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Practical Data Analysis

You're reading from   Practical Data Analysis Pandas, MongoDB, Apache Spark, and more

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Product type Paperback
Published in Sep 2016
Publisher
ISBN-13 9781785289712
Length 338 pages
Edition 2nd Edition
Languages
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Authors (2):
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Hector Cuesta Hector Cuesta
Author Profile Icon Hector Cuesta
Hector Cuesta
Dr. Sampath Kumar Dr. Sampath Kumar
Author Profile Icon Dr. Sampath Kumar
Dr. Sampath Kumar
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Table of Contents (16) Chapters Close

Preface 1. Getting Started 2. Preprocessing Data FREE CHAPTER 3. Getting to Grips with Visualization 4. Text Classification 5. Similarity-Based Image Retrieval 6. Simulation of Stock Prices 7. Predicting Gold Prices 8. Working with Support Vector Machines 9. Modeling Infectious Diseases with Cellular Automata 10. Working with Social Graphs 11. Working with Twitter Data 12. Data Processing and Aggregation with MongoDB 13. Working with MapReduce 14. Online Data Analysis with Jupyter and Wakari 15. Understanding Data Processing using Apache Spark

Getting started with Wakari

Wakari is a cloud service for collaborative Python data analysis environments, created by Continuum Analytics. Wakari provides a powerful set of pre-configured Python environments built on top of Anaconda, which is a free Python distribution for large-scale data processing and scientific computing. Wakari uses a Jupyter GUI, which is a Python shell improved to write, debug, and test Python code for scientific computing.

Jupyter is an open source, interactive data science tool with support for 40 programming languages. Jupyter provides a terminal-based interface and a Wolfram-Matematica such as HTML notebook. In Wakari, we can use either the terminal console or Jupyter notebook.

Wakari helps us to set up a complete scientific Python environment without any local installation. This can be very convenient for learning purposes, because we may start coding right away, and the Anaconda distribution includes several of the most used libraries, such as NumPy, SciPy,...

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