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Python Data Analysis, Second Edition

Python Data Analysis, Second Edition

By : Idris
4 (4)
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Python Data Analysis, Second Edition

Python Data Analysis, Second Edition

4 (4)
By: Idris

Overview of this book

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.
Table of Contents (16 chapters)
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13
A. Key Concepts
15
C. Online Resources

Chapter 11.  Environments Outside the Python Ecosystem and Cloud Computing

Outside the Python ecosystem, programming languages such as R, C, Java, and Fortran are fairly popular. In this chapter, we will delve into the particulars of exchanging information with these environments.

Cloud computing aims to deliver computing power as a utility over the Internet. This means that we don't need to have a lot of powerful hardware locally. Instead, we pay as we go, depending on our current needs. We will also talk about how to get our Python code in the Cloud. This is a rapidly evolving industry in a fast-paced world. We have many options available PythonAnywhere. Amazon Web Services (AWS) is deliberately not discussed in this book, since other books, such as Building Machine Learning Systems with Python, Willi Richert and Luis Pedro Coelho, Packt Publishing, cover the topic in great detail.

Data science toolbox, available from http://datasciencetoolbox.org/, is a virtual environment...

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