##Organizing data tables
Goals for this lesson
- understand tradeoffs between human and machine readability
- understand some common errors students often make when creating data tables
- never make another terrible data table again
Okay, I know this seems crazy. But I think about data table formatting a lot. I know from lots of personal experience that the single most challenging aspect of a typical workflow in science is getting your stats program to understand what your data are. Working through data formatting problems were the catalyst for me getting into the open science community.
I think organismal ecologists are often at a disadvantage here. Data formatting and spreadsheet management are very rarely explicitly taught, but in many other fields, there is some degree of automation in data collection- machines process the samples and create data tables. But using a few simple guidelines when you design your data tables can save you so, so much time and frustration down the road.
In this class, we will work through the Data Carpentry lesson on spreadsheets for ecology. A link to a deliciously messy data set is here.
Resources:
- I tried to find a funny video about spreadsheets for you guys but all the spreadsheet videos are so not funny
- please, PR something better here, I implore you.
- Advice on research data mamagement- a storify
- Ten Commandments for entering data to use in R
- Nine simple ways to make it easier to (re)use your data