| Record ID | marc_columbia/Columbia-extract-20221130-027.mrc:104740052:2848 |
| Source | marc_columbia |
| Download Link | /show-records/marc_columbia/Columbia-extract-20221130-027.mrc:104740052:2848?format=raw |
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001 13262648
005 20180618185025.0
008 161003t20182017caua 001 0 eng d
019 $a961160703$a1017088298
020 $a1491957662$qpaperback
020 $a9781491957660$qpaperback
035 $a(OCoLC)ocn959595088
035 $a(OCoLC)959595088$z(OCoLC)961160703$z(OCoLC)1017088298
035 $a(NNC)13262648
040 $aYDX$beng$erda$cYDX$dBDX$dOCLCQ$dBTCTA$dINO$dIUL$dOCLCF$dOCL$dCHVBK$dOCLCO$dEYM$dJRZ$dGL4$dJRZ$dLOY
050 4 $aQA76.73.P98$bM42 2018
082 04 $a005.133$223
100 1 $aMcKinney, Wes,$eauthor.
245 10 $aPython for data analysis :$bdata wrangling with pandas, NumPy, and IPython /$cWes McKinney.
246 30 $aData wrangling with pandas, NumPy, and IPython
250 $aSecond edtiion.
264 1 $aSebastopol, CA :$bO'Reilly Media, Inc.,$cOctober 2018.
264 4 $c©2018.
300 $axvi, 524 pages :$billustrations ;$c24 cm
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
338 $avolume$bnc$2rdacarrier
500 $a"Revision history for the Second Edition: 2017-09-25: First Release"--Title page verso.
500 $aFirst edition: October 2012.
500 $aIncludes index.
505 0 $aPreliminaries -- Python language basics, IPython, and Jupyter notebooks -- Built-in data structures, functions, and files -- NumPy basics: arrays and vectorized computation -- Getting started with pandas -- Data loading, storage, and file formats -- Data cleaning and preparation -- Data wrangling: join, combine, and reshape -- Plotting and visualization -- Data aggregation and group operations -- Time series -- Advanced pandas -- Introduction to modeling libraies in Python -- Data analysis examples -- Advanced NumPy -- More on the IPython system.
520 $a"Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process"--Page 4 of cover.
650 0 $aPython (Computer program language)
650 0 $aProgramming languages (Electronic computers)
650 0 $aData mining.
650 7 $aProgramming languages (Electronic computers)$2fast$0(OCoLC)fst01078704
650 7 $aData mining.$2fast$0(OCoLC)fst00887946
650 7 $aPython (Computer program language)$2fast$0(OCoLC)fst01084736
650 7 $aPython 3.6$2gnd$0(DE-588)113674746X
650 7 $aDatenanalyse$2gnd$0(DE-588)4123037-1
650 7 $aDatenmanagement$2gnd$0(DE-588)4213132-7
650 7 $aData Mining$2gnd$0(DE-588)4428654-5
852 00 $bets$hQA76.73.P98$iM42 2018g