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Hands-On Data Preprocessing in Python: Learn how to effectively prepare data for successful data analytics
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Hands-On Data Preprocessing in Python: Learn how to effectively prepare data for successful data analytics
Hands-On Data Preprocessing in Python: Learn how to effectively prepare data for successful data analytics
Hands-On Data Preprocessing in Python: Learn how to effectively prepare data for successful data analytics
제품번호 #: 47170266

Hands-On Data Preprocessing in Python: Learn how to effectively prepare data for successful data analytics

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제품번호 #: 47170266

KRW 118925

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Master the art of effectively preparing data for successful data analytics with our hands-on Python tutorials. Dive deep into data preprocessing techniques today! Shop at Ubuy South Korea
  • Get your raw data cleaned up and ready for processing to design better data analytic solutionsKey FeaturesDevelop the skills to perform data cleaning, data integration, data reduction, and data transformationMake the most of your raw data with powerful data transformation and massaging techniquesPerform thorough data cleaning, including dealing with missing values and outliersBook DescriptionHands-On Data Preprocessing is a primer on the best data cleaning and preprocessing techniques, written by an expert who's developed college-level courses on data preprocessing and related subjects. With this book, you'll be equipped with the optimum data preprocessing techniques from multiple perspectives, ensuring that you get the best possible insights from your data. You'll learn about different technical and analytical aspects of data preprocessing – data collection, data cleaning, data integration, data reduction, and data transformation – and get to grips with implementing them using the open source Python programming environment. The hands-on examples and easy-to-follow chapters will help you gain a comprehensive articulation of data preprocessing, its whys and hows, and identify opportunities where data analytics could lead to more effective decision making. As you progress through the chapters, you'll also understand the role of data management systems and technologies for effective analytics and how to use APIs to pull data.By the end of this Python data preprocessing book, you'll be able to use Python to read, manipulate, and analyze data; perform data cleaning, integration, reduction, and transformation techniques, and handle outliers or missing values to effectively prepare data for analytic tools.What you will learnUse Python to perform analytics functions on your dataUnderstand the role of databases and how to effectively pull data from databasesPerform data preprocessing steps defined by your analytics goalsRecognize and resolve data integration challengesIdentify the need for data reduction and execute itDetect opportunities to improve analytics with data transformationWho this book is forThis book is for junior and senior data analysts, business intelligence professionals, engineering undergraduates, and data enthusiasts looking to perform preprocessing and data cleaning on large amounts of data. You don't need any prior experience with data preprocessing to get started with this book. However, basic programming skills, such as working with variables, conditionals, and loops, along with beginner-level knowledge of Python and simple analytics experience, are a prerequisite.Table of ContentsReview of the Core Modules of NumPy and PandasReview of Another Core Module - MatplotlibData – What Is It Really?DatabasesData VisualizationPredictionClassificationClustering AnalysisData Cleaning Level I - Cleaning Up the TableData Cleaning Level II - Unpacking, Restructuring, and Reformulating the TableData Cleaning Level III- Missing Values, Outliers, and ErrorsData Fusion and Data IntegrationData ReductionData Transformation and MassagingCase Study 1 - Mental Health in TechCase Study 2 - Predicting COVID-19 HospitalizationsCase Study 3: United States Counties Clustering AnalysisSummary, Practice Case Studies, and Conclusions
Publisher Packt Publishing
Publication date January 21, 2022
Language English
Print length 602 pages
ISBN-10 1801072132
ISBN-13 978-1801072137
Item Weight 2.25 pounds (1.02 kg)
Dimensions 7.5 x 1.36 x 9.25 inches (19.1 x 3.5 x 23.5 cm)

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Hands-On Data Preprocessing in Python: Learn how to effectively prepare data for successful data analytics

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