000 01887nam a22003377a 4500
003 OSt
005 20260324111459.0
008 260324s2022 caua frb 001 0 eng d
020 _a9781098104030
035 _a(CKB)5590000000474271
035 _a(CaSebORM)9781098104023
035 _a(OCoLC)1341278534
035 _a(OCoLC-P)1341278534
035 _a(EXLCZ)995590000000474271
040 _aOCoLC-P
_beng
_erda
_epn
_cOCoLC-P
_dclrauoh
050 4 _aQA76.73.P98
082 0 4 _a006.312
100 1 _aMcKinney, Wes,
_eauthor.
245 1 0 _aPython for data analysis :
_bdata wrangling with Pandas, NumPy, and Jupyter /
_cWes McKinney.
250 _aThird edition.
260 _aSebastopol, CA :
_bO'Reilly Media,
_c2022
300 _axvi, 561 pages :
_billustrations.
336 _atext
_btxt
_2rdacontent
337 _aunmediated
_bn
_2rdamedia
338 _avolumen
_bnc
_2rdacarrier
505 _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 -- Introduction to Modeling Libraries in Python -- Data Analysis Examples.
520 _aGet the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third 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, and Jupyter in the process.
650 0 _aData mining.
650 0 _aPython (Computer program language)
942 _2ddc
_cBOOK
_n0
999 _c6983
_d6983