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| <link rel="modulepreload" href="/docs/datasets/pr_8021/en/_app/immutable/chunks/CodeBlock.5919a092.js"><!-- HEAD_svelte-u9bgzb_START --><meta name="hf:doc:metadata" content="{"title":"Use with Pandas","local":"use-with-pandas","sections":[{"title":"Dataset format","local":"dataset-format","sections":[],"depth":2},{"title":"Process data","local":"process-data","sections":[],"depth":2},{"title":"Import or Export from Pandas","local":"import-or-export-from-pandas","sections":[],"depth":2}],"depth":1}"><!-- HEAD_svelte-u9bgzb_END --> <p></p> <div class="items-center shrink-0 min-w-[100px] max-sm:min-w-[50px] justify-end ml-auto flex" style="float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"><div class="inline-flex rounded-md max-sm:rounded-sm"><button class="inline-flex items-center gap-1 h-7 max-sm:h-7 px-2 max-sm:px-1.5 text-sm font-medium text-gray-800 border border-r-0 rounded-l-md max-sm:rounded-l-sm border-gray-200 bg-white hover:shadow-inner dark:border-gray-850 dark:bg-gray-950 dark:text-gray-200 dark:hover:bg-gray-800" aria-live="polite"><span class="inline-flex items-center justify-center rounded-md p-0.5 max-sm:p-0 hover:text-gray-800 dark:hover:text-gray-200"><svg class="sm:size-3.5 size-3" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg></span> <span>Copy page</span></button> <button class="inline-flex items-center justify-center w-6 max-sm:w-5 h-7 max-sm:h-7 disabled:pointer-events-none text-sm text-gray-500 hover:text-gray-700 dark:hover:text-white rounded-r-md max-sm:rounded-r-sm border border-l transition border-gray-200 bg-white hover:shadow-inner dark:border-gray-850 dark:bg-gray-950 dark:text-gray-200 dark:hover:bg-gray-800" aria-haspopup="menu" aria-expanded="false" aria-label="Open copy menu"><svg class="transition-transform text-gray-400 overflow-visible sm:size-3.5 size-3 rotate-0" width="1em" height="1em" viewBox="0 0 12 7" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M1 1L6 6L11 1" stroke="currentColor"></path></svg></button></div> </div> <h1 class="relative group"><a id="use-with-pandas" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#use-with-pandas"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Use with Pandas</span></h1> <p data-svelte-h="svelte-rghtkp">This document is a quick introduction to using <code>datasets</code> with Pandas, with a particular focus on how to process | |
| datasets using Pandas functions, and how to convert a dataset to Pandas or from Pandas.</p> <p data-svelte-h="svelte-rzzdyf">This is particularly useful as it allows fast operations, since <code>datasets</code> uses PyArrow under the hood and PyArrow is well integrated with Pandas.</p> <h2 class="relative group"><a id="dataset-format" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#dataset-format"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Dataset format</span></h2> <p data-svelte-h="svelte-ej8pz8">By default, datasets return regular Python objects: integers, floats, strings, lists, etc.</p> <p data-svelte-h="svelte-1vasaf">To get Pandas DataFrames or Series instead, you can set the format of the dataset to <code>pandas</code> using <a href="/docs/datasets/pr_8021/en/package_reference/main_classes#datasets.Dataset.with_format">Dataset.with_format()</a>:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> Dataset | |
| <span class="hljs-meta">>>> </span>data = {<span class="hljs-string">"col_0"</span>: [<span class="hljs-string">"a"</span>, <span class="hljs-string">"b"</span>, <span class="hljs-string">"c"</span>, <span class="hljs-string">"d"</span>], <span class="hljs-string">"col_1"</span>: [<span class="hljs-number">0.</span>, <span class="hljs-number">0.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>]} | |
| <span class="hljs-meta">>>> </span>ds = Dataset.from_dict(data) | |
| <span class="hljs-meta">>>> </span>ds = ds.with_format(<span class="hljs-string">"pandas"</span>) | |
| <span class="hljs-meta">>>> </span>ds[<span class="hljs-number">0</span>] <span class="hljs-comment"># pd.DataFrame</span> | |
| col_0 col_1 | |
| <span class="hljs-number">0</span> a <span class="hljs-number">0.0</span> | |
| <span class="hljs-meta">>>> </span>ds[:<span class="hljs-number">2</span>] <span class="hljs-comment"># pd.DataFrame</span> | |
| col_0 col_1 | |
| <span class="hljs-number">0</span> a <span class="hljs-number">0.0</span> | |
| <span class="hljs-number">1</span> b <span class="hljs-number">0.0</span> | |
| <span class="hljs-meta">>>> </span>ds[<span class="hljs-string">"data"</span>] <span class="hljs-comment"># pd.Series</span> | |
| <span class="hljs-number">0</span> a | |
| <span class="hljs-number">1</span> b | |
| <span class="hljs-number">2</span> c | |
| <span class="hljs-number">3</span> d | |
| Name: col_0, dtype: <span class="hljs-built_in">object</span><!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-2qljfh">This also works for <code>IterableDataset</code> objects obtained e.g. using <code>load_dataset(..., streaming=True)</code>:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span>ds = ds.with_format(<span class="hljs-string">"pandas"</span>) | |
| <span class="hljs-meta">>>> </span><span class="hljs-keyword">for</span> df <span class="hljs-keyword">in</span> ds.<span class="hljs-built_in">iter</span>(batch_size=<span class="hljs-number">2</span>): | |
| <span class="hljs-meta">... </span> <span class="hljs-built_in">print</span>(df) | |
| <span class="hljs-meta">... </span> <span class="hljs-keyword">break</span> | |
| col_0 col_1 | |
| <span class="hljs-number">0</span> a <span class="hljs-number">0.0</span> | |
| <span class="hljs-number">1</span> b <span class="hljs-number">0.0</span><!-- HTML_TAG_END --></pre></div> <h2 class="relative group"><a id="process-data" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#process-data"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Process data</span></h2> <p data-svelte-h="svelte-bzmsm5">Pandas functions are generally faster than regular hand-written python functions, and therefore they are a good option to optimize data processing. You can use Pandas functions to process a dataset in <a href="/docs/datasets/pr_8021/en/package_reference/main_classes#datasets.Dataset.map">Dataset.map()</a> or <a href="/docs/datasets/pr_8021/en/package_reference/main_classes#datasets.Dataset.filter">Dataset.filter()</a>:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> Dataset | |
| <span class="hljs-meta">>>> </span>data = {<span class="hljs-string">"col_0"</span>: [<span class="hljs-string">"a"</span>, <span class="hljs-string">"b"</span>, <span class="hljs-string">"c"</span>, <span class="hljs-string">"d"</span>], <span class="hljs-string">"col_1"</span>: [<span class="hljs-number">0.</span>, <span class="hljs-number">0.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>]} | |
| <span class="hljs-meta">>>> </span>ds = Dataset.from_dict(data) | |
| <span class="hljs-meta">>>> </span>ds = ds.with_format(<span class="hljs-string">"pandas"</span>) | |
| <span class="hljs-meta">>>> </span>ds = ds.<span class="hljs-built_in">map</span>(<span class="hljs-keyword">lambda</span> df: df.assign(col_2=df.col_1 + <span class="hljs-number">1</span>), batched=<span class="hljs-literal">True</span>) | |
| <span class="hljs-meta">>>> </span>ds[:<span class="hljs-number">2</span>] | |
| col_0 col_1 col_2 | |
| <span class="hljs-number">0</span> a <span class="hljs-number">0.0</span> <span class="hljs-number">1.0</span> | |
| <span class="hljs-number">1</span> b <span class="hljs-number">0.0</span> <span class="hljs-number">1.0</span> | |
| <span class="hljs-meta">>>> </span>ds = ds.<span class="hljs-built_in">filter</span>(<span class="hljs-keyword">lambda</span> df: df.col_0 == <span class="hljs-string">"b"</span>, batched=<span class="hljs-literal">True</span>) | |
| <span class="hljs-meta">>>> </span>ds[<span class="hljs-number">0</span>] | |
| col_0 col_1 col_2 | |
| <span class="hljs-number">0</span> b <span class="hljs-number">0.0</span> <span class="hljs-number">1.0</span><!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-1iws501">We use <code>batched=True</code> because it is faster to process batches of data in Pandas rather than row by row. It’s also possible to use <code>batch_size=</code> in <code>map()</code> to set the size of each <code>df</code>.</p> <p data-svelte-h="svelte-1lzi5rt">This also works for <a href="/docs/datasets/pr_8021/en/package_reference/main_classes#datasets.IterableDataset.map">IterableDataset.map()</a> and <a href="/docs/datasets/pr_8021/en/package_reference/main_classes#datasets.IterableDataset.filter">IterableDataset.filter()</a>.</p> <h2 class="relative group"><a id="import-or-export-from-pandas" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#import-or-export-from-pandas"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Import or Export from Pandas</span></h2> <p data-svelte-h="svelte-117nd8q">To import data from Pandas, you can use <a href="/docs/datasets/pr_8021/en/package_reference/main_classes#datasets.Dataset.from_pandas">Dataset.from_pandas()</a>:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START -->ds = Dataset.from_pandas(df)<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-1cg4cwe">And you can use <a href="/docs/datasets/pr_8021/en/package_reference/main_classes#datasets.Dataset.to_pandas">Dataset.to_pandas()</a> to export a Dataset to a Pandas DataFrame:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START -->df = Dataset.to_pandas()<!-- HTML_TAG_END --></pre></div> <a class="!text-gray-400 !no-underline text-sm flex items-center not-prose mt-4" href="https://github.com/huggingface/datasets/blob/main/docs/source/use_with_pandas.mdx" target="_blank"><svg class="mr-1" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M31,16l-7,7l-1.41-1.41L28.17,16l-5.58-5.59L24,9l7,7z"></path><path d="M1,16l7-7l1.41,1.41L3.83,16l5.58,5.59L8,23l-7-7z"></path><path d="M12.419,25.484L17.639,6.552l1.932,0.518L14.351,26.002z"></path></svg> <span data-svelte-h="svelte-zjs2n5"><span class="underline">Update</span> on GitHub</span></a> <p></p> | |
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