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Practical Data Analysis Cookbook

You're reading from   Practical Data Analysis Cookbook Over 60 practical recipes on data exploration and analysis

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Product type Paperback
Published in Apr 2016
Publisher
ISBN-13 9781783551668
Length 384 pages
Edition 1st Edition
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Author (1):
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Tomasz Drabas Tomasz Drabas
Author Profile Icon Tomasz Drabas
Tomasz Drabas
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Toc

Table of Contents (13) Chapters Close

Preface 1. Preparing the Data FREE CHAPTER 2. Exploring the Data 3. Classification Techniques 4. Clustering Techniques 5. Reducing Dimensions 6. Regression Methods 7. Time Series Techniques 8. Graphs 9. Natural Language Processing 10. Discrete Choice Models 11. Simulations Index

Chapter 7. Time Series Techniques

In this chapter, we will cover various techniques of handling, analyzing, and predicting the future with time series data. You will learn the following recipes:

  • Handling date objects in Python
  • Understanding time series data
  • Smoothing and transforming the observations
  • Filtering the time series data
  • Removing trend and seasonality
  • Forecasting the future with ARMA and ARIMA models
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