Python Data Analysis - Second Edition
Beschreibung
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Learn how to apply powerful data analysis techniques with popular open source Python modulesAbout This Book• 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.Who This Book Is ForThis book is for programmers, scientists, and engineers who h…

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With Perlego (The Spotify for Books) you get unlimited access to
more than 250,000 professional and self-development books in one
simple space for one simple price. You can learn on the go with our
mobile app!
Learn how to apply powerful data analysis techniques with
popular open source Python modulesAbout This Book• 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.Who This Book Is ForThis
book is for programmers, scientists, and engineers who have the
knowledge of Python and know the basics of data science. It is for
those who wish to learn different data analysis methods using
Python 3.5 and its libraries. This book contains all the basic
ingredients you need to become an expert data analyst.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 HDF5• Visualize your data with open source
libraries such as matplotlib, bokeh, and plotly• Learn about
various machine learning methods such as supervised, unsupervised,
probabilistic, and Bayesian• Understand signal processing and time
series data analysis• Get to grips with graph processing and social
network analysisIn DetailData 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.Style and approachThe book
takes a very comprehensive approach to enhance your understanding
of data analysis. Sufficient real-world examples and use cases are
included in the book to help you grasp the concepts quickly and
apply them easily in your day-to-day work. Packed with clear, easy
to follow examples, this book will turn you into an ace data
analyst in no time.
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