Join Mike Chapple for an in-depth discussion in this video What's next?, part of Cleaning Bad Data in R.
- [Mike] Thanks for joining me for this exploration…of Cleaning Bad Data in R.…I hope that you've learned quite a bit in this course…and found it helpful in developing…your data analysis skills.…If you haven't gone through the examples…in this course step-by-step on your own,…I encourage you to go back and do that now.…You might also wanna try starting…with one of the data sets…and building an R script…to manipulate it on your own,…without rewatching the video.…You can reference the videos if you need the help,…but doing the work yourself…will really help solidify your skills.…
As a next step, I encourage you to try this work…on a data set from your work or school.…If you don't have a good data set that you can use,…the U.S. government's data portal at data.gov…is a great starting point…to find all sorts of interesting data.…If you want to move on to some other courses,…you might try my course Data Wrangling in R,…which explores some more of these…data cleaning topics in greater detail,…or my course Visualizing Data in R with ggplot2,…
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
What's next?1m 5s
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