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school_compare/nextjs-app/components/PerformanceChart.tsx
TudorandClaude Fable 5 22769b6295
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feat(compare): readable comparison chart on mobile
The compare chart squashed clustered schools into a thin band (y pinned
0-100) under an in-chart title + per-school legend that ate ~40% of a
300px card, leaving converging lines indistinguishable on phones.

- Auto-fit the y-axis to the data on all viewports (computeYBounds in
  lib/utils: padded + min-span for percentages, symmetric around 0 for
  progress, fitted for scores; negative pct-named trend metrics are not
  zero-clamped).
- Distinct point style per school (circle/triangle/rect/rectRot/star)
  as secondary encoding for convergence and colour-blindness.
- Mobile: drop in-chart title/legend/axis titles; add a chip row (colour
  dot + name) that doubles as tap-to-focus — highlights one school's
  line and dims the rest. Chart card 300px -> 340px, nearly all plot.
- Fix a latent colour mismatch: datasets were built from Object.entries
  whose integer-like URN keys enumerate in ascending numeric order,
  desyncing line colours from card colours; the chart now receives the
  ordered school list.
- Union years across schools instead of taking the first school's.
- Extract PerformanceChart's matchMedia pattern into hooks/useIsMobile.

Unit tests for metricKind/computeYBounds; e2e journey covers the mobile
chips and focus toggle.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-05 22:02:26 +01:00

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/**
* PerformanceChart Component
* Displays school performance data over time using Chart.js.
*
* Desktop: full multi-series chart with dual y-axis (percentage + progress).
* Mobile (≤640px): a chip selector switches the chart between one focused view
* at a time — no dual axis, no legend, auto-scaled y-axis. Designed so the
* actual variation in the data is visible on a phone instead of a flat line.
*/
'use client';
import { useMemo, useState } from 'react';
import { Line } from 'react-chartjs-2';
import { ChartOptions, ChartDataset } from 'chart.js';
import '@/lib/chartSetup';
import type { SchoolResult } from '@/lib/types';
import { formatAcademicYear } from '@/lib/utils';
import { useIsMobile } from '@/hooks/useIsMobile';
import { track } from '@/lib/analytics';
import styles from './PerformanceChart.module.css';
interface NationalByYear {
year: number;
primary: Record<string, number>;
secondary: Record<string, number>;
}
interface PerformanceChartProps {
data: SchoolResult[];
schoolName: string;
isSecondary?: boolean;
nationalRwmAvg?: number | null;
nationalAtt8Avg?: number | null;
nationalByYear?: NationalByYear[];
}
const COVID_YEARS = new Set([201920, 202021]);
// Mobile chip definitions: which datasets render when each chip is active.
// `series` keys reference the dataset labels so we can filter cleanly.
type ChipId = 'expected' | 'higher' | 'progress' | 'attainment8' | 'em_pass' | 'progress8';
interface ChipDef {
id: ChipId;
label: string;
/** Dataset labels (from the desktop dataset list below) this chip surfaces. */
series: string[];
}
const PRIMARY_CHIPS: ChipDef[] = [
{ id: 'expected', label: 'At expected level', series: ['Reading, Writing & Maths expected %', 'National average'] },
{ id: 'higher', label: 'Above expected level', series: ['Exceeding expected level'] },
{ id: 'progress', label: 'Pupil progress', series: ['Reading progress', 'Writing progress', 'Maths progress'] },
];
const SECONDARY_CHIPS: ChipDef[] = [
{ id: 'attainment8', label: 'Attainment 8', series: ['Attainment 8', 'National average'] },
{ id: 'em_pass', label: 'English & Maths grade 4+', series: ['English & Maths Grade 4+'] },
{ id: 'progress8', label: 'Progress 8', series: ['Progress 8'] },
];
export function PerformanceChart({
data,
isSecondary = false,
nationalRwmAvg,
nationalAtt8Avg,
nationalByYear,
}: PerformanceChartProps) {
const sortedData = [...data].sort((a, b) => a.year - b.year);
const years = sortedData.map(d => formatAcademicYear(d.year));
const isMobile = useIsMobile();
// ── Build per-year national averages ─────────────────────────────────
const natRefRwm: (number | null)[] = sortedData.map(d => {
if (nationalByYear) {
const match = nationalByYear.find(n => n.year === d.year);
return match?.primary?.rwm_expected_pct ?? null;
}
return nationalRwmAvg ?? null;
});
const natRefAtt8: (number | null)[] = sortedData.map(d => {
if (nationalByYear) {
const match = nationalByYear.find(n => n.year === d.year);
return match?.secondary?.attainment_8_score ?? null;
}
return nationalAtt8Avg ?? null;
});
const hasNatRwm = natRefRwm.some(v => v != null);
const hasNatAtt8 = natRefAtt8.some(v => v != null);
// ── Trend summary (primary only — references headline metric) ────────
const trendSummary = (() => {
if (isSecondary) return null;
const rwm = sortedData.filter(d => d.rwm_expected_pct != null);
if (rwm.length < 2) return null;
const latest = rwm[rwm.length - 1];
const prev = rwm[rwm.length - 2];
const best = rwm.reduce((a, b) => (b.rwm_expected_pct! > a.rwm_expected_pct! ? b : a));
const latestPct = Math.round(latest.rwm_expected_pct!);
const bestPct = Math.round(best.rwm_expected_pct!);
const delta = latest.rwm_expected_pct! - prev.rwm_expected_pct!;
const arrow = delta > 1 ? '↑' : delta < -1 ? '↓' : '→';
if (best.year === latest.year) {
return `${arrow} Best year on record — ${latestPct}% met the expected standard in Reading, Writing & Maths`;
}
return `${arrow} Reading, Writing & Maths peaked at ${bestPct}% (${formatAcademicYear(best.year)}), currently ${latestPct}%`;
})();
const hasCovidGap = isSecondary
? false
: COVID_YEARS.size > 0 &&
[...COVID_YEARS].some(y => !sortedData.find(d => d.year === y));
// ── Datasets (full set; mobile filters them via the active chip) ─────
const refLineStyle = {
borderColor: 'rgba(90,80,70,0.35)',
backgroundColor: 'transparent',
borderWidth: 1.5,
borderDash: [6, 4] as number[],
pointRadius: 0,
tension: 0,
order: 10,
};
const allDatasets: ChartDataset<'line'>[] = isSecondary ? [
{
label: 'Attainment 8',
data: sortedData.map(d => d.attainment_8_score),
borderColor: '#2d7d7d',
backgroundColor: 'rgba(45,125,125,0.08)',
borderWidth: 2.5,
tension: 0.3,
pointRadius: 4,
pointHoverRadius: 6,
yAxisID: 'y',
},
{
label: 'English & Maths Grade 4+',
data: sortedData.map(d => d.english_maths_standard_pass_pct),
borderColor: '#c9a227',
backgroundColor: 'rgba(201,162,39,0.08)',
borderWidth: 1.5,
tension: 0.3,
pointRadius: 3,
yAxisID: 'y',
},
{
label: 'Progress 8',
data: sortedData.map(d => d.progress_8_score),
borderColor: 'rgb(139,92,246)',
backgroundColor: 'rgba(139,92,246,0.08)',
borderWidth: 1.5,
tension: 0.3,
pointRadius: 3,
hidden: true,
yAxisID: 'y1',
},
...(hasNatAtt8 ? [{
...refLineStyle,
label: 'National average',
data: natRefAtt8,
yAxisID: 'y',
} as ChartDataset<'line'>] : []),
] : [
{
label: 'Reading, Writing & Maths expected %',
data: sortedData.map(d => d.rwm_expected_pct),
borderColor: '#2d7d7d',
backgroundColor: 'rgba(45,125,125,0.08)',
borderWidth: 2.5,
tension: 0.3,
pointRadius: 4,
pointHoverRadius: 6,
yAxisID: 'y',
},
{
label: 'Exceeding expected level',
data: sortedData.map(d => d.rwm_high_pct),
borderColor: '#c9a227',
backgroundColor: 'rgba(201,162,39,0.08)',
borderWidth: 1.5,
tension: 0.3,
pointRadius: 3,
yAxisID: 'y',
},
...(hasNatRwm ? [{
...refLineStyle,
label: 'National average',
data: natRefRwm,
yAxisID: 'y',
} as ChartDataset<'line'>] : []),
{
label: 'Reading progress',
data: sortedData.map(d => d.reading_progress),
borderColor: 'rgb(59,130,246)',
backgroundColor: 'rgba(59,130,246,0.08)',
borderWidth: 1.5,
tension: 0.3,
pointRadius: 3,
hidden: true,
yAxisID: 'y1',
},
{
label: 'Writing progress',
data: sortedData.map(d => d.writing_progress),
borderColor: 'rgb(139,92,246)',
backgroundColor: 'rgba(139,92,246,0.08)',
borderWidth: 1.5,
tension: 0.3,
pointRadius: 3,
hidden: true,
yAxisID: 'y1',
},
{
label: 'Maths progress',
data: sortedData.map(d => d.maths_progress),
borderColor: 'rgb(236,72,153)',
backgroundColor: 'rgba(236,72,153,0.08)',
borderWidth: 1.5,
tension: 0.3,
pointRadius: 3,
hidden: true,
yAxisID: 'y1',
},
];
// ── Mobile chip state + filtered datasets ────────────────────────────
const chips = isSecondary ? SECONDARY_CHIPS : PRIMARY_CHIPS;
// A chip is enabled only if at least one of its series has any real data.
const chipHasData = (chip: ChipDef) =>
chip.series.some(name => {
const ds = allDatasets.find(d => d.label === name);
return ds?.data?.some(v => v != null);
});
const firstEnabledChip = chips.find(chipHasData)?.id ?? chips[0].id;
const [activeChip, setActiveChip] = useState<ChipId>(firstEnabledChip);
const activeChipDef = chips.find(c => c.id === activeChip) ?? chips[0];
const mobileDatasets = useMemo(() => {
return allDatasets
.filter(ds => activeChipDef.series.includes(ds.label ?? ''))
.map(ds => ({ ...ds, hidden: false, yAxisID: 'y' as const }));
}, [activeChipDef, allDatasets]);
// Auto-scale Y axis for the mobile chart so variation is visible.
// For percentage chips: clamp to 0100 but tighten when data sits in a band.
// For progress chips: centre on 0 with a small symmetric range.
const mobileYBounds = useMemo(() => {
const isProgress = activeChip === 'progress' || activeChip === 'progress8';
const values: number[] = mobileDatasets.flatMap(ds =>
(ds.data as Array<number | null | undefined>).filter((v): v is number => typeof v === 'number')
);
if (values.length === 0) return { min: 0, max: 100, isProgress };
const lo = Math.min(...values);
const hi = Math.max(...values);
if (isProgress) {
const reach = Math.max(2, Math.ceil(Math.max(Math.abs(lo), Math.abs(hi)) + 0.5));
return { min: -reach, max: reach, isProgress };
}
// Percentage: leave headroom but never widen below 0 / above 100.
const padded = Math.max(5, Math.round((hi - lo) * 0.2));
return {
min: Math.max(0, Math.floor((lo - padded) / 5) * 5),
max: Math.min(100, Math.ceil((hi + padded) / 5) * 5),
isProgress,
};
}, [activeChip, mobileDatasets]);
// ── Chart options ────────────────────────────────────────────────────
const desktopOptions: ChartOptions<'line'> = {
responsive: true,
maintainAspectRatio: false,
interaction: { mode: 'index', intersect: false },
plugins: {
legend: {
position: 'top',
labels: {
usePointStyle: true,
padding: 14,
font: { size: 12 },
},
},
title: { display: false },
tooltip: {
backgroundColor: 'rgba(26,22,18,0.92)',
padding: 12,
titleFont: { size: 13 },
bodyFont: { size: 12 },
callbacks: {
label: ctx => {
const label = ctx.dataset.label ?? '';
if (ctx.parsed.y == null) return label;
const isProgress = ctx.dataset.yAxisID === 'y1';
const suffix = isProgress ? '' : '%';
return `${label}: ${ctx.parsed.y.toFixed(1)}${suffix}`;
},
},
},
},
scales: {
y: {
type: 'linear', display: true, position: 'left',
title: { display: true, text: isSecondary ? 'Score / %' : 'Percentage (%)', font: { size: 11 } },
min: 0, max: isSecondary ? undefined : 100,
grid: { color: 'rgba(0,0,0,0.05)' },
ticks: { font: { size: 11 } },
},
y1: {
type: 'linear', display: true, position: 'right',
title: { display: true, text: isSecondary ? 'Progress 8' : 'Progress score', font: { size: 11 } },
grid: { drawOnChartArea: false },
ticks: { font: { size: 11 } },
},
x: {
grid: { display: false },
ticks: { font: { size: 11 } },
},
},
};
const mobileOptions: ChartOptions<'line'> = {
responsive: true,
maintainAspectRatio: false,
interaction: { mode: 'index', intersect: false },
plugins: {
legend: { display: false },
title: { display: false },
tooltip: {
backgroundColor: 'rgba(26,22,18,0.92)',
padding: 10,
titleFont: { size: 12 },
bodyFont: { size: 11 },
callbacks: {
label: ctx => {
const label = ctx.dataset.label ?? '';
if (ctx.parsed.y == null) return label;
const suffix = mobileYBounds.isProgress ? '' : '%';
return `${label}: ${ctx.parsed.y.toFixed(1)}${suffix}`;
},
},
},
},
scales: {
y: {
type: 'linear', display: true, position: 'left',
min: mobileYBounds.min, max: mobileYBounds.max,
grid: { color: 'rgba(0,0,0,0.05)' },
ticks: { font: { size: 10 }, maxTicksLimit: 5 },
},
x: {
grid: { display: false },
ticks: { font: { size: 10 }, autoSkip: false },
},
},
};
const subtitle = isSecondary
? 'GCSE results · Year 11'
: 'KS2 SATs · Reading, Writing & Maths';
return (
<div className={styles.chartOuter}>
{trendSummary && (
<div className={styles.trendSummary}>{trendSummary}</div>
)}
{/* Mobile-only chip selector */}
<div className={styles.mobileChips} aria-hidden={!isMobile}>
<div className={styles.mobileSubtitle}>{subtitle}</div>
<div className={styles.chipRow} role="tablist" aria-label="Select metric">
{chips.map(chip => {
const enabled = chipHasData(chip);
const active = chip.id === activeChip;
return (
<button
key={chip.id}
type="button"
role="tab"
aria-selected={active}
disabled={!enabled}
onClick={() => {
if (chip.id !== activeChip) {
track('chart_metric_changed', { chip: chip.id, phase: isSecondary ? 'secondary' : 'primary', viewport: 'mobile' });
}
setActiveChip(chip.id);
}}
className={`${styles.chip}${active ? ` ${styles.chipActive}` : ''}`}
title={!enabled ? 'No data for this school' : undefined}
>
{chip.label}
</button>
);
})}
</div>
</div>
<div className={styles.chartWrapper}>
<Line
data={{ labels: years, datasets: isMobile ? mobileDatasets : allDatasets }}
options={isMobile ? mobileOptions : desktopOptions}
/>
</div>
{/* When the Progress chip is active on primary, show a tiny inline legend
for the 3 sub-series (reading/writing/maths) — they share a unit and
belong together. */}
{isMobile && activeChip === 'progress' && (
<div className={styles.miniLegend}>
<span><span className={styles.miniDot} style={{ background: 'rgb(59,130,246)' }} />Reading</span>
<span><span className={styles.miniDot} style={{ background: 'rgb(139,92,246)' }} />Writing</span>
<span><span className={styles.miniDot} style={{ background: 'rgb(236,72,153)' }} />Maths</span>
</div>
)}
{hasCovidGap && (
<p className={styles.covidNote}>
* No data for 2019/20 or 2020/21 national assessments were cancelled due to COVID-19.
</p>
)}
{/* Desktop-only hint about toggling progress in the legend */}
{!isSecondary && (
<p className={styles.chartHint}>
Progress scores (Reading, Writing, Maths) are hidden by default click them in the legend to show.
</p>
)}
</div>
);
}