LEADER 00000cam a2200481 i 4500 
003    OCoLC 
005    20240129213017.0 
006    m     o  d         
007    cr unu|||||||| 
008    180103s2017    enka    o     000 0 eng d 
020    9781787283671 
020    1787283674 
020    1787286134 
020    9781787286139 
029 1  GBVCP|b1014939585 
035    (OCoLC)1017738649 
037    CL0500000921|bSafari Books Online 
040    UMI|beng|erda|epn|cUMI|dTOH|dSTF|dOCLCF|dCEF|dKSU|dINT
       |dDEBBG|dOCLCQ|dG3B|dS9I|dUAB|dRDF|dVT2|dQGK|dOCLCQ|dOCLCO
       |dOCLCQ|dOCLCO 
049    INap 
082 04 006.312 
082 04 006.312|223 
099    eBook O'Reilly for Public Libraries 
100 1  Visochek, Allan,|eauthor. 
245 10 Practical data wrangling :|bexpert techniques for 
       transforming your raw data into a valuable source for 
       analytics /|cAllan Visochek.|h[O'Reilly electronic 
       resource] 
246 30 Expert techniques for transforming your raw data into a 
       valuable source for analytics 
264  1 Birmingham, UK :|bPackt Publishing,|c2017. 
300    1 online resource (1 volume) :|billustrations 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
347    data file 
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 ... 
588 0  Online resource; title from title page (Safari, viewed 
       December 19, 2017). 
590    O'Reilly|bO'Reilly Online Learning: Academic/Public 
       Library Edition 
650  0 Data mining. 
650  0 Big data. 
650  2 Data Mining 
650  6 Exploration de données (Informatique) 
650  6 Données volumineuses. 
650  7 Big data|2fast 
650  7 Data mining|2fast 
856 40 |uhttps://ezproxy.naperville-lib.org/login?url=https://
       learning.oreilly.com/library/view/~/9781787286139/?ar
       |zAvailable on O'Reilly for Public Libraries 
994    92|bJFN