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    Python Data Analysis

    Posted By: Grev27
    Python Data Analysis

    Armando Fandango, "Python Data Analysis"
    English | ISBN: 1787127486 | 2017 | EPUB/MOBI/Code files | 330 pages | 20 MB

    Key Features
    Find, manipulate, and analyze your data using the Python 3.5 libraries
    Perform advanced, high-performance linear algebra and mathematical calculations with clean and efficient Python code
    An easy-to-follow guide with realistic examples that are frequently used in real-world data analysis projects.
    Book Description
    Data 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 learn
    Install open source Python modules such NumPy, SciPy, Pandas, stasmodels, scikit-learn,theano, keras, and tensorflow on various platforms
    Prepare and clean your data, and use it for exploratory analysis
    Manipulate your data with Pandas
    Retrieve and store your data from RDBMS, NoSQL, and distributed filesystems such as HDFS and