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Hands-On Data Analysis with NumPy and pandas

Miller Curtis Miller

E-Book (epub)

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Get to grips with the most popular Python packages that make data analysis possibleKey FeaturesExplore the tools you need to beco...

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Beschreibung

Get to grips with the most popular Python packages that make data analysis possibleKey FeaturesExplore the tools you need to become a data analystDiscover practical examples to help you grasp data processing conceptsWalk through hierarchical indexing and grouping for data analysisBook DescriptionPython, a multi-paradigm programming language, has become the language of choice for data scientists for visualization, data analysis, and machine learning.Hands-On Data Analysis with NumPy and Pandas starts by guiding you in setting up the right environment for data analysis with Python, along with helping you install the correct Python distribution. In addition to this, you will work with the Jupyter notebook and set up a database. Once you have covered Jupyter, you will dig deep into Python's NumPy package, a powerful extension with advanced mathematical functions. You will then move on to creating NumPy arrays and employing different array methods and functions. You will explore Python's pandas extension which will help you get to grips with data mining and learn to subset your data. Last but not the least you will grasp how to manage your datasets by sorting and ranking them. By the end of this book, you will have learned to index and group your data for sophisticated data analysis and manipulation.What you will learnUnderstand how to install and manage AnacondaRead, sort, and map data using NumPy and pandasFind out how to create and slice data arrays using NumPyDiscover how to subset your DataFrames using pandasHandle missing data in a pandas DataFrameExplore hierarchical indexing and plotting with pandasWho this book is forHands-On Data Analysis with NumPy and Pandas is for you if you are a Python developer and want to take your first steps into the world of data analysis. No previous experience of data analysis is required to enjoy this book.