Book Image

Practical Data Science Cookbook, Second Edition - Second Edition

By : Prabhanjan Narayanachar Tattar, Bhushan Purushottam Joshi, Sean Patrick Murphy, ABHIJIT DASGUPTA, Anthony Ojeda
Book Image

Practical Data Science Cookbook, Second Edition - Second Edition

By: Prabhanjan Narayanachar Tattar, Bhushan Purushottam Joshi, Sean Patrick Murphy, ABHIJIT DASGUPTA, Anthony Ojeda

Overview of this book

As increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don’t. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract valuable insights from data and create valuable solutions that put those insights to use. Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis—R and Python.
Table of Contents (17 chapters)
Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface

Visualizing time series data


Visual depiction of time series is important to get early insights into the nature of the data. Visualization of time series is very simple in the sense that simply plotting the time series variable against the time itself gives insight about the behavior of the data. The R function plot.ts can be applied on the ts objects and the time series can be visualized. For the overseas visitors problem, we plot the number of visitors for the month against that time instance.

Getting ready

The reader needs to have the osv object from the previous session in the current environment.

How to do it...

  1. We will now apply the plot.ts function to obtain the visual depiction of the overseas data.
  2. Run the following line in the R session:

plot.ts
(osv, main="New Zealand Overseas Visitors",ylab="Frequency")

The output given by running the R line is shown in the following diagram:

It may be seen from the diagram that a certain pattern is recurrent and that cycle appears as 12 data points...