000			01556nam a22002177a 4500
005			20230302150609.0
008			230302b |||||||| |||| 00| 0 eng d
020			_a9789352136414
082			_a005.133 _bMCK
100			_aMcKinney, Wes
245			_aPython for data analysis : _bData Wrangling wit Pandas, NumPy, and IPython _cWes McKinney
250			_a2nd Ed.
260			_aBeijing : _bO'Reilly, _c2018
300			_a522 pages : _bill.; _c24 cm.
505			_tPreliminaries _tPython language basics, IPython, and Jupyter notebooks _tBuilt-in data structures, functions, and files _tNumPy basics: arrays and vectorized computation _tGetting started with pandas _tData loading, storage, and file formats _tData cleaning and preparation _tData wrangling: join, combine, and reshape _tPlotting and visualization _tData aggregation and group operations _tTime series _tAdvanced pandas _tIntroduction to modeling libraies in Python _tData analysis examples _tAdvanced NumPy _tMore on the IPython system
520			_aGet 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
650			_aPython (Computer program language)
650			_aData mining
650			_aProgramming languages (Electronic computers)
942			_2ddc _cBK
999			_c1918 _d1918