From the course: Data Science Foundations: Data Assessment for Predictive Modeling
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Challenge: Producing multivariate visualizations for case study 1
From the course: Data Science Foundations: Data Assessment for Predictive Modeling
Challenge: Producing multivariate visualizations for case study 1
(electronic music) - [Instructor] Welcome to your next challenge. I'm showing the previous ggplot2 chart, because your challenge is to reproduce a chart just like this using the Titanic dataset. I've created a special file for this purpose. It's called train modified, train because it's only the train partition and modified because some numeric variables have been converted into strings so that ggplot2 immediately recognizes that they are nominal variables and not scale. So your challenge is to take the following variables and imitate this chart. Age, passenger class, survived, and sex, and note that just one of those is a scale variable and the other three are nominal. If you know, ggplot2, this should only take about five minutes. If you've never used ggplot2 before, you should be able to figure it out from the previous example, but it might take more like 15 minutes.
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Contents
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How to utilize an SME's time effectively2m 8s
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Techniques for working with the top predictors4m 19s
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Advice for weak predictors6m 4s
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Tips and tricks when searching for quirks in your data4m 46s
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Learning when to discard rows2m 5s
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Introducing ggplot21m 44s
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Orientating to R's ggplot2 for powerful multivariate data visualizations5m 52s
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Challenge: Producing multivariate visualizations for case study 11m 12s
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Solution: Producing multivariate visualizations for case study 12m 31s
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