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LEADER 00000uam a2200397 a 4500 
003    CaSebORM 
005    20200110005156.2 
006    m     o  d         
007    cr cn          
008    171117s2017    xx      o           eng   
024 8  9781787286139 
035    (CaSebORM)9781787286139 
041 0  eng 
100 1  Visochek, Allan,|eauthor. 
245 10 Practical Data Wrangling|h[O'Reilly electronic resource] /
       |cVisochek, Allan. 
250    1st edition 
264  1 |bPackt Publishing,|c2017. 
300    1 online resource (204 pages) 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
347    text file 
365    |b29.99 
520    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 en... 
533    Electronic reproduction.|bBoston, MA :|cSafari,|nAvailable
       via World Wide Web.|d2017. 
538    Mode of access: World Wide Web. 
542    |fCopyright © Packt Publishing|g2017 
550    Made available through: Safari, an O’Reilly Media Company.
588 00 Online resource; Title from title page (viewed November 15,
655  7 Electronic books.|2local 
710 2  Safari, an O’Reilly Media Company. 
856 40 |zConnect to this resource online|uhttps://