From the course: Data Science Foundations: Data Assessment for Predictive Modeling
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What is the pattern of missing data in your data?
From the course: Data Science Foundations: Data Assessment for Predictive Modeling
What is the pattern of missing data in your data?
- [Instructor] Okay, I'm in KNIME, and I've started a new workflow called chapter 10. And I'm working with the reduced vars version of the data set just to make it a little bit more manageable. You're going to find that when you have a large data set, and 100,000 really shouldn't be large. But when you have a large data set with a lot of missing data, it can be more computationally intensive and the reason is that you can end up having huge numbers of categories within those nominal variables, particularly if there's a lot of errors and blanks and so on. So I think you're going to find that handling the original version of the data can be a little bit challenging. So we're using the reduced vars version for this. And I've attached to Data Explorer, and it's already run. So let's take a look. Okay, so here we go. How do you size up your missing data situation? Well, clearly, we can scan through all these variables, at…
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