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jarrodmillman · jarrodmillman · commit 5569970a04ae · 2024-03-12T15:55:33.000Z
diff --git a/index.html b/index.html
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 </a><a href=/news class="navbar-item is-secondary">News
 </a><a href=/contribute class="navbar-item is-secondary">Contribute</a><div class="navbar-item has-dropdown is-hoverable"><a aria-label="Select language" class=navbar-link>English</a><div class=navbar-dropdown><a href=/pt/ class=navbar-item>Português
 </a><a href=/ja/ class=navbar-item>日本語 (Japanese)</a></div></div></div></div></div></nav><section class=hero><div class=hero-container><div class=hero-content><div class=hero-title-content><div class=hero-title>NumPy
-<img class=hero-logo src=/images/logo.svg alt="NumPy logo. "></div><div class=flex-column><div class=hero-subtitle>The fundamental package for scientific computing with Python</div><div class=hero-cta><a href=/news/#releases><button class=cta-button>Latest release: NumPy 1.26. View all releases</button></a></div></div></div></div></div></section><div class=news-container><div class=news-title><a href=/news>NumPy 1.26.0 released</a></div><div class=news-date><a href=/news>2023-09-16</a></div></div><section class="article content-padding"><div class=content-container><div class=article-content><div class="sd-container-fluid sd-mb-4"><div class="sd-row sd-row-cols-1 sd-row-cols-xs-1 sd-row-cols-sm-2 sd-row-cols-md-2 sd-row-cols-lg-3 sd-g-2 sd-g-xs-1 sd-g-sm-2 sd-g-md-2 sd-g-lg-3"><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">Powerful N-dimensional arrays</div>Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today.</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">Numerical computing tools</div>NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more.</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">Open source</div>Distributed under a liberal <a href=https://github.com/numpy/numpy/blob/main/LICENSE.txt>BSD license</a>, NumPy is developed and maintained <a href=https://github.com/numpy/numpy>publicly on GitHub</a> by a vibrant, responsive, and diverse <a href=/community/>community</a>.</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">Interoperable</div>NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries.</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">Performant</div>The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code.</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">Easy to use</div>NumPy&rsquo;s high level syntax makes it accessible and productive for programmers from any background or experience level.</div></div></div></div></div></div></div></section><div class=hero-right><div class="flex-column shell-title-container"><div class=shell-title>Try NumPy</div><div class=shell-content-message><p>Use the interactive shell to try NumPy in the browser</p></div></div><div class=numpy-shell-canvas><div class=numpy-shell-container><div class="shell-lesson shell-content"><div class=highlight><pre class=chroma><code><span style=display:flex><span><span style=color:#e6db74>&#34;&#34;&#34;
+<img class=hero-logo src=/images/logo.svg alt="NumPy logo. "></div><div class=flex-column><div class=hero-subtitle>The fundamental package for scientific computing with Python</div><div class=hero-cta><a href=/news/#releases><button class=cta-button>Latest release: NumPy 1.26. View all releases</button></a></div></div></div></div></div></section><div class=news-container><div class=news-title><a href=/news>NumPy 1.26.0 released</a></div><div class=news-date><a href=/news>2023-09-16</a></div></div><section class="article content-padding"><div class=content-container><div class=article-content><div class="sd-container-fluid sd-mb-4 false"><div class="sd-row sd-row-cols-1 sd-row-cols-xs-1 sd-row-cols-sm-2 sd-row-cols-md-2 sd-row-cols-lg-3 sd-g-2 sd-g-xs-1 sd-g-sm-2 sd-g-md-2 sd-g-lg-3"><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">Powerful N-dimensional arrays</div>Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today.</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">Numerical computing tools</div>NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more.</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">Open source</div>Distributed under a liberal <a href=https://github.com/numpy/numpy/blob/main/LICENSE.txt>BSD license</a>, NumPy is developed and maintained <a href=https://github.com/numpy/numpy>publicly on GitHub</a> by a vibrant, responsive, and diverse <a href=/community/>community</a>.</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">Interoperable</div>NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries.</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">Performant</div>The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code.</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">Easy to use</div>NumPy&rsquo;s high level syntax makes it accessible and productive for programmers from any background or experience level.</div></div></div></div></div></div></div></section><div class=hero-right><div class="flex-column shell-title-container"><div class=shell-title>Try NumPy</div><div class=shell-content-message><p>Use the interactive shell to try NumPy in the browser</p></div></div><div class=numpy-shell-canvas><div class=numpy-shell-container><div class="shell-lesson shell-content"><div class=highlight><pre class=chroma><code><span style=display:flex><span><span style=color:#e6db74>&#34;&#34;&#34;
 </span></span></span><span style=display:flex><span><span style=color:#e6db74>To try the examples in the browser:
 </span></span></span><span style=display:flex><span><span style=color:#e6db74>1. Type code in the input cell and press
 </span></span></span><span style=display:flex><span><span style=color:#e6db74>   Shift + Enter to execute
diff --git a/ja/index.html b/ja/index.html
@@ -8,7 +8,7 @@
 </a><a href=/ja/news class="navbar-item is-secondary">ニュース
 </a><a href=/ja/contribute class="navbar-item is-secondary">NumPyに貢献する</a><div class="navbar-item has-dropdown is-hoverable"><a aria-label="Select language" class=navbar-link>日本語 (Japanese)</a><div class=navbar-dropdown><a href=/ class=navbar-item>English
 </a><a href=/pt/ class=navbar-item>Português</a></div></div></div></div></div></nav><section class=hero><div class=hero-container><div class=hero-content><div class=hero-title-content><div class=hero-title>NumPy
-<img class=hero-logo src=/images/logo.svg alt="NumPy logo. "></div><div class=flex-column><div class=hero-subtitle>Pythonによる科学技術計算の基礎パッケージ</div><div class=hero-cta><a href=/ja/news/#releases><button class=cta-button>最新リリース: Numpy 1.26. すべてのリリースを表示する</button></a></div></div></div></div></div></section><div class=news-container><div class=news-title><a href=/news>NumPy 1.26.0 がリリースされました。</a></div><div class=news-date><a href=/news>2023-09-16</a></div></div><section class="article content-padding"><div class=content-container><div class=article-content><div class="sd-container-fluid sd-mb-4"><div class="sd-row sd-row-cols-1 sd-row-cols-xs-1 sd-row-cols-sm-2 sd-row-cols-md-2 sd-row-cols-lg-3 sd-g-2 sd-g-xs-1 sd-g-sm-2 sd-g-md-2 sd-g-lg-3"><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">強力な多次元配列</div>NumPyの高速で多機能なベクトル化計算、インデックス処理、ブロードキャストの考え方は、現在の配列計算におけるデファクト・スタ>ンダードです。</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">数値計算ツール群</div>NumPyは、様々な数学関数、乱数生成器、線形代数ルーチン、フーリエ変換などを提供しています。</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">相互運用性</div>NumPyは、幅広いハードウェアとコンピューティング・プラットフォームをサポートしており、分散処理、GPU、疎行列ライブラリにも対
+<img class=hero-logo src=/images/logo.svg alt="NumPy logo. "></div><div class=flex-column><div class=hero-subtitle>Pythonによる科学技術計算の基礎パッケージ</div><div class=hero-cta><a href=/ja/news/#releases><button class=cta-button>最新リリース: Numpy 1.26. すべてのリリースを表示する</button></a></div></div></div></div></div></section><div class=news-container><div class=news-title><a href=/news>NumPy 1.26.0 がリリースされました。</a></div><div class=news-date><a href=/news>2023-09-16</a></div></div><section class="article content-padding"><div class=content-container><div class=article-content><div class="sd-container-fluid sd-mb-4 false"><div class="sd-row sd-row-cols-1 sd-row-cols-xs-1 sd-row-cols-sm-2 sd-row-cols-md-2 sd-row-cols-lg-3 sd-g-2 sd-g-xs-1 sd-g-sm-2 sd-g-md-2 sd-g-lg-3"><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">強力な多次元配列</div>NumPyの高速で多機能なベクトル化計算、インデックス処理、ブロードキャストの考え方は、現在の配列計算におけるデファクト・スタ>ンダードです。</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">数値計算ツール群</div>NumPyは、様々な数学関数、乱数生成器、線形代数ルーチン、フーリエ変換などを提供しています。</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">相互運用性</div>NumPyは、幅広いハードウェアとコンピューティング・プラットフォームをサポートしており、分散処理、GPU、疎行列ライブラリにも対
 応しています。</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">高パフォーマンス</div>NumPyの大部分は最適化されたC言語のコードで構成されています。これによりPythonの柔軟性とコンパイルされたコードの高速性の両方
 を享受できます。</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">使いやすさ</div>NumPyの高水準なシンタックスは、どんなバックグラウンドや経験を持つのプログラマーでも簡単に利用することができ、生産性を高め>ることができます。</div></div></div><div class="sd-col sd-d-flex-row"><div class="sd-card sd-w-100 sd-shadow-sm"><div class=sd-card-body><div class="sd-card-title sd-font-weight-bold">オープンソース</div>NumPyは、寛容な<a href=https://github.com/numpy/numpy/blob/main/LICENSE.txt>BSDライセンス</a>で公開されています。NumPyは活発で、互>いを尊重し、多様性を認め合う<a href=/ja/community>コミュニティ</a>によって、 <a href=https://github.com/numpy/numpy>GitHub</a>上でオープンに開発されていま
 す.</div></div></div></div></div></div></div></section><div class=hero-right><div class="flex-column shell-title-container"><div class=shell-title>NumPy を試す</div><div class=shell-content-message><p>インタラクティブシェルを使用して、ブラウザ上で Numpy を試してみてください。</p></div></div><div class=numpy-shell-canvas><div class=numpy-shell-container><div class="shell-lesson shell-content"><div class=highlight><pre class=chroma><code><span style=display:flex><span><span style=color:#e6db74>&#34;&#34;&#34;
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