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A Data Scientist's Guide to Acquiring, Cleaning and Managing Data in R

The only how-to guide offering a unified, systemic approach to acquiring, cleaning, and managing data in R Every experienced practitioner;

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Clean Data

If you are a data scientist of any level, beginners included, and interested in cleaning up your data, this is the book for you! Experience;

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Hands-On Data Science with R

with Spark and Hadoop for large-scale data analytics Who this book is forIf you are a budding data scientist keen to learn about the popular;

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Mastering Data Analysis With R

scientist or R developer who wants to explore and optimize your use of R's advanced features and tools, this is the book for you. A basic knowledge;

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Data Science

Data Science: An Introduction focuses on using the R programming language in Jupyter notebooks to perform basic data manipulation and;

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Data Wrangling with R

analysis is spent on cleaning and preparing data; however, being a prerequisite to the rest of the data analysis workflow (visualization, analysis;

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Data Cleaning

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;

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Data Cleaning

to serve as a useful reference for researchers and practitioners who are interested in the area of data quality and data cleaning. It can;

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Data Science From Scratch: The #1 Data Science Guide For Everything A Data Scientist Needs To Know

science is and why it is important.The prerequisites you will need to get started in data science.What it means to be a data scientist;

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Machine Learning and Data Science

A practitioner’s tools have a direct impact on the success of his or her work. This book will provide the data scientist with the tools and;

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Introduction to Data Science for Social and Policy Research

into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming;

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Introduction to Data Science for Social and Policy Research

into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming;

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Data Cleaning

business decisions. Errors in data tend to creep in for a variety of reasons. Some of these reasons include errors during input data collection and;

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Graphical Data Analysis with R

book focuses on why you draw graphics to display data and which graphics to draw (and uses R to do so). All the datasets are available in R or;

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Graphical Data Analysis with R

book focuses on why you draw graphics to display data and which graphics to draw (and uses R to do so). All the datasets are available in R or;

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Delivering Business Analytics

* The Data Scientist s Code, fifteen management principles that when followed help teams move towards best practice * Practical solutions and;

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Practical Data Science Cookbook -

various data science concepts such as acquisition, cleaning and munging through R and Python * Build a predictive model and an exploratory model;

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SQL for Data Scientists - A Beginner's Guide for Building Datasets for Analysis

Jump-start your career as a data scientist-learn to develop datasets for exploration, analysis, and machine learning SQL for Data;

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A Beginner's Guide to Microarrays

A Beginner's Guide to Microarrays addresses two audiences - the core facility manager who produces, hybridizes, and scans arrays, and the;

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Practical Data Wrangling

reporting. Python and R are considered a popular choice of tool for data analysis, and have packages that can be best used to manipulate different;

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Learning Predictive Analytics with R

Get to grips with key data visualization and predictive analytic skills using R About This Book * Acquire predictive analytic skills;

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Cleaning Data for Effective Data Science

resource, arming you with the insights and heuristics experienced data scientists had to learn the hard way. In a light-hearted and engaging;

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Mathematical Foundations of Data Science Using R

worldwide importance. The book gives the mathematical foundations to handle data properly. It introduces basics and functionalities of the R;

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Data Science From Scratch: The #1 Data Science Guide For Everything A Data Scientist Needs To Know

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Plant Molecular Biology Labfax

Labfax is a unique single source of reference to key data and information required by the plant molecular biologist on an almost daily basis. A;

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R In Finance And Economics

reproducible research examples. It will enable students to use R for data cleaning, data visualization and quantitative model building using;

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R and Data Mining

R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for;

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