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Books > Computing & IT > Applications of computing > Databases > Data capture & analysis
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Practical Data Wrangling (Paperback)
Loot Price: R816
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Practical Data Wrangling (Paperback)
Expected to ship within 18 - 22 working days
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Turn your noisy data into relevant, insight-ready information by
leveraging the data wrangling techniques in Python and R About This
Book * This easy-to-follow guide takes you through every step of
the data wrangling process in the best possible way * Work with
different types of datasets, and reshape the layout of your data to
make it easier for analysis * Get simple examples and real-life
data wrangling solutions for data pre-processing Who This Book Is
For If you are a data scientist, data analyst, or a statistician
who wants to learn how to wrangle your data for analysis in the
best possible manner, this book is for you. As this book covers
both R and Python, some understanding of them will be beneficial.
What You Will Learn * Read a csv file into python and R, and print
out some statistics on the data * Gain knowledge of the data
formats and programming structures involved in retrieving API data
* Make effective use of regular expressions in the data wrangling
process * Explore the tools and packages available to prepare
numerical data for analysis * Find out how to have better control
over manipulating the structure of the data * Create a dexterity to
programmatically read, audit, correct, and shape data * Write and
complete programs to take in, format, and output data sets In
Detail Around 80% of time in data analysis is spent on cleaning and
preparing data for analysis. This is, however, an important task,
and is a prerequisite to the rest of the data analysis workflow,
including visualization, analysis and 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 kinds of
data, as per your requirements. This book will show you the
different data wrangling techniques, and how you can leverage the
power of Python and R packages to implement them. You'll start by
understanding the data wrangling process and get a solid foundation
to work with different types of data. You'll work with different
data structures and acquire and parse data from various locations.
You'll also see how to reshape the layout of data and manipulate,
summarize, and join data sets. Finally, we conclude with a quick
primer on accessing and processing data from databases, conducting
data exploration, and storing and retrieving data quickly using
databases. The book includes practical examples on each of these
points using simple and real-world data sets to give you an easier
understanding. By the end of the book, you'll have a thorough
understanding of all the data wrangling concepts and how to
implement them in the best possible way. Style and approach This is
a practical book on data wrangling designed to give you an insight
into the practical application of data wrangling. It takes you
through complex concepts and tasks in an accessible way, featuring
information on a wide range of data wrangling techniques with
Python and R.
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