Statistics And Data Visualisation With Python
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Statistics And Data Visualisation With Python
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Author : Jesus Rogel-Salazar
language : en
Publisher: CRC Press
Release Date : 2023-01-31
Statistics And Data Visualisation With Python written by Jesus Rogel-Salazar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-31 with Social Science categories.
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 Analytics And Visualization
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Author : Phuong Vo.T.H
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-03-31
Python Data Analytics And Visualization written by Phuong Vo.T.H and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-31 with Computers categories.
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
Fundamentals Of Statistics And Visualization In Python
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Author : Karen Yang
language : en
Publisher:
Release Date : 2020
Fundamentals Of Statistics And Visualization In Python written by Karen Yang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Learn to display your data using Python's visualization tools About This Video Discover and sharpen your skills in core statistics and visualization Create vibrant data visualizations using Seaborn and Matplotlib Apply what you've learned from this course to your data analysis projects In Detail Statistics and visualization in Python can be applied to a wide variety of areas; having these skills is crucial for data scientists. In this course, we explore several core statistical concepts to utilize data; construct confidence intervals in Python and assess the results; discover correlations; and update your beliefs using Bayesian Inference. In this tutorial, you will discover how to use the Statsmodels, Matplotlib, pandas, and Seaborn Python libraries for statistical data visualization. Follow along with author--Dr. Karen Yang, a seasoned data scientist and data engineer--to explore, learn, and strengthen your skills in fundamental statistics and visualization. This course utilizes the Jupyter Notebook environment to execute tasks. By the end of this learning journey, you'll have developed a solid understanding of fundamental statistics and visualization concepts and will be confident enough to apply them to your data analysis projects. Please note that prior knowledge of Python programming and some familiarity with pandas and NumPy are needed in order to get the best out of this course.
Statistics And Data Visualization In Climate With R And Python
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Author : Samuel S. Shen
language : en
Publisher:
Release Date : 2023
Statistics And Data Visualization In Climate With R And Python written by Samuel S. Shen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Climatology categories.
"A comprehensive overview of essential statistical concepts, useful statistical methods, data visualization, and computing tools for the climate and related sciences. This book is an invaluable reference for students and researchers in climatology and its connected fields who wish to learn data science, statistics, R and Python programming"--
Data Visualization And Statistical Literacy For Open And Big Data
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Author : Prodromou, Theodosia
language : en
Publisher: IGI Global
Release Date : 2017-03-20
Data Visualization And Statistical Literacy For Open And Big Data written by Prodromou, Theodosia and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-20 with Computers categories.
Data visualization has emerged as a serious scholarly topic, and a wide range of tools have recently been developed at an accelerated pace to aid in this research area. Examining different ways of analyzing big data can result in increased efficiency for many corporations and organizations. Data Visualization and Statistical Literacy for Open and Big Data highlights methodological developments in the way that data analytics is both learned and taught. Featuring extensive coverage on emerging relevant topics such as data complexity, statistics education, and curriculum development, this publication is geared toward teachers, academicians, students, engineers, professionals, and researchers that are interested in expanding their knowledge of data examination and analysis.
Oswaal Cbse Question Bank Class 10 Artificial Intelligence Chapterwise And Topicwise Solved Papers For Board Exams 2025
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Author : Oswaal Editorial Board
language : en
Publisher: Oswaal Books
Release Date : 2024-05-21
Oswaal Cbse Question Bank Class 10 Artificial Intelligence Chapterwise And Topicwise Solved Papers For Board Exams 2025 written by Oswaal Editorial Board and has been published by Oswaal Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-21 with Study Aids categories.
Description of the Product: • 100% Updated with Latest Syllabus Questions Typologies: We have got you covered with the latest and 100% updated curriculum • Crisp Revision with Topic-wise Revision Notes & Smart Mind Maps: Study smart, not hard! • Extensive Practice with 700+ Questions & Self Assessment Papers: To give you 700+ chances to become a champ! • Concept Clarity with 500+ Concepts & Concept Videos: For you to learn the cool way—with videos and mind-blowing concepts • 100% Exam Readiness with Expert Answering Tips & Suggestions for • Students: For you to be on the cutting edge of the coolest educational trends
Interactive Data Visualization With Python Second Edition
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Author : Abha Belorkar
language : en
Publisher:
Release Date : 2020-04-13
Interactive Data Visualization With Python Second Edition written by Abha Belorkar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-13 with Computers categories.
Interactive Data Visualization with Python sharpens your data exploration skills, tells you everything there is to know about interactive data visualization in Python, and most importantly, helps you make your storytelling more intuitive and persuasive.
Encyclopedia Of Bioinformatics And Computational Biology
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Author :
language : en
Publisher: Elsevier
Release Date : 2018-08-21
Encyclopedia Of Bioinformatics And Computational Biology written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-21 with Medical categories.
Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Three Volume Set combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases
Python For Data Science For Dummies
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Author : John Paul Mueller
language : en
Publisher: John Wiley & Sons
Release Date : 2015-07-07
Python For Data Science For Dummies written by John Paul Mueller and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-07 with Computers categories.
Unleash the power of Python for your data analysis projects with For Dummies! Python is the preferred programming language for data scientists and combines the best features of Matlab, Mathematica, and R into libraries specific to data analysis and visualization. Python for Data Science For Dummies shows you how to take advantage of Python programming to acquire, organize, process, and analyze large amounts of information and use basic statistics concepts to identify trends and patterns. You’ll get familiar with the Python development environment, manipulate data, design compelling visualizations, and solve scientific computing challenges as you work your way through this user-friendly guide. Covers the fundamentals of Python data analysis programming and statistics to help you build a solid foundation in data science concepts like probability, random distributions, hypothesis testing, and regression models Explains objects, functions, modules, and libraries and their role in data analysis Walks you through some of the most widely-used libraries, including NumPy, SciPy, BeautifulSoup, Pandas, and MatPlobLib Whether you’re new to data analysis or just new to Python, Python for Data Science For Dummies is your practical guide to getting a grip on data overload and doing interesting things with the oodles of information you uncover.
Interactive Data Visualization With Python
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Author : Abha Belorkar
language : en
Publisher:
Release Date : 2019-10-22
Interactive Data Visualization With Python written by Abha Belorkar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-22 with categories.
Create your own clear and impactful interactive data visualizations with the powerful data visualization libraries of Python Key Features Study and use Python interactive libraries, such as Bokeh and Plotly Explore different visualization principles and understand when to use which one Create interactive data visualizations with real-world data Book 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 learn Explore and apply different static and interactive data visualization techniques Make effective use of plot types and features from the Matplotlib, Seaborn, Altair, Bokeh, and Plotly libraries Master the art of selecting appropriate plotting parameters and styles to create attractive plots Choose meaningful and informative ways to present your stories through data Customize data visualization for specific scenarios, contexts, and audiences Avoid common errors and slip-ups in visualizing data Who 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.