Visualizing Time Series Data in R
Offered By: DataCamp
Course Description
Overview
Learn how to visualize time series in R, then practice with a stock-picking case study.
As the saying goes, “A chart is worth a thousand words”. This is why visualization is the most used and powerful way to get a better understanding of your data. After this course you will have a very good overview of R time series visualisation capabilities and you will be able to better decide which model to choose for subsequent analysis. You will be able to also convey the message you want to deliver in an efficient and beautiful way.
As the saying goes, “A chart is worth a thousand words”. This is why visualization is the most used and powerful way to get a better understanding of your data. After this course you will have a very good overview of R time series visualisation capabilities and you will be able to better decide which model to choose for subsequent analysis. You will be able to also convey the message you want to deliver in an efficient and beautiful way.
Syllabus
- R Time Series Visualization Tools
- This chapter will introduce you to basic R time series visualization tools.
- 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.
- 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.
- 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.
Taught by
Arnaud Amsellem
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