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Books > Computing & IT > Applications of computing > Databases
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Data Wrangling with R (Paperback, 1st ed. 2016)
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Data Wrangling with R (Paperback, 1st ed. 2016)
Series: Use R!
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This guide for practicing statisticians, data scientists, and R
users and programmers will teach the essentials of preprocessing:
data leveraging the R programming language to easily and quickly
turn noisy data into usable pieces of information. Data wrangling,
which is also commonly referred to as data munging, transformation,
manipulation, janitor work, etc., can be a painstakingly laborious
process. Roughly 80% of data analysis is spent on cleaning and
preparing data; however, being a prerequisite to the rest of the
data analysis workflow (visualization, analysis, reporting), it is
essential that one become fluent and efficient in data wrangling
techniques. This book will guide the user through the data
wrangling process via a step-by-step tutorial approach and provide
a solid foundation for working with data in R. The author's goal is
to teach the user how to easily wrangle data in order to spend more
time on understanding the content of the data. By the end of the
book, the user will have learned: How to work with different types
of data such as numerics, characters, regular expressions, factors,
and dates The difference between different data structures and how
to create, add additional components to, and subset each data
structure How to acquire and parse data from locations previously
inaccessible How to develop functions and use loop control
structures to reduce code redundancy How to use pipe operators to
simplify code and make it more readable How to reshape the layout
of data and manipulate, summarize, and join data sets
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