Python for Data Analysis PDF Download

Author: Wes McKinney
Publisher: "O'Reilly Media, Inc."
ISBN: 1491957611
Category : Computers
Languages : en
Pages : 553

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Book Description
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples

Author: Brian Larson
Publisher: McGraw Hill Professional
ISBN: 1260458628
Category : Computers
Languages : en
Pages : 546

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Book Description
Explore, create, and manage highly interactive data visualizations using Microsoft Power BI Extract meaningful business insights from your disparate enterprise data using the detailed information contained in this practical guide. Written by a recognized BI expert and bestselling author, Data Analysis with Microsoft Power BI teaches you the skills you need to interact with, author, and maintain robust visualizations and custom data models. Hands-on exercises based on real-life business scenarios clearly demonstrate each technique. Publishing your results to the Power BI Service (PowerBI.com) and Power BI Report Server are also fully covered. Inside, you will discover how to: •Understand Business Intelligence and self-service analytics •Explore the tools and features of Microsoft Power BI •Create and format effective data visualizations •Incorporate advanced interactivity and custom graphics •Build and populate accurate data models •Transform data using the Power BI Query Editor •Work with measures, calculated columns, and tabular models •Write powerful DAX language scripts •Share content on the PowerBI Service (PowerBI.com) •Store your visualizations on the Power BI Report Server

Author: Cathy Tanimura
Publisher: "O'Reilly Media, Inc."
ISBN: 1492088730
Category : Computers
Languages : en
Pages : 360

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Book Description
With the explosion of data, computing power, and cloud data warehouses, SQL has become an even more indispensable tool for the savvy analyst or data scientist. This practical book reveals new and hidden ways to improve your SQL skills, solve problems, and make the most of SQL as part of your workflow. You'll learn how to use both common and exotic SQL functions such as joins, window functions, subqueries, and regular expressions in new, innovative ways--as well as how to combine SQL techniques to accomplish your goals faster, with understandable code. If you work with SQL databases, this is a must-have reference. Learn the key steps for preparing your data for analysis Perform time series analysis using SQL's date and time manipulations Use cohort analysis to investigate how groups change over time Use SQL's powerful functions and operators for text analysis Detect outliers in your data and replace them with alternate values Establish causality using experiment analysis, also known as A/B testing

Author: Saumyadipta Pyne
Publisher: Springer
ISBN: 8132236289
Category : Computers
Languages : en
Pages : 278

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Book Description
This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.

Author: Walter R. Paczkowski
Publisher: Springer Nature
ISBN: 3030870235
Category : Business & Economics
Languages : en
Pages : 416

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Book Description
This book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems. These are a foundational understanding of: 1. statistical, econometric, and machine learning techniques; 2. data handling capabilities; 3. at least one programming language. Practical in orientation, the volume offers illustrative case studies throughout and examples using Python in the context of Jupyter notebooks. Covered topics include demand measurement and forecasting, predictive modeling, pricing analytics, customer satisfaction assessment, market and advertising research, and new product development and research. This volume will be useful to business data analysts, data scientists, and market research professionals, as well as aspiring practitioners in business data analytics. It can also be used in colleges and universities offering courses and certifications in business data analytics, data science, and market research.

Author: Kenneth C. Laudon
Publisher: Pearson Educación
ISBN: 9789702605287
Category : Business & Economics
Languages : en
Pages : 618

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Book Description
Management Information Systems provides comprehensive and integrative coverage of essential new technologies, information system applications, and their impact on business models and managerial decision-making in an exciting and interactive manner. The twelfth edition focuses on the major changes that have been made in information technology over the past two years, and includes new opening, closing, and Interactive Session cases.

Author: Nancy Burns
Publisher: Elsevier España
ISBN: 9788481747201
Category : Medical
Languages : en
Pages : 582

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Book Description
This leading texbook of nursig research, written by two of the most renowned experts in the field, is now published in full-colour, and this, the 4th edition has now been updated throughout to reflect today's evidence-based practice.

Author: John E. Hanke
Publisher: Pearson Educación
ISBN: 9789702607595
Category : Business & Economics
Languages : en
Pages : 544

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Book Description
This top-selling book presents, in a straightforward, application-driven manner, the basic statistical techniques necessary for preparing individual business forecasts and long-range plans. The emphasis is on the application of techniques by management for decision-making. This essential book provides understandable coverage of several important topics, often omitted from other books, including econometrics; autocorrelation analysis and the use of Box-Jenkins techniques; judgmental forecasting techniques; and the means of selecting the correct forecasting technique and analyzing data. The book also reviews statistical concepts prior to introducing material that requires an understanding of those concepts. The sixth edition of Business Forecasting has been revised to include instructions on using Excel spreadsheets and the statistical package MINITAB in forecasting. An essential reference for every professional in a business of any size, from large corporations to small family-run firms.

Author: Andrew Gelman
Publisher: CRC Press
ISBN: 1439840954
Category : Mathematics
Languages : en
Pages : 677

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Book Description
Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

Author: Christian Heumann
Publisher: Springer Nature
ISBN: 3031118332
Category : Mathematics
Languages : en
Pages : 584

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Book Description
Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference. The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications.