Read Python Data Analysis - Second Edition

Free Python Data Analysis - Second Edition

Free Python Data Analysis - Second Edition

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Key FeaturesFind, manipulate, and analyze your data using the Python 3.5 librariesPerform advanced, high-performance linear algebra and mathematical calculations with clean and efficient Python codeAn easy-to-follow guide with realistic examples that are frequently used in real-world data analysis projects.Book DescriptionData analysis techniques generate useful insights from small and large volumes of data. Python, with its strong set of libraries, has become a popular platform to conduct various data analysis and predictive modeling tasks.With this book, you will learn how to process and manipulate data with Python for complex analysis and modeling. We learn data manipulations such as aggregating, concatenating, appending, cleaning, and handling missing values, with NumPy and Pandas. The book covers how to store and retrieve data from various data sources such as SQL and NoSQL, CSV fies, and HDF5. We learn how to visualize data using visualization libraries, along with advanced topics such as signal processing, time series, textual data analysis, machine learning, and social media analysis.The book covers a plethora of Python modules, such as matplotlib, statsmodels, scikit-learn, and NLTK. It also covers using Python with external environments such as R, Fortran, C/C++, and Boost libraries.What you will learnInstall open source Python modules such NumPy, SciPy, Pandas, stasmodels, scikit-learn,theano, keras, and tensorflow on various platformsPrepare and clean your data, and use it for exploratory analysisManipulate your data with PandasRetrieve and store your data from RDBMS, NoSQL, and distributed filesystems such as HDFS and HDF5Visualize your data with open source libraries such as matplotlib, bokeh, and plotlyLearn about various machine learning methods such as supervised, unsupervised, probabilistic, and BayesianUnderstand signal processing and time series data analysisGet to grips with graph processing and social network analysisAbout the AuthorArmando Fandango is Chief Data Scientist at Epic Engineering and Consulting Group, and works on confidential projects related to defense and government agencies. Armando is an accomplished technologist with hands-on capabilities and senior executive-level experience with startups and large companies globally. His work spans diverse industries including FinTech, stock exchanges, banking, bioinformatics, genomics, AdTech, infrastructure, transportation, energy, human resources, and entertainment.Armando has worked for more than ten years in projects involving predictive analytics, data science, machine learning, big data, product engineering, high performance computing, and cloud infrastructures. His research interests spans machine learning, deep learning, and scientific computing.Table of ContentsGetting Started with Python LibrariesNumPy ArraysThe Pandas PrimerStatistics and Linear AlgebraRetrieving, Processing, and Storing DataData VisualizationSignal Processing and Time SeriesWorking with DatabasesAnalyzing Textual Data and Social MediaPredictive Analytics and Machine LearningEnvironments Outside the Python Ecosystem and Cloud ComputingPerformance Tuning, Profiling, and ConcurrencyKey ConceptsUseful FunctionsOnline Resources Statistics and Data Analysis for Microarrays Using R and Book Description: Richly illustrated in color Statistics and Data Analysis for Microarrays Using R and Bioconductor Second Edition provides a clear and rigorous Learning Python 5th Edition: Mark Lutz: 9781449355739 Buy Learning Python 5th Edition on FREE SHIPPING on qualified orders 1 Language Processing and Python 1 Language Processing and Python It is easy to get our hands on millions of words of text What can we do with it assuming we can write some simple programs? Python 3 Object-oriented Programming - Second Edition Rethink Python programming with this guide to Python data structures design patterns and effective object oriented techniques to uncover a truly modern Python Natural Language Toolkit NLTK 30 documentation Natural Language Toolkit NLTK is a leading platform for building Python programs to work with human language data It provides easy-to-use interfaces to over 50 Think Stats: Exploratory Data Analysis in Python Think Stats Exploratory Data Analysis in Python Version 2035 Allen B Downey Green Tea Press Needham Massachusetts Python Programming in Context Second Edition Python Programming in Context Second Edition is a clear accessible introduction to the fundamental programming and problem solving concepts necessary for students Addison-Wesley Professional InformIT Featured Book Learn Python Programming in 5 Hours Python from Scratch LiveLessons is a gentler more entertaining and more practical starting point to learning the Python Data Science Handbook: Essential Tools for Working Ebooks related to "Python Data Science Handbook: Essential Tools for Working with Data" : Learning SQLite for iOS Expert Consolidation in Oracle Database 12c The Popularity of Data Science Software r4statscom As we see Python surpassed R in terms of data science jobs back in 2013 These are of course very different languages and a quick scan of job descriptions will
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