Complex data deserves multiple view modes — grid, list, table — chosen by the user based on their task. Row and item selection should use large hit areas (the whole row or card, not just a checkbox). Selected state is communicated through a subtle background colour shift. Mass actions appear when items are selected. Use when designing data tables, product listings, file browsers, or any multi-item collection.
Complex data deserves multiple view modes — grid, list, table — chosen by the user based on their task. Row and item selection should use large hit areas (the whole row or card, not just a checkbox). Selected state is communicated through a subtle background colour shift. Mass actions appear when items are selected. Use when designing data tables, product listings, file browsers, or any multi-item collection.
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Data Display and Selection
Complex data collections — products, files, users, orders, tasks — have no single correct view. Different tasks call for different views. Browsing benefits from grid; comparing details benefits from list or table; bulk management benefits from a dense table with mass actions. Give users the choice.
View Modes
Offer multiple views when the data has both visual and detailed dimensions.
View
Best for
When to default
Grid
Visual items: products, images, files, cards
When items are visually distinct and browsing is the primary task
List
Moderate detail: tasks, emails, articles
When a key piece of text or metadata drives selection
Table
Dense data: orders, reports, user management
When multiple columns of data must be compared
View toggle placement: top-right of the collection, adjacent to sort/filter controls. Use icon buttons with tooltips (grid, list, table). Persist the user's choice in localStorage.
[Filter ▾] [Sort ▾] [⊞ Grid] [☰ List] [⊟ Table]
On mobile, collapse to the view that works best for the content — grid for visual items, list for text. Do not offer a view toggle on small screens unless both views are genuinely usable.
Selection: Prefer Large Hit Areas
Checkboxes are small targets. Requiring users to hit a 16×16px checkbox to select a row is unnecessary friction — especially on touch devices.
Default: the entire row or card is the selection target.
Click anywhere on the row → selects the row (background shifts, checkbox checks)
The checkbox is a visual indicator of selection state, not the only way to select
Keyboard: Space selects the focused row; Shift+click extends selection; Ctrl/Cmd+click toggles individual items
Lead with the selection count: "3 selected" — confirms the scope before any action
Show only actions applicable to the selection — if some actions require a single item, disable them for multi-select
"Clear" deselects everything and dismisses the toolbar
Destructive mass actions (Delete) always trigger a confirm dialog naming the count: "Delete 3 projects? This cannot be undone."
Select all: A checkbox in the table header selects all items on the current page. A secondary action "Select all 247" extends to the full dataset.
[☑ Select all on page] → [Select all 247 results]
Sorting and Filtering
Column sorting (table view)
Click a column header to sort ascending; click again for descending; third click clears sort
Active sort column shows a directional arrow (↑ ↓)
Only sortable columns are clickable — non-sortable columns have no hover state on header
Filters
Persistent filters belong in a sidebar or filter bar above the collection
Active filters should be visible as chips/tags that can be individually removed
"Clear all filters" removes all active filters in one action
Filter count badge on the filter button when filters are active: Filter (3)
Empty states
No results from filter: "No results for these filters. [Clear filters]" — do not show a generic empty state
Genuinely empty collection: show a call to action for the first item: "No projects yet. [Create project]"
Search and Autocomplete
Search is how users find one thing in a large set, so it must feel instant and recognisable.
Suggest from the first keystrokes. Start returning results after 1 character, at most 2–3 — don't make the user finish typing or press enter to see anything. Results appear live in a dropdown as they type.
Make a valid result recognisable at a glance. The whole point of a suggestion list is that the user spots their result in a long list without reading every row. Give each result more than a bare string:
a thumbnail/image where the item is visual (products, people, files),
the category / area it belongs to, and for typed domains (products, spare parts, services) a category icon and colour so the type is legible before the label is read — find good brand-appropriate icons for these result types (see [[brand-visual-language]]),
the matched text highlighted within the result.
This is a soft rule — not every search needs images — but the goal is constant: the user should identify the right result out of many, fast (reading is time — see [[ui-density]]).
Give a way out to the full results. The dropdown is a shortcut, not the whole story. Always offer "See all results for '…'", opening a full listing/results page with filters (the collection patterns above) for when the quick suggestions aren't enough.
Fully keyboard-navigable. Arrow keys move through suggestions, Enter selects, Esc closes — and it must all work by mouse too. Search is a power-user path; don't force the hand off the keyboard.
Table-Specific Patterns
Sticky header
Table column headers stick to the top when scrolling vertically — users must always be able to see what each column means.
Sticky first column
For wide tables that scroll horizontally, the first column (row identifier — name, ID) sticks to the left.
Row actions
Per-row actions (Edit, Delete, View) appear on hover in the rightmost column. Do not show them at rest — they add visual noise.
[Name] [Status] [Date] [Amount] ← at rest
[Name] [Status] [Date] [Amount] [Edit] [⋯] ← on hover
Column resize and reorder
For enterprise data tables: allow columns to be resized by dragging the header border, and reordered by dragging the header. Persist the layout.
Making Numbers Comprehensible
A raw number is hard to judge on its own — "1,240 users" or "€48,900" means little without a reference. Presenting data is not just laying out the figures; it is giving them the context and shape that let a user understand them at a glance.
Give a number a reference. A bare value communicates far less than a value with a baseline: a percentage, an average, a delta, or a comparison. "€48,900 (+12% vs last month)", "72% of target", "avg 3.4 per user" — the comparison is usually the insight, not the absolute figure.
Visualise when the story is a pattern. Reach for a graph when the message is a trend, distribution, comparison, or relationship the eye reads faster than a column of digits. A single KPI can pair with a sparkline; a set of categories reads better as a bar chart than a table. A table is for looking up exact values; a chart is for seeing the shape.
Show time-series for anything that evolves. If a value lives and changes over time — revenue, usage, a status history — present its trajectory, not just the current snapshot. A trend line answers "is this getting better or worse?" that a single number never can. Whenever something is time-dependent, consider showing its history alongside its current value.
Choose familiar, widely-understood chart types. Pick the chart most people already know how to read — bar, line, area, pie/donut, sparkline — over an exotic one (sankey, radar, chord, treemap) that looks impressive but forces the user to learn the chart before they can read the data. Novelty in a chart type is a tax on comprehension; spend it only when a common chart genuinely can't tell the story.
Limited, semantic palette. At most 2–3 colours; each means exactly one thing (see [[status-colors-and-errors]]). Traffic-light or a known convention (brand-primary vs grey). Need more distinctions? Add a legend or tooltips — don't add hues. Chart craft (axes, legends, light/dark): dataviz. Pairing a chart with its table: [[coordinated-data-views]].
Review Checklist
Is a view mode toggle offered when data has both visual and detail dimensions?
Is the user's preferred view persisted across sessions?
Is the entire row or card the selection hit area — not just the checkbox?
Does selected state use a subtle background colour shift (--color-primary-subtle)?
Does a mass action toolbar appear when items are selected, showing the selection count?
Do destructive mass actions require a confirm dialog naming the item count?
Does "Select all" work per page, with an option to extend to the full dataset?
Are active filters visible as removable chips?
Does the empty state differ between "no results" and "genuinely empty"?
Are per-row actions shown on hover only, not at rest?
Is the table header sticky when the table scrolls vertically?
Are key numbers given a reference (%, average, delta, comparison) rather than shown bare?
Is a graph used where the story is a trend/distribution/comparison, and is time-evolving data shown as a time-series, not just a snapshot?
Are chart types familiar and widely understood (bar/line/area/pie/sparkline) rather than exotic ones that must be learned before they can be read?
Does a chart/infographic use a small, semantic palette (≤2–3 colours, traffic-light or a known convention), with each colour meaning one thing — and a legend/tooltips where the encoding isn't self-evident?
