Learn how to use conditional formatting to quickly explore your data and find initial patterns.
Tutorials about exploring the data include:
- How to automatically color-code your cells
- Highlighting Blank Cells
- Top/Bottom Rules: Example 1 and Example 2
- How to create Data Bars
Or, watch the entire exploring playlist in YouTube.
How to automatically color-code your cells
Learn how to use conditional formatting to automatically color-code specific response options in a satisfaction survey.
Highlighting Blank Cells
Collecting and using data is hard work! You’re bound to run into some situations where you are missing data. Maybe the program participants skipped a survey question because they didn’t understand the wording, or maybe the program staff forgot to enter the information into your nonprofit’s database. Either way, you need to know how much missing data you’re dealing with so you can find a solution. In this tutorial, you’ll learn how to automatically color-code your blank cells to visualize how much missing data you’re dealing with.
Top/Bottom Rules: Example 1
Automatically color-code cells to scan for patterns in your dataset.
Top/Bottom Rules: Example 2
Color-code scores and then calculate r to measure the correlation between pretest and posttest scores.
How to create Data Bars
The ultimate purpose of data analysis and evaluation is to share findings with other leaders at your organization and use that information to make adjustments and improvements. You don’t need a lot of data, and the analyses don’t have to be complicated or time-consuming. Sometimes the simplest data are the most useful. Here’s an example where I created data bars — miniature within-cell bar charts — to quickly compare each youth’s pretest score and posttest score.
Return to top