Good data organization is the foundation of any research project. Most researchers have data in spreadsheets, so it's the place that many research projects start. Typically, we organize data in spreadsheets in ways that we as humans want to work with the data. However computers require data to be organized in particular ways. To use tools that make computation more efficient, such as programming languages like R or Python, we need to structure our data the way that computers can read the data.
In this hands-on workshop, you will learn:
Good data entry practices - formatting data tables in spreadsheets
How to avoid common formatting mistakes
Approaches for handling dates in spreadsheets
Basic quality control and data manipulation in spreadsheets
Exporting data from spreadsheets
You will not learn about data analysis with spreadsheets. Much of your time as a researcher will be spent in the initial "data wrangling' stage, where you need to organize the data to perform a proper analysis later. It's not the most fun, but it is necessary. In this lesson you will learn how to think about data organization and some practices for more effective data wrangling. With this approach you can better format current data and plan new data collection so less data wrangling is needed.