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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
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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

Data sources

Data source is a term for all the technology related to the extraction and storage of data. A data source can be anything from a simple text file to a big database. The raw data can come from observation logs, sensors, transactions, or user behavior.

A dataset is a collection of data, usually presented in a tabular form. Each column represents a particular attribute, and each row corresponds to a given member of the data, as is showed in the following screenshot.

Data sources

In this section, we will take a look at the most common forms for data sources and datasets.

Tip

The data in the preceding screenshot is from the classical Weather dataset of the UC Irvine Machine Learning Repository:

http://archive.ics.uci.edu/ml/

A dataset represents a logical implementation of a data source; the common features of a dataset:

  • Dataset characteristics (multivariate and univariate)
  • Number of instances
  • Area (life, business, and many more)
  • Attribute characteristics (real, categorical, and nominal)
  • Number of...
You have been reading a chapter from
Practical Data Analysis - Second Edition
Published in: Sep 2016
Publisher:
ISBN-13: 9781785289712
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