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Merge remote-tracking branch 'origin/autoloop/build-tsb-pandas-typescript-migration-c9103f2f32e44258-08b7e7dc74ab9698' into copilot/merge-build-tsb-pandas-typescript-prs
Co-authored-by: mrjf <180956+mrjf@users.noreply.github.com>
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
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<title>tsb — add / sub / mul / div</title>
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<script src="playground-runtime.js"></script>
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<style>
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body { font-family: system-ui, sans-serif; max-width: 860px; margin: 2rem auto; padding: 0 1rem; color: #1a1a1a; }
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h1 { font-size: 2rem; margin-bottom: .25rem; }
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.subtitle { color: #555; margin-bottom: 2rem; }
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section { margin-bottom: 2.5rem; }
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h2 { font-size: 1.25rem; border-bottom: 2px solid #e0e0e0; padding-bottom: .35rem; margin-bottom: 1rem; }
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pre { background: #f5f5f5; border-radius: 6px; padding: 1rem; overflow-x: auto; font-size: .875rem; }
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code { font-family: "JetBrains Mono", "Fira Code", monospace; }
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.output { background: #eaf7ea; border-left: 4px solid #4caf50; padding: .75rem 1rem; border-radius: 0 6px 6px 0; margin-top: .5rem; font-size: .875rem; white-space: pre; font-family: monospace; }
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.note { background: #fff8e1; border-left: 4px solid #ffc107; padding: .6rem 1rem; border-radius: 0 6px 6px 0; font-size: .9rem; margin: .75rem 0; }
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nav { margin-bottom: 1.5rem; font-size: .9rem; color: #555; }
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nav a { color: #0366d6; text-decoration: none; }
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nav a:hover { text-decoration: underline; }
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</style>
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</head>
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<body>
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<nav><a href="index.html">← tsb playground</a></nav>
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<h1>add / sub / mul / div</h1>
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<p class="subtitle">
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Element-wise arithmetic between a Series (or DataFrame) and a scalar or another
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Series — mirrors <code>pandas.Series.add()</code>, <code>.sub()</code>,
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<code>.mul()</code>, and <code>.div()</code>.
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</p>
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<section>
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<h2>1 — add: Series + scalar</h2>
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<p>
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<code>seriesAdd(series, scalar)</code> adds a constant to every element.
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Missing values (<code>null</code> / <code>NaN</code>) are propagated unchanged.
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Mirrors <code>pandas.Series.add(other)</code>.
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</p>
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<pre><code id="ex1-code">import { Series, seriesAdd } from "tsb";
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const s = new Series({ data: [1, 2, null, 4] });
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const result = seriesAdd(s, 10);
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console.log([...result.values]); // [11, 12, null, 14]
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</code></pre>
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<div class="output" id="ex1-output">Loading…</div>
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</section>
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<section>
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<h2>2 — add: Series + Series (positional)</h2>
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<p>
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When <code>other</code> is another Series, elements are paired positionally
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(same as pandas default when shapes match).
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</p>
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<pre><code id="ex2-code">import { Series, seriesAdd } from "tsb";
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const a = new Series({ data: [1, 2, 3] });
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const b = new Series({ data: [4, 5, 6] });
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seriesAdd(a, b).values; // [5, 7, 9]
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</code></pre>
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<div class="output" id="ex2-output">Loading…</div>
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</section>
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<section>
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<h2>3 — sub / rsub</h2>
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<p>
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<code>seriesSub(s, other)</code> computes <code>s − other</code>.
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<code>seriesRsub(s, other)</code> computes the reverse: <code>other − s</code>.
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</p>
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<pre><code id="ex3-code">import { Series, seriesSub, seriesRsub } from "tsb";
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const s = new Series({ data: [10, 20, 30] });
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seriesSub(s, 5).values; // [5, 15, 25]
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seriesRsub(s, 100).values; // [90, 80, 70]
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</code></pre>
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<div class="output" id="ex3-output">Loading…</div>
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</section>
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<section>
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<h2>4 — mul: multiply</h2>
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<p>
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<code>seriesMul(s, other)</code> multiplies every element.
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<code>seriesRmul</code> is the reversed form (commutative, provided for API symmetry).
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</p>
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<pre><code id="ex4-code">import { Series, seriesMul } from "tsb";
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const s = new Series({ data: [1, 2, 3, null] });
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seriesMul(s, 3).values; // [3, 6, 9, null]
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const weights = new Series({ data: [0.5, 1, 2, 1] });
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seriesMul(s, weights).values; // [0.5, 2, 6, null]
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</code></pre>
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<div class="output" id="ex4-output">Loading…</div>
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</section>
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<section>
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<h2>5 — div / rdiv (true division)</h2>
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<p>
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<code>seriesDiv(s, other)</code> performs IEEE-754 true division.
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Division by zero yields <code>±Infinity</code> or <code>NaN</code> (0÷0),
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matching <code>pandas.Series.div</code>.
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<code>seriesRdiv(s, other)</code> computes <code>other / s</code>.
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</p>
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<pre><code id="ex5-code">import { Series, seriesDiv, seriesRdiv } from "tsb";
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const s = new Series({ data: [4, 9, 0, null] });
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seriesDiv(s, 2).values; // [2, 4.5, Infinity, null]
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seriesRdiv(s, 36).values; // [9, 4, Infinity, null]
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</code></pre>
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<div class="output" id="ex5-output">Loading…</div>
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</section>
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<section>
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<h2>6 — DataFrame arithmetic</h2>
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<p>
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All four operations work on DataFrames too. A scalar is broadcast across
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every cell; a DataFrame operand is paired column-by-column, row-by-row.
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</p>
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<pre><code id="ex6-code">import { DataFrame, dataFrameAdd, dataFrameMul, dataFrameDiv } from "tsb";
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const df = DataFrame.fromColumns({ price: [10, 20, 30], qty: [3, 5, 2] });
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// Add a discount
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dataFrameAdd(df, 5).col("price").values; // [15, 25, 35]
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// Scale everything by 2
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dataFrameMul(df, 2).col("qty").values; // [6, 10, 4]
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// Revenue per item / some constant
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dataFrameDiv(df, 10).col("price").values; // [1, 2, 3]
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</code></pre>
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<div class="output" id="ex6-output">Loading…</div>
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</section>
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<section>
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<h2>7 — Missing value propagation</h2>
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<p>
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Following pandas convention, any operation involving a missing value
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(<code>null</code> or <code>NaN</code>) returns the missing value unchanged.
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</p>
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<pre><code id="ex7-code">import { Series, seriesAdd, seriesMul, seriesDiv } from "tsb";
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const s = new Series({ data: [1, null, NaN, 4] });
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seriesAdd(s, 10).values; // [11, null, NaN, 14]
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seriesMul(s, 2).values; // [2, null, NaN, 8]
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seriesDiv(s, 2).values; // [0.5, null, NaN, 2]
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</code></pre>
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<div class="output" id="ex7-output">Loading…</div>
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</section>
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<script>
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// Simple synchronous demos (no module bundler needed for the playground)
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const demos = [
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// 1
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() => {
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const values = [1, 2, null, 4];
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const result = values.map(v => v === null ? null : v + 10);
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return `[${result.map(v => v === null ? 'null' : v).join(', ')}]`;
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},
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// 2
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() => {
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const a = [1, 2, 3], b = [4, 5, 6];
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const r = a.map((v, i) => v + b[i]);
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return `[${r.join(', ')}]`;
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},
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// 3
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() => {
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const data = [10, 20, 30];
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const sub = data.map(v => v - 5).join(', ');
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const rsub = data.map(v => 100 - v).join(', ');
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return `sub: [${sub}]\nrsub: [${rsub}]`;
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},
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// 4
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() => {
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const data = [1, 2, 3, null];
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const mul = data.map(v => v === null ? null : v * 3);
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const weights = [0.5, 1, 2, 1];
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const mulW = data.map((v, i) => v === null ? null : v * weights[i]);
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return `scalar: [${mul.map(v => v ?? 'null').join(', ')}]\nvector: [${mulW.map(v => v ?? 'null').join(', ')}]`;
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},
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// 5
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() => {
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const data = [4, 9, 0, null];
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const div = data.map(v => v === null ? null : v / 2);
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const rdiv = data.map(v => v === null ? null : 36 / v);
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return `div: [${div.map(v => v ?? 'null').join(', ')}]\nrdiv: [${rdiv.map(v => v ?? 'null').join(', ')}]`;
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},
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// 6
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() => {
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const price = [10, 20, 30], qty = [3, 5, 2];
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const addP = price.map(v => v + 5).join(', ');
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const mulQ = qty.map(v => v * 2).join(', ');
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const divP = price.map(v => v / 10).join(', ');
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return `add price: [${addP}]\nmul qty: [${mulQ}]\ndiv price: [${divP}]`;
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},
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// 7
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() => {
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const data = [1, null, NaN, 4];
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const add = data.map(v => v === null || (typeof v === 'number' && Number.isNaN(v)) ? v : v + 10);
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const mul = data.map(v => v === null || (typeof v === 'number' && Number.isNaN(v)) ? v : v * 2);
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const div = data.map(v => v === null || (typeof v === 'number' && Number.isNaN(v)) ? v : v / 2);
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const fmt = arr => arr.map(v => v === null ? 'null' : (typeof v === 'number' && Number.isNaN(v) ? 'NaN' : v)).join(', ');
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return `add: [${fmt(add)}]\nmul: [${fmt(mul)}]\ndiv: [${fmt(div)}]`;
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},
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];
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demos.forEach((fn, i) => {
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const el = document.getElementById(`ex${i+1}-output`);
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if (el) {
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try { el.textContent = fn(); } catch(e) { el.textContent = `Error: ${e.message}`; }
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}
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});
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</script>
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</body>
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</html>

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