Описание: This book presents an introductory overview of spatial data analysis methods and geoinformation analysis techniques. Each chapter introduces the related theory, explains how to interpret metrics outputs, and provides worked examples using ArcGIS and GeoDa. This is a valuable resource for graduate students and researchers analyzing geospatial data.
Автор: Titscher S et al Название: Methods of Text and Discourse Analysis ISBN: 0761964835 ISBN-13(EAN): 9780761964834 Издательство: Sage Publications Рейтинг: Цена: 9346.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An overview of linguistic and sociological approaches to text and discourse analysis.
Jump-start your career as a data scientist--learn to develop datasets for exploration, analysis, and machine learning
SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that's dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls.
You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data.
This guide for data scientists differs from other instructional guides on the subject. It doesn't cover SQL broadly. Instead, you'll learn the subset of SQL skills that data analysts and data scientists use frequently. You'll also gain practical advice and direction on "how to think about constructing your dataset."
Gain an understanding of relational database structure, query design, and SQL syntax
Develop queries to construct datasets for use in applications like interactive reports and machine learning algorithms
Review strategies and approaches so you can design analytical datasets
Practice your techniques with the provided database and SQL code
In this book, author Renee Teate shares knowledge gained during a 15-year career working with data, in roles ranging from database developer to data analyst to data scientist. She guides you through SQL code and dataset design concepts from an industry practitioner's perspective, moving your data scientist career forward
Описание: This book provides a detailed description of the entire study process concerning gathering and analysing big data and making observations to develop a crime-prediction model that utilises its findings.
Автор: Brooker, Phillip Название: Programming with python for social scientists ISBN: 1526431726 ISBN-13(EAN): 9781526431721 Издательство: Sage Publications Рейтинг: Цена: 7602.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Programming with Python for Social Scientists offers a vital foundation to one of the most popular programming tools in computer science, specifically for social science researchers, assuming no prior coding knowledge.
Автор: Brooker, Phillip Название: Programming with python for social scientists ISBN: 1526431718 ISBN-13(EAN): 9781526431714 Издательство: Sage Publications Рейтинг: Цена: 21226.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Programming with Python for Social Scientists offers a vital foundation to one of the most popular programming tools in computer science, specifically for social science researchers, assuming no prior coding knowledge.
Автор: Decaria Alex, Petty Grant W. Название: Python Programming and Visualization for Scientists ISBN: 0972903356 ISBN-13(EAN): 9780972903356 Издательство: Неизвестно Рейтинг: Цена: 10483.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Python continues to gain dominance as a language of choice for analyzing and visualizing scientific data. Although it has concise, intuitive syntax, learning how to plot and visualize data requires scouring the internet for documentation and examples. This book was written from the perspective of "What book would the authors want to have had when they were transitioning to Python?"
A second edition of the book was made necessary by the transition to Python 3, which did not maintain full backward compatibility with earlier versions of the language. The second edition has been completely revised to ensure that all code examples work in Python 3. Additional chapters on the Pandas library and Cartopy have been included, as well as an appendix on Jupyter notebooks, which have become an important tool for developing and communicating code in both the research and educational settings.
The 90 figures are mostly in color, and color syntax highlighting is used with all code samples throughout the text to facilitate visual recognition of program structure.
The first edition of the book has proven useful not only as a classroom text but also as a guide and reference for students, educators, and researchers who already have programming experience and want to start creating plots and analyzing data using Python. The second edition will serve the same role. It is not meant for the person who is completely new to programming, nor is it an introductory computer science textbook. The authors' assumptions are that the reader has some experience programming with a language other than Python.
Although the new Python programmer may wish to read the book cover to cover, the book is organized such that an experienced programmer can readily jump to the appropriate chapter. An extensive index aids in searching for functions and methods useful for data visualization and analysis.
Описание: Discusses the issues that the agricultural industry currently faces and the technological opportunities that can be explored to help protect and predict crop growth and achieve more resilient agricultural processes. The book analyses the impact of agricultural pollution and food insecurity and proposes solutions to promote sustainability.
Название: Learn Data Analysis with Python ISBN: 1484234855 ISBN-13(EAN): 9781484234853 Издательство: Springer Рейтинг: Цена: 6288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Table of Contents 1. IntroductionHow to use this bookInstalling iPython NotebookWhat is iPython notebook?What is Anaconda?Getting StartedGetting the datasets for the workbook's exercises2. Getting Data into and out of PythonLoading Data from CSV FilesSaving Data to CSVLoading Data from Excel FilesSaving Data to Excel FilesCombining Data from Multiple Excel Files: Loading Data from SQLSaving Data to SQLRandom Numbers and Creating Random Data3. Preparing Data is Half the BattleCleaning DataCalculating and Removing OutliersMissing Data in Pandas DataframesFiltering Inappropriate ValuesFinding Duplicate RowsRemoving Punctuation from Column ContentsRemoving Whitespace from Column ContentsStandardizing DatesStandardizing Text like SSN's, Phone #'s and Zip CodesCreating New VariablesBinning DataApplying Function to Groups, Bins and ColumnsRanking Rows of DataCreate a Column Based on a ConditionalMaking New Columns Using FunctionsConverting String Categories to Numeric VariablesOrganizing the DataRemoving and Adding ColumnsSelecting ColumnsChange Column NameSetting Column Names to Lower CaseFinding Matching RowsFilter Rows Based on Conditions: Selecting Rows Based on ConditionsRandom Sampling Dataframe4. Finding the MeaningComputing aggregate statisticsComputing Aggregate Statistics on Matching RowsSorting DataCorrelationRegressionRegression without InterceptBasic Pivot TableRandom Sampling DataframeSelecting Pandas DataFrame Rows Based on ConditionsDistribution AnalysisCategorical Variable AnalysisTime Series Analysis5. Visualizing DataData Quality ReportGraph a Dataset - Line PlotGraph a Dataset - Bar PlotGraph a Dataset - Box PlotGraph a Dataset - HistogramGraph a Dataset - Pie ChartGraph a Dataset - Scatter PlotPlotting w/ ImagePlotting Data on a Map with BasemapPlotting a Gantt ChartSetting ticks, labels & gridsAdding legends & annotationsMoving Spines to the Center6. Practice ProblemsPivot Exercise 1Pivot Exercise 2Pivot Exercise 2Pivot Exercise 3LegendRegression Exercise 1Regression Exercise 2Regression Exercise 3Analysis ProjectNotes
Автор: Kumar Mukhiya Suresh, Ahmed Usman Название: Hands-On Exploratory Data Analysis with Python ISBN: 1789537258 ISBN-13(EAN): 9781789537253 Издательство: Неизвестно Рейтинг: Цена: 14712.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides practical knowledge about the main pillars of EDA including data cleaning, data preparation, data exploration, and data visualization. You can leverage the power of Python to understand, summarize and investigate your data in the best way possible. The book presents a unique approach to exploring hidden features in your data.
Описание: Looking for methods that you can use to make yourself more competitive in your industry? Or are you worried about what your customers may think about your products or services?
The truth is...In the modern world, data has become fundamental, and companies are finding new ways to use the insights provided by data to improve their bottom line and customer experience. This is sometimes a challenge. There is so much data that figuring out what steps to take, and what is found in that data is not always as easy as we would like.
The good news is that working with data science can help you learn more about your customers and your industry, with the use of a simple coding language, and give you the insights and predictions that you need to see some great improvements with your business. And that's what you'll learn in Python for Data Science.
Python for Data Science is going to spend some time looking at all of the neat things that we can do with data science, so you can finally beat out the competition and increase your bottom line, all while helping out the customer.
You will learn:
Why Data Science is so Important in our Fast-Paced World of Today
5 Practical Applications of Data Science
Best Data Science Library that will help us to Get our Work Done with Python
A Simple Technique to Set Up our Virtual Environment
Proven Strategies to Get High-Quality Data
Tips and Tricks to Get your Data Organized
Data Analytics and Why It is so Important
What Machine Learning is all About and How it Fit into your Data Science Projects
Learning how data science works and how to complete your own data analysis in the process is going to be very important to the amount of success that you are going to see.
Even if you're completely new to data science or you've done some programming before and are looking to switch to an exciting new career track in Data Science, Python for Data Science will teach you all the practical techniques used by real-world data scientists and analysts to solve problems.
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