Course
Visualizing Time Series Data in R
IntermediateSkill Level
Updated 03/2024RData Visualization4 hr11 videos45 Exercises3,550 XP16,239Statement of Accomplishment
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Prerequisites
Manipulating Time Series Data in R1
R Time Series Visualization Tools
This chapter will introduce you to basic R time series visualization tools.
2
Univariate Time Series
Univariate plots are designed to learn as much as possible about the distribution, central tendency and spread of the data at hand. In this chapter you will be presented with some visual tools used to diagnose univariate times series.
3
Multivariate Time Series
What to do if you have to deal with multivariate time series? In this chapter, you will learn how to identify patterns in the distribution, central tendency and spread over pairs or groups of data.
4
Case study: Visually Selecting a Stock That Improves Your Existing Portfolio
Let's put everything you learned so far in practice! Imagine you already own a portfolio of stocks and you have some spare cash to invest, how can you wisely select a new stock to invest your additional cash? Analyzing the statistical properties of individual stocks vs. an existing portfolio is a good way of approaching the problem.
Visualizing Time Series Data in R
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FAQs
What types of time series visualizations does this course cover?
You learn univariate plots for distribution and spread, multivariate visualizations for comparing groups, and portfolio-oriented charts for comparing stocks against an existing portfolio.
Is this course focused on modeling or on visualization?
It focuses on visualization. The goal is to help you choose the right chart type for time series data so you can make better decisions about which model to apply afterward.
What is the case study in the final chapter about?
You use visual analysis to decide which stock to add to an existing portfolio, comparing statistical properties of individual stocks against portfolio performance.
What R experience do I need before starting?
You should know Intermediate R, have experience manipulating time series data in R, and be comfortable working with dates and times in R.
How many exercises does this course include?
The course has 45 exercises spread across 4 chapters, with a total estimated time of 240 minutes. Most learners complete it in about 2.3 hours.
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