Get started with Python for data analysis and numerical computing
in the Jupyter notebook About This Book * Learn the basics of
Python in the Jupyter Notebook * Analyze and visualize data with
pandas, NumPy, matplotlib, and seaborn * Perform highly-efficient
numerical computations with Numba, Cython, and ipyparallel Who This
Book Is For This book targets students, teachers, researchers,
engineers, analysts, journalists, hobbyists, and all data
enthusiasts who are interested in analyzing and visualizing
real-world datasets. If you are new to programming and data
analysis, this book is exactly for you. If you're already familiar
with another language or analysis software, you will also
appreciate this introduction to the Python data analysis platform.
Finally, there are more technical topics for advanced readers. No
prior experience is required; this book contains everything you
need to know. What You Will Learn * Install Anaconda and code in
Python in the Jupyter Notebook * Load and explore datasets
interactively * Perform complex data manipulations effectively with
pandas * Create engaging data visualizations with matplotlib and
seaborn * Simulate mathematical models with NumPy * Visualize and
process images interactively in the Jupyter Notebook with
scikit-image * Accelerate your code with Numba, Cython, and
IPython.parallel * Extend the Notebook interface with HTML,
JavaScript, and D3 In Detail Python is a user-friendly and powerful
programming language. IPython offers a convenient interface to the
language and its analysis libraries, while the Jupyter Notebook is
a rich environment well-adapted to data science and visualization.
Together, these open source tools are widely used by beginners and
experts around the world, and in a huge variety of fields and
endeavors. This book is a beginner-friendly guide to the Python
data analysis platform. After an introduction to the Python
language, IPython, and the Jupyter Notebook, you will learn how to
analyze and visualize data on real-world examples, how to create
graphical user interfaces for image processing in the Notebook, and
how to perform fast numerical computations for scientific
simulations with NumPy, Numba, Cython, and ipyparallel. By the end
of this book, you will be able to perform in-depth analyses of all
sorts of data. Style and approach This is a hands-on
beginner-friendly guide to analyze and visualize data on real-world
examples with Python and the Jupyter Notebook.
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