Data Cleaning Pocket Primer
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Data Cleaning Pocket Primer
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Author : Oswald Campesato
language : en
Publisher: Mercury Learning and Information
Release Date : 2018-01-16
Data Cleaning Pocket Primer written by Oswald Campesato and has been published by Mercury Learning and Information this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-16 with Computers categories.
As part of the best selling Pocket Primer series, this book is an effort to give programmers sufficient knowledge of data cleaning to be able to work on their own projects. It is designed as a practical introduction to using flexible, powerful (and free) Unix / Linux shell commands to perform common data cleaning tasks. The book is packed with realistic examples and numerous commands that illustrate both the syntax and how the commands work together. Companion files with source code are available for downloading from the publisher. Features: - A practical introduction to using flexible, powerful (and free) Unix / Linux shell commands to perform common data cleaning tasks - Includes the concept of piping data between commands, regular expression substitution, and the sed and awk commands - Packed with realistic examples and numerous commands that illustrate both the syntax and how the commands work together - Assumes the reader has no prior experience, but the topic is covered comprehensively enough to teach a pro some new tricks - Includes companion files with all of the source code examples (download from the publisher).
Dealing With Data Pocket Primer
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Author : Oswald Campesato
language : en
Publisher: Mercury Learning and Information
Release Date : 2022-05-04
Dealing With Data Pocket Primer written by Oswald Campesato and has been published by Mercury Learning and Information this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-04 with Computers categories.
As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of managing data using a variety of computer languages and applications. It is intended to be a fast-paced introduction to some basic features of data management and covers statistical concepts, data-related techniques, features of Pandas, RDBMS, SQL, NLP topics, Matplotlib, and data visualization. Companion files with source code and color figures are available. FEATURES: Covers Pandas, RDBMS, NLP, data cleaning, SQL, and data visualization Introduces probability and statistical concepts Features numerous code samples throughout Includes companion files with source code and figures
Python 3 And Data Analytics Pocket Primer
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Author : Oswald Campesato
language : en
Publisher: Mercury Learning and Information
Release Date : 2021-03-19
Python 3 And Data Analytics Pocket Primer written by Oswald Campesato and has been published by Mercury Learning and Information this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-19 with Computers categories.
As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of data analytics using Python 3. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, and data cleaning. The book includes numerous code samples using NumPy, Pandas, Matplotlib, Seaborn, and features an appendix on regular expressions. Companion files with source code and color figures are available online by emailing the publisher with proof of purchase at [email protected]. FEATURES: Includes a concise introduction to Python 3 Provides a thorough introduction to data and data cleaning Covers NumPy and Pandas Introduces statistical concepts and data visualization (Matplotlib/Seaborn) Features an appendix on regular expressions Includes companion files with source code and figures
Python Tools For Data Scientists Pocket Primer
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Author : Oswald Campesato
language : en
Publisher: Mercury Learning and Information
Release Date : 2022-10-21
Python Tools For Data Scientists Pocket Primer written by Oswald Campesato and has been published by Mercury Learning and Information this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-21 with Computers categories.
As part of the best-selling Pocket Primer series, this book is designed to provide a thorough introduction to numerous Python tools for data scientists. The book covers features of NumPy and Pandas, how to write regular expressions, and how to perform data cleaning tasks. It includes separate chapters on data visualization and working with Sklearn and SciPy. Companion files with source code are available. FEATURES: Introduces Python, NumPy, Sklearn, SciPy, and awk Covers data cleaning tasks and data visualization Features numerous code samples throughout Includes companion files with source code
Practical Data Cleaning
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Author : Lee Baker
language : en
Publisher: Lee Baker
Release Date : 2019-01-30
Practical Data Cleaning written by Lee Baker and has been published by Lee Baker this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-30 with Education categories.
Data cleaning is a waste of time. If the data had been collected properly in the first place there wouldn’t be any cleaning to do, and you wouldn’t now be faced with the prospect of weeks of cleaning to get your dataset analysis-ready. Worse still, your boss won’t understand why your analysis report isn’t on his desk yet, a mere 48 hours after he’s asked for it. Bless him, he doesn’t understand – he thinks that cleaning data is just about clicking a few buttons in Excel and – ta da! – it’s all done. Even a monkey can do that, right? And – for good reason – you won’t get any help from statistics books either. Data is messy and cleaning it can be difficult, time-consuming and costly. Not to mention it’s the least sexy thing you can do with a dataset. Yet you’ve still got to do it, because, well, someone has to… But it doesn’t have to be so difficult. If you're organised and follow a few simple rules your data cleaning processes can be simple, fast and effective. Not to mention fun! Well, not fun exactly, just not quite as coma-inducing. Practical Data Cleaning (now in its 5th Edition!) explains the 19 most important tips about data cleaning with a focus on understanding your data, how to work with it, choose the right ways to analyse it, select the correct tools and how to interpret the results to get your data clean in double quick time. Best of all, there is no technical jargon – it is written in plain English and is perfect for beginners! Discover how to clean your data quickly and effectively. Get this book, TODAY!
Data Cleaning
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Author : Ihab F. Ilyas
language : en
Publisher: Morgan & Claypool
Release Date : 2019-06-18
Data Cleaning written by Ihab F. Ilyas and has been published by Morgan & Claypool this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-18 with Computers categories.
Data quality is one of the most important problems in data management, since dirty data often leads to inaccurate data analytics results and incorrect business decisions. Poor data across businesses and the U.S. government are reported to cost trillions of dollars a year. Multiple surveys show that dirty data is the most common barrier faced by data scientists. Not surprisingly, developing effective and efficient data cleaning solutions is challenging and is rife with deep theoretical and engineering problems. This book is about data cleaning, which is used to refer to all kinds of tasks and activities to detect and repair errors in the data. Rather than focus on a particular data cleaning task, we give an overview of the end-to-end data cleaning process, describing various error detection and repair methods, and attempt to anchor these proposals with multiple taxonomies and views. Specifically, we cover four of the most common and important data cleaning tasks, namely, outlier detection, data transformation, error repair (including imputing missing values), and data deduplication. Furthermore, due to the increasing popularity and applicability of machine learning techniques, we include a chapter that specifically explores how machine learning techniques are used for data cleaning, and how data cleaning is used to improve machine learning models. This book is intended to serve as a useful reference for researchers and practitioners who are interested in the area of data quality and data cleaning. It can also be used as a textbook for a graduate course. Although we aim at covering state-of-the-art algorithms and techniques, we recognize that data cleaning is still an active field of research and therefore provide future directions of research whenever appropriate.
Natural Language Processing Using R Pocket Primer
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Author : Oswald Campesato
language : en
Publisher: Stylus Publishing, LLC
Release Date : 2022-01-05
Natural Language Processing Using R Pocket Primer written by Oswald Campesato and has been published by Stylus Publishing, LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-05 with Computers categories.
This book is for developers who are looking for an overview of basic concepts in Natural Language Processing using R. It casts a wide net of techniques to help developers who have a range of technical backgrounds. Numerous code samples and listings are included to support myriad topics. The final chapter presents the Transformer Architecture, BERT-based models, and the GPT family of models, all of which were developed during the past three years. Companion files with source code and figures are included and available for downloading by emailing the publisher at [email protected] with proof of purchase. FEATURES: Covers extensive topics related to natural language processing using R Features companion files with source code and figures from the book
Python Data Cleaning Cookbook
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Author : Michael Walker
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-12-11
Python Data Cleaning Cookbook written by Michael Walker 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 2020-12-11 with Computers categories.
Discover how to describe your data in detail, identify data issues, and find out how to solve them using commonly used techniques and tips and tricks Key FeaturesGet well-versed with various data cleaning techniques to reveal key insightsManipulate data of different complexities to shape them into the right form as per your business needsClean, monitor, and validate large data volumes to diagnose problems before moving on to data analysisBook Description Getting clean data to reveal insights is essential, as directly jumping into data analysis without proper data cleaning may lead to incorrect results. This book shows you tools and techniques that you can apply to clean and handle data with Python. You'll begin by getting familiar with the shape of data by using practices that can be deployed routinely with most data sources. Then, the book teaches you how to manipulate data to get it into a useful form. You'll also learn how to filter and summarize data to gain insights and better understand what makes sense and what does not, along with discovering how to operate on data to address the issues you've identified. Moving on, you'll perform key tasks, such as handling missing values, validating errors, removing duplicate data, monitoring high volumes of data, and handling outliers and invalid dates. Next, you'll cover recipes on using supervised learning and Naive Bayes analysis to identify unexpected values and classification errors, and generate visualizations for exploratory data analysis (EDA) to visualize unexpected values. Finally, you'll build functions and classes that you can reuse without modification when you have new data. By the end of this Python book, you'll be equipped with all the key skills that you need to clean data and diagnose problems within it. What you will learnFind out how to read and analyze data from a variety of sourcesProduce summaries of the attributes of data frames, columns, and rowsFilter data and select columns of interest that satisfy given criteriaAddress messy data issues, including working with dates and missing valuesImprove your productivity in Python pandas by using method chainingUse visualizations to gain additional insights and identify potential data issuesEnhance your ability to learn what is going on in your dataBuild user-defined functions and classes to automate data cleaningWho this book is for This book is for anyone looking for ways to handle messy, duplicate, and poor data using different Python tools and techniques. The book takes a recipe-based approach to help you to learn how to clean and manage data. Working knowledge of Python programming is all you need to get the most out of the book.
Python For Tensorflow Pocket Primer
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Author : Oswald Campesato
language : en
Publisher: Mercury Learning and Information
Release Date : 2019-05-09
Python For Tensorflow Pocket Primer written by Oswald Campesato and has been published by Mercury Learning and Information this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-09 with Computers categories.
As part of the best-selling Pocket Primer series, this book is designed to prepare programmers for machine learning and deep learning/TensorFlow topics. It begins with a quick introduction to Python, followed by chapters that discuss NumPy, Pandas, Matplotlib, and scikit-learn. The final two chapters contain an assortment of TensorFlow 1.x code samples, including detailed code samples for TensorFlow Dataset (which is used heavily in TensorFlow 2 as well). A TensorFlow Dataset refers to the classes in the tf.data.Dataset namespace that enables programmers to construct a pipeline of data by means of method chaining so-called lazy operators, e.g., map(), filter(), batch(), and so forth, based on data from one or more data sources. Companion files with source code are available for downloading from the publisher by writing [email protected]. Features: A practical introduction to Python, NumPy, Pandas, Matplotlib, and introductory aspects of TensorFlow 1.x Contains relevant NumPy/Pandas code samples that are typical in machine learning topics, and also useful TensorFlow 1.x code samples for deep learning/TensorFlow topics Includes many examples of TensorFlow Dataset APIs with lazy operators, e.g., map(), filter(), batch(), take() and also method chaining such operators Assumes the reader has very limited experience Companion files with all of the source code examples (download from the publisher)
Data Science Fundamentals Pocket Primer
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Author : Oswald Campesato
language : en
Publisher: Mercury Learning and Information
Release Date : 2021-05-12
Data Science Fundamentals Pocket Primer written by Oswald Campesato and has been published by Mercury Learning and Information this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-12 with Computers categories.
As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of data science using Python 3 and other computer applications. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, linear algebra, and regular expressions. The book includes numerous code samples using Python, NumPy, R, SQL, NoSQL, and Pandas. Companion files with source code and color figures are available. FEATURES: Includes a concise introduction to Python 3 and linear algebra Provides a thorough introduction to data visualization and regular expressions Covers NumPy, Pandas, R, and SQL Introduces probability and statistical concepts Features numerous code samples throughout Companion files with source code and figures