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Python: Real-World Data Science

You're reading from   Python: Real-World Data Science Real-World Data Science

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Product type Course
Published in Jun 2016
Publisher
ISBN-13 9781786465160
Length 1255 pages
Edition 1st Edition
Languages
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Authors (5):
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Fabrizio Romano Fabrizio Romano
Author Profile Icon Fabrizio Romano
Fabrizio Romano
Phuong Vo.T.H Phuong Vo.T.H
Author Profile Icon Phuong Vo.T.H
Phuong Vo.T.H
Robert Layton Robert Layton
Author Profile Icon Robert Layton
Robert Layton
Sebastian Raschka Sebastian Raschka
Author Profile Icon Sebastian Raschka
Sebastian Raschka
Martin Czygan Martin Czygan
Author Profile Icon Martin Czygan
Martin Czygan
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Table of Contents (12) Chapters Close

Table of Contents FREE CHAPTER
Python: Real-World Data Science
Meet Your Course Guide
What's so cool about Data Science?
Course Structure
Course Journey
The Course Roadmap and Timeline
1. Course Module 1: Python Fundamentals 2. Course Module 2: Data Analysis 3. Course Module 3: Data Mining 4. Course Module 4: Machine Learning Index

Chapter 5. Time Series

Time series typically consist of a sequence of data points coming from measurements taken over time. This kind of data is very common and occurs in a multitude of fields.

A business executive is interested in stock prices, prices of goods and services or monthly sales figures. A meteorologist takes temperature measurements several times a day and also keeps records of precipitation, humidity, wind direction and force. A neurologist can use electroencephalography to measure electrical activity of the brain along the scalp. A sociologist can use campaign contribution data to learn about political parties and their supporters and use these insights as an argumentation aid. More examples for time series data can be enumerated almost endlessly.

Time series primer

In general, time series serve two purposes. First, they help us to learn about the underlying process that generated the data. On the other hand, we would like to be able to forecast future values of the...

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