دانلود کتاب Python Data Analysis Cookbook

Key FeaturesAnalyze Big Data sets, create attractive visualizations, and manipulate and process various data typesPacked with rich recipes to help you learn and explore amazing algorithms for statistics and machine learningAuthored by Ivan Idris, expert in python programming and proud author of eight highly reviewed booksBook DescriptionData analysis is a rapidly evolving field and Python is a multi-paradigm programming language suitable for object-oriented application development and functional design patterns. As Python offers a range of tools and libraries for all purposes, it has slowly evolved as the primary language for data science, including topics on: data analysis, visualization, and machine learning.Python Data Analysis Cookbook focuses on reproducibility and creating production-ready systems. You will start with recipes that set the foundation for data analysis with libraries such as matplotlib, NumPy, and pandas. You will learn to create visualizations by choosing color maps and palettes then dive into statistical data analysis using distribution algorithms and correlations. You’ll then help you find your way around different data and numerical problems, get to grips with Spark and HDFS, and then set up migration scripts for web mining.In this book, you will dive deeper into recipes on spectral analysis, smoothing, and bootstrapping methods. Moving on, you will learn to rank stocks and check market efficiency, then work with metrics and clusters. You will achieve parallelism to improve system performance by using multiple threads and speeding up your code.By the end of the book, you will be capable of handling various data analysis techniques in Python and devising solutions for problem scenarios. What You Will LearnSet up reproducible data analysisClean and transform dataApply advanced statistical analysisCreate attractive data visualizationsWeb scrape and work with databases, Hadoop, and SparkAnalyze images and time series dataMine text and analyze social networksUse machine learning and evaluate the resultsTake advantage of parallelism and concurrencyAbout the AuthorIvan Idris was born in Bulgaria to Indonesian parents. He moved to the Netherlands and graduated in experimental physics. His graduation thesis had a strong emphasis on applied computer science. After graduating, he worked for several companies as a software developer, data warehouse developer, and QA analyst.His professional interests are business intelligence, big data, and cloud computing. He enjoys writing clean, testable code and interesting technical articles. He is the author of NumPy Beginner's Guide, NumPy Cookbook, Learning NumPy, and Python Data Analysis, all by Packt Publishing.Table of ContentsLaying the Foundation for Reproducible Data AnalysisCreating Attractive Data VisualizationsStatistical Data Analysis and ProbabilityDealing with Data and Numerical IssuesWeb Mining, Databases, and Big DataSignal Processing and TimeseriesSelecting Stocks with Financial Data AnalysisText Mining and Social Network AnalysisEnsemble Learning and Dimensionality ReductionEvaluating Classifi ers, Regressors, and ClustersAnalyzing ImagesParallelism and PerformanceGlossaryFunction Reference