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. In order 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 need the data. Because this is where most research projects start, this is where we want to start, too!

In this lesson, you will learn:

1. Good data entry practices - formatting data tables in spreadsheets
2. How to avoid common formatting mistakes
3. Approaches for handling dates in spreadsheets
4. Basic quality control and data manipulation in spreadsheets
5. Exporting data from spreadsheets

In this lesson, however, 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 that less data wrangling is needed.

Prerequisites: 

1. This lesson assumes no prior knowledge of the skills or tools.
2. Please bring a laptop to the session (laptops are available for three-hour loans on a first-come, first-served basis at the 1st floor Circulation Desk).
3. Before the session, please download the three data files linked in the setup page, placing them in a location you can easily find and access on your computer (such as a folder on your desktop).

This workshop will follow a Carpentries curriculum. Learn more about Carpentries workshops at Notre Dame.