Tables

Data organisation: tables structure raw data into a more digestible format.
Information retrieval: tables allow users to quickly locate specific information within large datasets.
Data comparison: tables allow users to easily compare data points across different records and attributes.
Action execution: provides a platform to perform actions on data, such as editing, deleting, or exporting multiple entries at once.

Presenting complex data: tables are an efficient way to display large amounts of data in a compact and digestible format.
Improving clarity: a well-designed table enhances clarity, making information easier to understand and analyse.
Reducing cognitive load: clear table design reduces the mental effort required for users to decipher data, which can decrease stress and fatigue.
Supporting key user tasks: effective tables are designed to support common user tasks, including finding specific records, comparing data, and taking actions on multiple items.

Use different text styles and backgrounds to establish a visual hierarchy and make data easier to scan.
Choose row styles that facilitate scanning and parsing of data.
Employ visual elements like color-coded backgrounds or data bars to provide organisational context and highlight key information.
Align numerical data to the right for easier comparison and text data to the left for readability.
Use tabular (monospaced) fonts for numbers to ensure consistent spacing and alignment.
Include sufficient padding between cells to improve spacing and readability.
Select an appropriate line height for your data and use subtext to provide helpful context without clutter.
Split large datasets into an overview and a details view to avoid overwhelming users with too much information at once.
Include an actions column with icons or buttons for users to perform tasks on records.
Provide search and advanced search options to help users quickly find specific data within large datasets.

Avoid wide tables that require horizontal scrolling. Where horizontal scrolling is unavoidable, ensure it is minimal, as this creates a jerky and disorienting experience.
Remove any visual clutter that distracts the user from the data.
Avoid slow loading tables. Work with developers to ensure tables load quickly, providing an efficient user experience

Use semantic HTML Structure
Keep tables simple. Avoid complex tables with merged, split, or nested cells, as they are difficult for screen readers to interpret.
Include a clear header row. The first row should clearly state the information contained in each column to provide context.
Add a descriptive caption/summary. Explain the table’s purpose so users can determine if they want to read the full data.
Provide sufficient color contrast. Ensure the text has a high enough contrast ratio against its background for readability.
Style headers for clarity. Make header cells visually distinct from data cells through styling.
Use zebra stripes. Implement alternate background colors for rows or columns to improve visual scanning and readability.
Don’t use tables for layout. Use CSS for page layouts instead, as tables are for displaying data, not organizing content.

Overview