Join Mike Chapple for an in-depth discussion in this video Missing rows, part of Cleaning Bad Data in R.
- [Instructor] Sometimes our data sets…are missing entire rows.…We've already talked about some of the reasons…this may occur.…Rows may be missing completely at random,…missing at random, or missing not at random.…In the last video we looked at the situation…that arises when we are missing values from a data set.…Those are generally easy to detect.…We can simply look for NA values or unusual flags in a file.…In the last video we looked at a data set…that had periods and Zs that both represented zero.…
Missing rows are usually much more difficult to detect…because there's no row there to analyze.…Detecting missing rows generally requires…some additional subject matter knowledge.…For example, if we know that there is supposed to be…a row in a data set for every year…and we have rows for 1990 through 2016…and then another row for 2018, it's logical to conclude…that 2017 is missing.…Let's take a look at an example of a data file…that's missing rows in R.…
As with the previous example, I've already set up the code…to load the data file.…
Where possible, instructor Mike Chapple shows how to correct the issues using R, but the same principles can be applied to any statistical programing language.
- Missing data
- Duplicate rows and values
- Converting data
- Formatting data
- Working with tidy data
- Tidying data sets
- Dealing with suspicious data
Skill Level Beginner
1. Missing Data
2. Duplicated Data
3. Formatting Data
5. Tidy Data
6. Red Flags
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