Analiza danych
Analiza danych jest ekscytującą dyscypliną, która umożliwia zrozumienie pewnych zjawisk, uzyskanie wglądu i wiedzy na podstawie surowych danych. Pojęcie to oznacza dokładnie przetwarzanie danych za pomocą technik matematycznych i statystycznych w celu uzyskania cennych wniosków, podjęcia ważnych decyzji i opracowania przydatnych produktów. Termin ten wywodzi się od angielskiego data science, często traktowanego jako synonim takich terminów, jak analityka biznesowa, badania operacyjne, business intelligence, wywiad konkurencyjny, analiza i modelowanie danych, a także pozyskiwanie wiedzy. Dzięki takim technologiom, jak języki Python czy R, platformy Hadoop i Spark masz szansę wyciągnąć maksimum wniosków, dostrzec szanse na rozwój swojej organizacji albo przewidzieć i zapobiec zagrożeniom.
MrExcel's Holy Macro! Books, Mike Girvin
Excel users often encounter limitations with standard formulas, but the Ctrl+Shift+Enter technique changes everything. This book is your gateway to mastering Excel array formulas, revealing their potential to solve complex problems effortlessly. You'll start with the basics, understand the fundamental concepts of array formulas, and gradually progress to advanced applications, including mathematical operations, comparative calculations, and dynamic ranges.Each chapter is crafted to build your confidence and expertise. From performing array operations that manipulate large datasets efficiently to utilizing advanced functions like SUMPRODUCT and AGGREGATE, you will learn how to apply these tools to real-world scenarios. The guide also covers the creation of dynamic ranges with INDEX and OFFSET, ensuring your formulas remain flexible and powerful even as your data changes.By the end of the book, you'll not only understand the theoretical aspects of array formulas but also possess the practical skills to implement them effectively. Whether you're creating complex financial models, conducting detailed data analysis, or automating routine tasks, this guide equips you with the knowledge to transform your Excel capabilities and achieve more with less effort.
D3.js 4.x Data Visualization. Learn to visualize your data with JavaScript - Third Edition
Aendrew Rininsland , Swizec Teller
Want to get started with impressive interactive visualizations and implement them in your daily tasks? This book offers the perfect solution-D3.js. It has emerged as the most popular tool for data visualization. This book will teach you how to implement the features of the latest version of D3 while writing JavaScript using the newest tools and techniqueYou will start by setting up the D3 environment and making your first basic bar chart. You will then build stunning SVG and Canvas-based data visualizations while writing testable, extensible code,as accurate and informative as it is visually stimulating. Step-by-step examples walk you through creating, integrating, and debugging different types of visualization and will have you building basic visualizations (such as bar, line, and scatter graphs) in no time.By the end of this book, you will have mastered the techniques necessary to successfully visualize data and will be ready to use D3 to transform any data into an engaging and sophisticated visualization.
D3.js Quick Start Guide. Create amazing, interactive visualizations in the browser with JavaScript
Matthew Huntington
D3.js is a JavaScript library that allows you to create graphs and data visualizations in the browser with HTML, SVG, and CSS. This book will take you from the basics of D3.js, so that you can create your own interactive visualizations, to creating the most common graphs that you will encounter as a developer, scientist, statistician, or data scientist.The book begins with an overview of SVG, the basis for creating two-dimensional graphics in the browser. Once the reader has a firm understanding of SVG, we will tackle the basics of how to use D3.js to connect data to our SVG elements. We will start with a scatter plot that maps run data to circles on a graph, and expand our scatter plot to make it interactive. You will see how you can easily allow the users of your graph to create, edit, and delete run data by simply dragging and clicking the graph. Next, we will explore creating a bar graph, using external data from a mock API.After that, we will explore animations and motion with a bar graph, and use various physics-based forces to create a force-directed graph. Finally, we will look at how to use GeoJSON data to create a map.
Dane grafowe w praktyce. Jak technologie grafowe ułatwiają rozwiązywanie złożonych problemów
Denise Gosnell, Matthias Broecheler
Komputer do pracy potrzebuje liczb i danych. Człowiek chętniej wysnuwa wnioski i wyodrębnia kontekst na podstawie relacji. Te dwa sposoby myślenia są tak odmienne, że komputery do niedawna z trudem wykonywały zadania związane z operowaniem na relacjach. Obecnie może się to zmienić dzięki grafom. Technologie grafowe łączą ludzkie postrzeganie świata i liniową pamięć komputerów. Ich wdrożenie na szerszą skalę będzie stanowić przełom i pozwoli osiągnąć nieznany dziś poziom. Ale najpierw trzeba nauczyć się stosować myślenie grafowe w rozwiązywaniu problemów technicznych. Dzięki tej książce opanujesz podstawy myślenia grafowego. Zapoznasz się z elementarnymi koncepcjami grafowymi: teorią grafów, schematami baz danych, systemami rozproszonymi, a także analizą danych. Dowiesz się również, jak wyglądają typowe wzorce wykorzystania danych grafowych w aplikacjach produkcyjnych. Poznasz sposób, w jaki można te wzorce stosować w praktyce. Pokazano tu, jak używać technik programowania funkcyjnego oraz systemów rozproszonych do tworzenia zapytań i analizowania danych grafowych. Opisano też podstawowe podejścia do proceduralnego przechodzenia przez dane grafowe i ich wykorzystanie za pomocą narzędzi grafowych. W książce: nowy paradygmat rozwiązywania problemów: dane grafowe wzorce wykorzystania danych grafowych przykładowa architektura aplikacji w technologiach relacyjnych i grafowych technologie grafowe a przewidywanie preferencji i zaufania użytkowników filtrowanie kolaboratywne i jego zastosowanie Grafy: przełomowa koncepcja w analizie danych!
David Rojas
Excel 2013 is one of the easiest to use data analysis tools you will ever come across. Its simplicity and powerful features has made it the go to tool for all your data needs. Complex operations with Excel, such as creating charts and graphs, visualization, and analyzing data make it a great tool for managers, data scientists, financial data analysts, and those who work closely with data. Learning data analysis and will help you bring your data skills to the next level.This book starts by walking you through creating your own data and bringing data into Excel from various sources. You’ll learn the basics of SQL syntax and how to connect it to a Microsoft SQL Server Database using Excel’s data connection tools. You will discover how to spot bad data and strategies to clean that data to make it useful to you. Next, you'll learn to create custom columns, identify key metrics, and make decisions based on business rules. You’ll create macros using VBA and use Excel 2013’s shiny new macros. Finally, at the end of the book, you'll be provided with useful shortcuts and tips, enabling you to do efficient data analysis and business modeling with Excel 2013.
Data Analysis for Business Decisions. A Laboratory Manual
Mercury Learning and Information, Andres Fortino
This manual is for business analysts to enhance their statistical analysis skills, with case studies focusing mainly on Excel. It covers basic descriptive techniques, linear regression, forecasting, t-Test, chi-square, A/B testing, text data analysis, and Big Data management. Companion files include solution spreadsheets, sample files, and data sets.The course starts with data shaping and cleaning, installing the Analysis ToolPak, and descriptive statistics. It progresses through histograms, scatter plots, Pareto analysis, correlation, linear and multivariate regression, and forecasting. Advanced topics include inferential statistics, contingency analysis, and A/B testing. The final chapters cover text analytics, big data sets, and data visualization.These techniques are crucial for informed business decisions. This book guides users from basic to advanced analysis, blending theory with practical skills. Companion files enhance learning, making this manual essential for mastering statistical analysis in business.
Data Analysis with IBM SPSS Statistics. Implementing data modeling, descriptive statistics and ANOVA
James C. Mott, Ken Stehlik-Barry, James Sugrue,...
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.
Prasad Kothari
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.