Book Image

Python Data Analysis - Second Edition

By : Ivan Idris
Book Image

Python Data Analysis - Second Edition

By: Ivan 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 (22 chapters)
Python Data Analysis - Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Key Concepts
Online Resources

Using REST web services and JSON


Representational State Transfer (REST) web services use the REST architectural style (for more information, refer to http://en.wikipedia.org/wiki/Representational_state_transfer). In the usual context of the HTTP(S) protocol, we have the GET, POST, PUT, and DELETE methods. These methods can be aligned with common operations on the data to create, request, update, or delete data items.

In a RESTful API, data items are identified by URIs such as http://example.com/resources or http://example.com/resources/item42. REST is not an official standard, but is so widespread that we need to know about it. Web services often use JavaScript Object Notation (JSON) (for more information refer to http://en.wikipedia.org/wiki/JSON) to exchange data. In this format, data is written using the JavaScript notation. The notation is similar to the syntax for Python lists and dicts. In JSON, we can define arbitrarily complex data consisting of a combination of lists and dicts...