000			01865nam a22002057a 4500
999			_c2440 _d2440
003			OSt
005			20200224131527.0
008			200117b ||||| |||| 00| 0 eng d
020			_a978-93-5213-434-2
028			_bAllied Informatics, Jaipur _c7084 _d13/01/2020 _q2019-20
040			_aBSDU _bEnglish _cBSDU
082			_a005.133 _bBRO
100			_aBrownley, Clinton W.
245			_aFoundations for Analytics with Python: From non-programmer to hacker
260			_aMumbai _bShroff Publishers & Distributors Pvt. Ltd. _c2018
300			_a322
504			_aIf you’re like many of Excel’s 750 million users, you want to do more with your data—like repeating similar analyses over hundreds of files, or combining data in many files for analysis at one time. This practical guide shows ambitious non-programmers how to automate and scale the processing and analysis of data in different formats—by using Python. After author Clinton Brownley takes you through Python basics, you’ll be able to write simple scripts for processing data in spreadsheets as well as databases. You’ll also learn how to use several Python modules for parsing files, grouping data, and producing statistics. No programming experience is necessary. Create and run your own Python scripts by learning basic syntax Use Python’s csv module to read and parse CSV files Read multiple Excel worksheets and workbooks with the xlrd module Perform database operations in MySQL or with the mysqlclient module Create Python applications to find specific records, group data, and parse text files Build statistical graphs and plots with matplotlib, pandas, ggplot, and seaborn Produce summary statistics, and estimate regression and classification models Schedule your scripts to run automatically in both Windows and Mac environments
650			_aPython
942			_2ddc _cBK