106 React microcharts, at true size.

A trend over ordered values, small enough to sit in a sentence.

Compact bars for magnitude, or a win–loss streak of outcomes.

A signed change, double-encoded by glyph and color.

A measure against a target and qualitative bands.

Calendar or matrix intensity: the contribution-graph shape.

Which way is this moving? At glyph size, before any number.

What state is this thing in: shape and color paired, never color alone.

One calibrated color step: the building block for host-owned grids.

How far along, exactly: bar plus the percent that is the datum.

Where the raw observations actually sit: distribution without binning.

Which category is biggest, and by roughly how much.

Counts a human can verify by counting: ●●●○○.

When did things happen, and how hard: event density over time.

How intensity evolved, glanceably: the 1×N sibling of ActivityGrid.

A few named values on one scale: minimum ink per comparison.

Where each row started and ended: hollow to filled, no legend.

Actual vs expected, category by category: one shared scale.

Who rose and who fell between two moments: crossings read instantly.

Are these two variables related? The relationship no other type tells.

What is this made of, and in what proportions.

What does the distribution look like? Mode, spread, skew in a cell.

The p50 and spread of a metric: a five-number summary in a row.

How complete is this? At icon size, where a bar doesn't fit.

Roughly what is this made of? An honest, capped concession at icon size.

Where does the pipeline leak? Stage-to-stage conversion in a cell.

Does the response lean agree or disagree, and how hard.

How the deltas compose into the total: P&L in a cell.

Where do we rank, and which way is it moving.

How is this series doing against its benchmark.

How the composition is shifting over time.

Price action per period: open, high, low, close in a cell.

A wide-range series folded into a slim, dense band.

The last few weeks, day by day: real calendar position.

What happened when, and for how long: spans and instants on one row.

Can I trust this data, and where was nothing measured?

Is this value normal for its peer group?

What does the tail look like, not just the median?

How sure are we about this one number?

How likely is this, really? One rate, made countable.

The rate moved, but on what volume?

In versus out, and where does that leave us net?

Do they stay, and does the curve plateau?

Will we finish on time?

Are we burning the error budget too fast to survive the window?

Is the process in control, or did something leave the band?

Will we land where we need to?

What are the odds, in countable form?

Did B beat A, and by more than the overlap?

Did the fix actually change the distribution?

What should we fix first?

What changed between two versions?

Where does it sit in the 2×2?

What repeats beneath the trend?

When did the behavior change level?

What could happen, across the futures?

Which vintage retains worst, compared at equal maturity.

The current run against the record, with the texture of every streak and break.

Is the backlog draining or growing?

Which of two series leads, by how much, and since when.

Is this entity's standing rising or slipping inside the pack?

How many, counted the way a human counts.

A small count or severity, read instantly as a die face.

Progress on a named task, where the label is the bar.

Which numbers in a dense column are big, before you read them.

Where a value sits on a calibrated range, and how close to the goal.

How far through a cycle or period: readable across cultures.

How much time is gone and how much remains, both at once.

Which of two sides outweighs, and roughly by how much.

How mature or healthy is each item in a small set.

The rhythm of activity over time: legible in grayscale and print.

Roughly how a few magnitudes compare. For precise comparison, use MiniBar.

The shape of a short series, read as a melody.

How growth accumulated, period over period, from the centre out.

How groups compare on size, and how activated each is.

How many of the available slots are taken.

When the rare events happened, and how big.

The shape of a day or week cycle.

How the year breathed: seasonality at a glance.

How loaded the system is right now, ambiently.

Is it alive, and how busy? Instantly.

Where the value is now, and where it has just been.

How slow and how busy is this dependency right now?

How hard the route is, and where: pitches coloured by grade, the steepest called out.

How much of the period stayed inside the corridor, and which side it missed on.

Which discrete state the system was in over time, and how choppy the transitions were.

How long this will actually take, given how it has actually been going.

The shape of a high-frequency signal, where its spikes and silences are, at word width.

When each source fired, and whether sources fire together, in sequence, or not at all.

How a thing scored per criterion, with each criterion's weight visible, no fake total.

Which parts of generated text you should double-check: the text is the chart.

Which way it's flowing and roughly how hard, in one character.

An entity's profile across a few metrics, and which one in a set is the odd one out.

Where am I in the whole, and where in the whole is everything else I care about.

Is the level compliant against its target, right now and on average: spikes vs drift.

How much pressure is stacked on each side of the current level, and how wide the gap is.

What the whole is made of, and what the big parts are made of, with parentage visible.

When a model says 70%, does it happen 70% of the time, and is there enough data to ask.

Where the errors go: the one thing accuracy-as-a-number hides.

What a typical period looks like, and whether the current one is typical.

At which level did activity concentrate, not when.

How two coupled signals move together: loops, regimes, and where the system is now.

Where the latency went: which spans, at which depth, on the path that set the total.

The level now, the zone it's in, and how fast it's moving, with the eye parked in one place.

A whole weather observation in one character: sky, wind, temperature, dew point, pressure.

Who's winning, and when did the lead flip?

Do two ways of measuring the same thing systematically disagree?