Data Science For Dummies by : John Paul Mueller

Download or read book Python for Data Science For Dummies written by John Paul Mueller and published by John Wiley & Sons. This book was released on 2019-02-27 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fast and easy way to learn Python programming and statistics Python is a general-purpose programming language created in the late 1980s—and named after Monty Python—that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the PyGame library. Python For Data Science For Dummies is written for people who are new to data analysis, and discusses the basics of Python data analysis programming and statistics. The book also discusses Google Colab, which makes it possible to write Python code in the cloud. Get started with data science and Python Visualize information Wrangle data Learn from data The book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction.

SPSS Statistics for Data Analysis and Visualization

Author : Keith McCormick
Publisher : John Wiley & Sons
ISBN 13 : 1119003660
Total Pages : 528 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis SPSS Statistics for Data Analysis and Visualization by : Keith McCormick

Download or read book SPSS Statistics for Data Analysis and Visualization written by Keith McCormick and published by John Wiley & Sons. This book was released on 2017-04-17 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dive deeper into SPSS Statistics for more efficient, accurate,and sophisticated data analysis and visualization SPSS Statistics for Data Analysis and Visualization goesbeyond the basics of SPSS Statistics to show you advancedtechniques that exploit the full capabilities of SPSS. The authorsexplain when and why to use each technique, and then walk youthrough the execution with a pragmatic, nuts and bolts example.Coverage includes extensive, in-depth discussion of advancedstatistical techniques, data visualization, predictive analytics,and SPSS programming, including automation and integration withother languages like R and Python. You'll learn the best methods topower through an analysis, with more efficient, elegant, andaccurate code. IBM SPSS Statistics is complex: true mastery requires a deepunderstanding of statistical theory, the user interface, andprogramming. Most users don't encounter all of the methods SPSSoffers, leaving many little-known modules undiscovered. This bookwalks you through tools you may have never noticed, and shows youhow they can be used to streamline your workflow and enable you toproduce more accurate results. Conduct a more efficient and accurate analysis Display complex relationships and create bettervisualizations Model complex interactions and master predictive analytics Integrate R and Python with SPSS Statistics for more efficient,more powerful code These "hidden tools" can help you produce charts that simplywouldn't be possible any other way, and the support for otherprogramming languages gives you better options for solving complexproblems. If you're ready to take advantage of everything thispowerful software package has to offer, SPSS Statistics for DataAnalysis and Visualization is the expert-led training youneed.

Fundamentals of Data Visualization

Author : Claus O. Wilke
Publisher : O'Reilly Media
ISBN 13 : 1492031054
Total Pages : 390 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Fundamentals of Data Visualization by : Claus O. Wilke

Download or read book Fundamentals of Data Visualization written by Claus O. Wilke and published by O'Reilly Media. This book was released on 2019-03-18 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business analysts often have to navigate a bewildering array of visualization choices and options. This practical book takes you through many commonly encountered visualization problems, and it provides guidelines on how to turn large datasets into clear and compelling figures. What visualization type is best for the story you want to tell? How do you make informative figures that are visually pleasing? Author Claus O. Wilke teaches you the elements most critical to successful data visualization. Explore the basic concepts of color as a tool to highlight, distinguish, or represent a value Understand the importance of redundant coding to ensure you provide key information in multiple ways Use the book’s visualizations directory, a graphical guide to commonly used types of data visualizations Get extensive examples of good and bad figures Learn how to use figures in a document or report and how employ them effectively to tell a compelling story

Essential MATLAB and Octave

Author : Jesus Rogel-Salazar
Publisher : CRC Press
ISBN 13 : 1482234645
Total Pages : 288 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Essential MATLAB and Octave by : Jesus Rogel-Salazar

Download or read book Essential MATLAB and Octave written by Jesus Rogel-Salazar and published by CRC Press. This book was released on 2014-11-06 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn Two Popular Programming Languages in a Single Volume Widely used by scientists and engineers, well-established MATLAB® and open-source Octave are similar software programs providing excellent capabilities for data analysis, visualization, and more. By means of straightforward explanations and examples from different areas in mathematics, engineering, finance, and physics, Essential MATLAB and Octave explains how MATLAB and Octave are powerful tools applicable to a variety of problems. This text provides an introduction that reveals basic structures and syntax, demonstrates the use of functions and procedures, outlines availability in various platforms, and highlights the most important elements for both programs. Effectively Implement Models and Prototypes Using Computational Models This text requires no prior knowledge. Self-contained, it allows the reader to use the material whenever needed rather than follow a particular order. Compatible with both languages, the book material incorporates commands and structures that allow the reader to gain a greater awareness of MATLAB and Octave, write their own code, and implement their scripts and programs within a variety of applicable fields. It is always made clear when particular examples apply only to MATLAB or only to Octave, allowing the book to be used flexibly depending on readers’ requirements. Includes brief, simple code that works in both MATLAB and Octave Provides exercise sections at the end of each chapter Introduces framed examples and discussions with a scientific twist Exercises are provided at the end of each chapter Essential MATLAB and Octave offers an introductory course in MATLAB and Octave programming and is an authoritative resource for students in physics, mathematics, statistics, engineering, and any other subjects that require the use of computers to solve numerical problems.

Introduction to Python in Earth Science Data Analysis

Author : Maurizio Petrelli
Publisher : Springer Nature
ISBN 13 : 3030780554
Total Pages : 229 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Introduction to Python in Earth Science Data Analysis by : Maurizio Petrelli

Download or read book Introduction to Python in Earth Science Data Analysis written by Maurizio Petrelli and published by Springer Nature. This book was released on 2021-09-16 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences. It drives the reader from his very first steps with Python, like setting up the environment and starting writing the first lines of codes, to proficient use in visualizing, analyzing, and modelling data in the field of Earth Science. Each chapter contains explicative examples of code, and each script is commented in detail. The book is minded for very beginners in Python programming, and it can be used in teaching courses at master or PhD levels. Also, Early careers and experienced researchers who would like to start learning Python programming for the solution of geological problems will benefit the reading of the book.