Learning Objectives
Following this assignment students should be able to:
- understand the basic rules of tidy data
- implement quality control for data entry in spreadsheets
- create an SQL database by importing data
Reading
Lecture Notes
Exercises
Improving Messy Data (50 pts)
A lot of real data isn’t very tidy, mostly because most scientists aren’t taught about how to structure their data in a way that is easy to analyze.
Download a messy version of some of the Portal Project data. Note that there are multiple tabs in this spreadsheet.
Think about what could be improved about this data. In a text file (to be turned in as part of the assignment):
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Describe five things about this data that are not tidy and how you could fix each of those issues.
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Could this data easily be imported into a programming language or a database in its current form?
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Do you think it’s a good idea to enter the data like this and clean it up later, or to have a good data structure for analysis by the time data is being entered? Why?
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Data entry validation in Excel (50 pts)
You’re starting a new study of small mammals at the NEON site at Ordway-Swisher. Create a spreadsheet in Excel for data entry. It should have four columns: Year, Site, Species, and Mass.
Set the following data validation criteria to prevent any obviously wrong data from getting entered:
- Year must be an integer between 2015 and 2025.
- Site should be one of the following
A1,A2,B1,B2. - Species should be one of the following
Dipodomys spectabilis,Dipodomys ordii,Dipodomys merriami. - Mass should be a decimal greater than or equal to zero but less than or equal to 500 since mass is measured in grams in this study and nothing bigger than half a kilogram will possibly fit into your Sherman traps. Change the error message on this validation criteria to explain why data is invalid and what the valid values are.
Save this file as
yourname_ordway_mammal_data.xlsx.