| Record ID | marc_loc_2016/BooksAll.2016.part40.utf8:152160494:1299 |
| Source | Library of Congress |
| Download Link | /show-records/marc_loc_2016/BooksAll.2016.part40.utf8:152160494:1299?format=raw |
LEADER: 01299cam a2200289 a 4500
001 2012538094
003 DLC
005 20151121080449.0
008 130208s2013 cc a 001 0 eng d
010 $a 2012538094
016 7 $a016118103$2Uk
020 $a9781449319793 (pbk.)
020 $a1449319793 (pbk.)
035 $a(OCoLC)ocn794362690
040 $aBTCTA$beng$cBTCTA$dUKMGB$dYDXCP$dSINLB$dOCLCO$dCDX$dIAD$dBWX$dTXI$dDLC
042 $alccopycat
050 00 $aQA76.73.P98$bM42 2013
082 00 $a005.13/3$223
100 1 $aMcKinney, Wes.
245 10 $aPython for data analysis /$cWes McKinney.
260 $aBeijing :$bO'Reilly,$cc2013.
300 $axiii, 447 p. :$bill. ;$c24 cm.
500 $aIncludes index.
505 0 $aPreliminaries -- Introductory examples -- IPython : an interactive computing and development environment -- NumPy basics : arrays and vectorized computation -- Getting started with pandas -- Data loading, storage, and file formats -- Data wrangling : clean, transform, merge, reshape -- Plotting and visualization -- Data aggregation and group operations -- Time series -- Financial and economic data applications -- Advancded NumPy.
650 0 $aPython (Computer program language)
650 0 $aProgramming languages (Electronic computers)
650 0 $aData mining.