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(This article was first published on <strong><a href="https://www.r-exercises.com/2018/06/06/intro-to-time-series-analysis-part-1/"> R-exercises</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p><a rel="nofollow" href="https://www.r-exercises.com/wp-content/uploads/2016/10/update-1672363_960_720.jpg" target="_blank"><img src="https://www.r-exercises.com/2018/06/06/intro-to-time-series-analysis-part-1/" alt="" sizes="(max-width: 150px) 100vw, 150px" width="150" class="wp-image-2308" height="150"></a><br>
In the exercises below, we will work with Time Series analysis and see how R can make your life easier when working with Time Series. </p>
<p>doing Time Series Analysis.This will be a series of Exercises and I urge you to take it in series<br>
Please install the package and load the library before starting<br>
Answers to these exercises are available <a rel="nofollow" href="https://www.r-exercises.com/2018/06/06/intro-to-time-series-analysis-part-1-solutions/" target="_blank">here</a>.</p>
<p><strong>Exercise 1</strong></p>
<p>Install Forecast package ,1st step in any analysis is to see the data , use autoplot to plot the gold data set </p>
<p>available in forecast package . </p>
<p><strong>Exercise 2</strong><br>
Find the outlier in the gold data .Find how far its from the median </p>
<p><strong>Exercise 3</strong></p>
<p>use ggseasonalplot to plot the gas data . See how each year stack with each other </p>
<p><strong>Exercise 4</strong></p>
<p>Now I want to plot the gas data for year 1990 and after .How do I achieve that .<br>
<strong>Exercise 5</strong></p>
<p>ggseasonalplot can be used to see seasonal plots as polar coordinates , plot the same data as above but use </p>
<p>polar coordinates instead . </p>
<p><strong>Exercise 6</strong><br>
How can I see monthly time series of the gas price<br>
Hint use monthplot or ggsubseriesplot</p>
<p><strong>Exercise 7</strong></p>
<p>For a timeseries ,we can find the dominant frequency of that time series and use it to our analysis .How to </p>
<p>find the frequency of gas data (assume that its a long /big data and you dont have a clue of the frequency)</p>
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<h3>Related exercise sets:</h3>
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<li><a rel="nofollow" href="https://www.r-exercises.com/2018/01/10/spatial-data-analysis-introduction-to-raster-processing-part-3/" title="Spatial Data Analysis: Introduction to Raster Processing: Part-3" target="_blank">Spatial Data Analysis: Introduction to Raster Processing: Part-3 </a></li>
<li><a rel="nofollow" href="https://www.r-exercises.com/2018/02/28/advanced-techniques-with-raster-data-part-1-unsupervised-classification/" title="Advanced Techniques With Raster Data: Part 1 – Unsupervised Classification" target="_blank">Advanced Techniques With Raster Data: Part 1 – Unsupervised Classification </a></li>
<li><a rel="nofollow" href="http://www.r-exercises.com/start-here-to-learn-r/" target="_blank">Explore all our (>1000) R exercises</a></li>
<li><a rel="nofollow" href="http://www.r-exercises.com/r-courses/" target="_blank">Find an R course using our R Course Finder</a> directory</li>
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