4. Best Practices When Creating Tabular Data

There are a number of best practices to consider when creating tabular data:

• Using contrast effectively
• Do not encode data in font or colours
• Alignment
• Ordering
• Spacing
• Minimizing the amount of information in a cell
• Name consistently

1. Use Contrast Effectively
By using bold, italics, or different font sizes you can help the viewer distinguish aspects of your table. We use a table from Zwar’s (2021) study as an example for best practices when creating tabular data. The table provides the results of a multiple regression analysis in a German study on public stigma towards informal long-term caregivers of older individuals. 

Below is an example of using bold to help viewer distinguish aspects of the table. Here, the use of bold and grey background helps the table headers stand out more clearly.  

Good Practice: Effective Contrast

Bad Practice: Poor Contrast

2. Do Not Encode Data in Font or Colours
Researchers often use colour to encode data, but this is not a good practice for several reasons. For example, it does not readily support analysis of the concept coded by the colour. A common example is shown in the ‘bad’ example below, where a researcher might highlight a value they suspect is an outlier. A better approach is to create a new column where you indicate notes using text to document this issue.

Good Practice

Bad Practice: Use of Colours

3. Alignment
Alignment is important to ensure your table is understandable and neat. Ensure that all numbers/text in columns align with their label heading. Be consistent with your alignment. See examples below of using proper versus inconsistent alignment. We use a table from Zwar’s (2021) study to illustrate our point. The ‘bad’ examples show inconsistent alignment. Note, however, that some journals may have specific style requirements for tables, so you will have to check this prior to submission of a manuscript.

Good Practice: Using Alignment

Bad Practice: No Alignment

4. Ordering
Place items that are similar to one another together in your table. You may want to indent subordinate data when it relates to another column. We use a table from Graphing -Designing Tables (2004) as an example.

5. Spacing
Ensure that you have sufficient ‘white space’ around all values and labels. 

Good Practice:

Bad Practice:

6. Minimizing the Amount of Information in a Cell
Put only one piece of information in each cell to minimize mis-interpretation of the data. In the ‘good’ example, we see that the values for SensMax and SpecMax are each listed in their own column. This practice helps clarify the data and prepares it to be readily analyzed.

7. Name Consistently
Use consistent labels across your data. Do not switch between different spellings or encodings that have the same meaning. Example: label sex by choosing one of: “female”, “Female”, “F”, “f”, “0” and using it consistently.

Please continue to the next lesson content to identify and learn more about best practices when creating tabular data