{"id":8128,"date":"2021-01-28T15:06:15","date_gmt":"2021-01-28T09:36:15","guid":{"rendered":"http:\/\/www.pythonpool.com\/?p=8128"},"modified":"2026-07-13T12:31:37","modified_gmt":"2026-07-13T07:01:37","slug":"matplotlib-annotate","status":"publish","type":"post","link":"https:\/\/www.pythonpool.com\/matplotlib-annotate\/","title":{"rendered":"Matplotlib annotate(): Add Labels and Arrows to Plots"},"content":{"rendered":"<p><strong>Quick answer:<\/strong> Matplotlib annotate() creates a callout attached to a coordinate. xy is the target point and xytext is the text position; arrowprops controls the connector. Keep coordinate systems, clipping, layout, and the final export size in mind so an annotation that looks correct interactively remains visible in a saved figure. A good annotation explains one decision or feature, not every point in a chart, so use labels selectively and keep the visual hierarchy readable.<\/p>\n<figure class=\"pythonpool-article-visual\"><img src=\"https:\/\/www.pythonpool.com\/wp-content\/uploads\/2026\/07\/matplotlib-annotate.png\" alt=\"Python Pool infographic showing Matplotlib annotate text point xytext arrowprops coordinate systems and clipping\" width=\"1536\" height=\"1024\" loading=\"lazy\" decoding=\"async\"><figcaption>annotate() connects explanatory text to a data point; choose coordinates, offsets, arrows, and clipping so the callout remains readable.<\/figcaption><\/figure>\n<p><code>matplotlib.annotate()<\/code> adds explanatory text to a plot and can draw an arrow from that text to a specific data point. Use it when a chart needs a callout, peak label, threshold note, outlier explanation, or any label that should point to a plotted value. Annotations and legends label different chart elements; <a href=\"https:\/\/www.pythonpool.com\/resolved-no-handles-with-labels-found-to-put-in-legend\/\">Fix No Handles With Labels Found in Legend<\/a> fixes the case where legend() cannot find labeled artists.<\/p>\n<p>In most object-oriented Matplotlib code, call <code>ax.annotate()<\/code>. The pyplot shortcut <code>plt.annotate()<\/code> works too, but using the Axes method is clearer when a figure has more than one subplot.<\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_85 counter-hierarchy ez-toc-counter ez-toc-transparent ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #990303;color:#990303\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #990303;color:#990303\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 eztoc-toggle-hide-by-default' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.pythonpool.com\/matplotlib-annotate\/#Basic_Syntax\" >Basic Syntax<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.pythonpool.com\/matplotlib-annotate\/#Simple_Annotation_Example\" >Simple Annotation Example<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.pythonpool.com\/matplotlib-annotate\/#Add_a_Box_Around_the_Label\" >Add a Box Around the Label<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.pythonpool.com\/matplotlib-annotate\/#Common_Coordinate_Systems\" >Common Coordinate Systems<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.pythonpool.com\/matplotlib-annotate\/#Annotation_With_Axes-Fraction_Text\" >Annotation With Axes-Fraction Text<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.pythonpool.com\/matplotlib-annotate\/#Styling_Annotation_Arrows\" >Styling Annotation Arrows<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.pythonpool.com\/matplotlib-annotate\/#Why_Matplotlib_annotate_Is_Not_Showing\" >Why Matplotlib annotate Is Not Showing<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.pythonpool.com\/matplotlib-annotate\/#Related_Matplotlib_Guides\" >Related Matplotlib Guides<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.pythonpool.com\/matplotlib-annotate\/#Official_References\" >Official References<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.pythonpool.com\/matplotlib-annotate\/#Conclusion\" >Conclusion<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.pythonpool.com\/matplotlib-annotate\/#Place_Text_At_A_Data_Point\" >Place Text At A Data Point<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.pythonpool.com\/matplotlib-annotate\/#Separate_xy_And_xytext\" >Separate xy And xytext<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.pythonpool.com\/matplotlib-annotate\/#Choose_Coordinate_Systems\" >Choose Coordinate Systems<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.pythonpool.com\/matplotlib-annotate\/#Prevent_Clipping_And_Overlap\" >Prevent Clipping And Overlap<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.pythonpool.com\/matplotlib-annotate\/#Frequently_Asked_Questions\" >Frequently Asked Questions<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Basic_Syntax\"><\/span>Basic Syntax<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<div class=\"pythonpool-code-scroll\" style=\"max-width:100%;overflow-x:auto;-webkit-overflow-scrolling:touch;\">\n<pre class=\"wp-block-code\"><code>ax.annotate(\n    text,\n    xy,\n    xytext=None,\n    xycoords=\"data\",\n    textcoords=None,\n    arrowprops=None,\n    annotation_clip=None,\n    **kwargs,\n)<\/code><\/pre>\n<\/div>\n<div class=\"pythonpool-table-scroll\" style=\"max-width:100%;overflow-x:auto;-webkit-overflow-scrolling:touch;\">\n<table>\n<thead>\n<tr>\n<th>Argument<\/th>\n<th>Purpose<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><code>text<\/code><\/td>\n<td>The annotation label.<\/td>\n<\/tr>\n<tr>\n<td><code>xy<\/code><\/td>\n<td>The point being annotated. This is where the arrow points.<\/td>\n<\/tr>\n<tr>\n<td><code>xytext<\/code><\/td>\n<td>The text position. If omitted, the text is placed at <code>xy<\/code>.<\/td>\n<\/tr>\n<tr>\n<td><code>xycoords<\/code><\/td>\n<td>Coordinate system for <code>xy<\/code>. The default is <code>data<\/code>.<\/td>\n<\/tr>\n<tr>\n<td><code>textcoords<\/code><\/td>\n<td>Coordinate system for <code>xytext<\/code>.<\/td>\n<\/tr>\n<tr>\n<td><code>arrowprops<\/code><\/td>\n<td>Dictionary of arrow styling options. If omitted, no arrow is drawn.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<h2><span class=\"ez-toc-section\" id=\"Simple_Annotation_Example\"><\/span>Simple Annotation Example<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>This example labels the highest point of a sine curve. The annotation point uses data coordinates, while the text is offset from that point by 25 points horizontally and 35 points vertically.<\/p>\n<div class=\"pythonpool-code-scroll\" style=\"max-width:100%;overflow-x:auto;-webkit-overflow-scrolling:touch;\">\n<pre class=\"wp-block-code\"><code>import numpy as np\nimport matplotlib.pyplot as plt\n\nx = np.linspace(0, 10, 100)\ny = np.sin(x)\npeak_index = np.argmax(y)\n\nfig, ax = plt.subplots()\nax.plot(x, y)\n\nax.annotate(\n    \"peak\",\n    xy=(x[peak_index], y[peak_index]),\n    xytext=(25, 35),\n    textcoords=\"offset points\",\n    arrowprops={\"arrowstyle\": \"-&gt;\", \"color\": \"crimson\"},\n)\n\nplt.show()<\/code><\/pre>\n<\/div>\n<p>The key detail is the difference between <code>xy<\/code> and <code>xytext<\/code>. <code>xy<\/code> identifies the data point. <code>xytext<\/code> controls where the label appears.<\/p>\n<p><!-- Python Pool visual layout repair 2026-07-13 --><\/p>\n<figure class=\"pythonpool-article-visual pythonpool-supporting-visual\"><img src=\"https:\/\/www.pythonpool.com\/wp-content\/uploads\/2026\/07\/annotate-label-b148.png\" alt=\"Python Pool infographic showing a Matplotlib point, annotation text, coordinates, and an arrow\" width=\"1536\" height=\"1054\" loading=\"lazy\" decoding=\"async\"><figcaption>Plot label: A Matplotlib point, annotation text, coordinates, and an arrow.<\/figcaption><\/figure>\n<h2><span class=\"ez-toc-section\" id=\"Add_a_Box_Around_the_Label\"><\/span>Add a Box Around the Label<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Because <code>annotate()<\/code> accepts text styling keyword arguments, you can add a background box with <code>bbox<\/code> and align the label with <code>ha<\/code> and <code>va<\/code>.<\/p>\n<div class=\"pythonpool-code-scroll\" style=\"max-width:100%;overflow-x:auto;-webkit-overflow-scrolling:touch;\">\n<pre class=\"wp-block-code\"><code>ax.annotate(\n    \"maximum value\",\n    xy=(x[peak_index], y[peak_index]),\n    xytext=(30, 40),\n    textcoords=\"offset points\",\n    ha=\"left\",\n    va=\"bottom\",\n    bbox={\"boxstyle\": \"round,pad=0.3\", \"fc\": \"white\", \"ec\": \"crimson\"},\n    arrowprops={\"arrowstyle\": \"-&gt;\", \"color\": \"crimson\"},\n)<\/code><\/pre>\n<\/div>\n<p>This pattern is useful when the plotted line or background would make plain text hard to read.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Common_Coordinate_Systems\"><\/span>Common Coordinate Systems<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Matplotlib annotations are flexible because the arrow target and text can use different coordinate systems.<\/p>\n<ul>\n<li><strong><code>data<\/code><\/strong>: Uses the plotted data coordinates. This is the default for <code>xy<\/code>.<\/li>\n<li><strong><code>offset points<\/code><\/strong>: Places the text a fixed point offset from <code>xy<\/code>. This is common for labels that should follow a data point without covering it.<\/li>\n<li><strong><code>axes fraction<\/code><\/strong>: Uses the Axes box, where <code>(0, 0)<\/code> is bottom-left and <code>(1, 1)<\/code> is top-right.<\/li>\n<li><strong><code>figure fraction<\/code><\/strong>: Uses the full figure instead of a single Axes.<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"Annotation_With_Axes-Fraction_Text\"><\/span>Annotation With Axes-Fraction Text<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Sometimes the arrow should point to data, but the text should stay in a stable corner of the plot. Use <code>xycoords=\"data\"<\/code> and <code>textcoords=\"axes fraction\"<\/code>.<\/p>\n<div class=\"pythonpool-code-scroll\" style=\"max-width:100%;overflow-x:auto;-webkit-overflow-scrolling:touch;\">\n<pre class=\"wp-block-code\"><code>ax.annotate(\n    \"important point\",\n    xy=(4, np.sin(4)),\n    xycoords=\"data\",\n    xytext=(0.05, 0.95),\n    textcoords=\"axes fraction\",\n    ha=\"left\",\n    va=\"top\",\n    arrowprops={\"arrowstyle\": \"-&gt;\", \"connectionstyle\": \"arc3,rad=0.2\"},\n)<\/code><\/pre>\n<\/div>\n<p>This keeps the label near the top-left of the Axes even if the data limits change.<\/p>\n<figure class=\"pythonpool-article-visual pythonpool-supporting-visual\"><img src=\"https:\/\/www.pythonpool.com\/wp-content\/uploads\/2026\/07\/annotate-arrow-b148.png\" alt=\"Python Pool infographic mapping annotate arguments through arrow style, offset text, and target point\" width=\"1536\" height=\"1054\" loading=\"lazy\" decoding=\"async\"><figcaption>Arrow props: Annotate arguments through arrow style, offset text, and target point.<\/figcaption><\/figure>\n<h2><span class=\"ez-toc-section\" id=\"Styling_Annotation_Arrows\"><\/span>Styling Annotation Arrows<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>For modern Matplotlib code, prefer the fancy-arrow style by setting <code>arrowstyle<\/code>. You can also use <code>connectionstyle<\/code> for curved arrows.<\/p>\n<div class=\"pythonpool-code-scroll\" style=\"max-width:100%;overflow-x:auto;-webkit-overflow-scrolling:touch;\">\n<pre class=\"wp-block-code\"><code>arrowprops = {\n    \"arrowstyle\": \"-&gt;\",\n    \"color\": \"black\",\n    \"linewidth\": 1.5,\n    \"connectionstyle\": \"arc3,rad=-0.2\",\n}<\/code><\/pre>\n<\/div>\n<p>If you need standalone arrows rather than text annotations, see the related <a href=\"https:\/\/www.pythonpool.com\/matplotlib-arrow\/\">Matplotlib arrow guide<\/a>.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Why_Matplotlib_annotate_Is_Not_Showing\"><\/span>Why Matplotlib annotate Is Not Showing<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul>\n<li><strong>The point is outside the visible axis limits.<\/strong> Check <code>ax.set_xlim()<\/code> and <code>ax.set_ylim()<\/code>. The <a href=\"https:\/\/www.pythonpool.com\/matplotlib-ylim\/\">Matplotlib ylim guide<\/a> covers y-axis limits in detail.<\/li>\n<li><strong>The text is clipped.<\/strong> Try moving <code>xytext<\/code>, using <code>annotation_clip=False<\/code>, or increasing the plot margins.<\/li>\n<li><strong>The arrow color blends into the chart.<\/strong> Set a visible <code>color<\/code>, <code>linewidth<\/code>, or <code>bbox<\/code>.<\/li>\n<li><strong>You annotated the wrong Axes.<\/strong> In multi-plot figures, call <code>annotate()<\/code> on the correct <code>ax<\/code>. The <a href=\"https:\/\/www.pythonpool.com\/matplotlib-gca\/\">Matplotlib gca guide<\/a> explains current Axes behavior.<\/li>\n<\/ul>\n<figure class=\"pythonpool-article-visual pythonpool-supporting-visual\"><img src=\"https:\/\/www.pythonpool.com\/wp-content\/uploads\/2026\/07\/annotate-layout-b148.png\" alt=\"Python Pool infographic comparing text offset, clipping, axes limits, overlapping labels, and layout\" width=\"1536\" height=\"1054\" loading=\"lazy\" decoding=\"async\"><figcaption>Keep readable: Text offset, clipping, axes limits, overlapping labels, and layout.<\/figcaption><\/figure>\n<h2><span class=\"ez-toc-section\" id=\"Related_Matplotlib_Guides\"><\/span>Related Matplotlib Guides<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Annotations often pair well with shape and styling helpers. See <a href=\"https:\/\/www.pythonpool.com\/matplotlib-circle\/\">how to draw circles in Matplotlib<\/a>, <a href=\"https:\/\/www.pythonpool.com\/matplotlib-background-color\/\">how to change Matplotlib background color<\/a>, and <a href=\"https:\/\/www.pythonpool.com\/matplotlib-pcolormesh\/\">Matplotlib pcolormesh<\/a> for more plotting examples.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Official_References\"><\/span>Official References<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul>\n<li><a href=\"https:\/\/matplotlib.org\/stable\/api\/_as_gen\/matplotlib.axes.Axes.annotate.html\" rel=\"nofollow noopener\" target=\"_blank\">Matplotlib Axes.annotate documentation<\/a><\/li>\n<li><a href=\"https:\/\/matplotlib.org\/stable\/api\/_as_gen\/matplotlib.pyplot.annotate.html\" rel=\"nofollow noopener\" target=\"_blank\">Matplotlib pyplot.annotate documentation<\/a><\/li>\n<li><a href=\"https:\/\/matplotlib.org\/stable\/users\/explain\/text\/annotations.html\" rel=\"nofollow noopener\" target=\"_blank\">Matplotlib annotations guide<\/a><\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span>Conclusion<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Use <code>ax.annotate()<\/code> when a plot needs a clear callout. Set <code>xy<\/code> for the data point, <code>xytext<\/code> for the label position, <code>textcoords<\/code> for offsets, and <code>arrowprops<\/code> for arrows. These four options handle most annotation tasks cleanly.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Place_Text_At_A_Data_Point\"><\/span>Place Text At A Data Point<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>The simplest annotation uses data coordinates for both the target and text. This keeps the label tied to plotted values when the axes limits change. Use a short label and inspect crowded points before adding more callouts.<\/p>\n<div class=\"pythonpool-code-scroll\" style=\"max-width:100%;overflow-x:auto;-webkit-overflow-scrolling:touch;\">\n<pre><code class=\"language-python\">import matplotlib.pyplot as plt\n\nfig, ax = plt.subplots()\nx = [1, 2, 3, 4]\ny = [2, 5, 3, 7]\nax.plot(x, y, marker=\"o\")\nax.annotate(\"peak\", xy=(4, 7))\nfig.savefig(\"annotated.png\", dpi=160)\nplt.close(fig)<\/code><\/pre>\n<\/div>\n<h2><span class=\"ez-toc-section\" id=\"Separate_xy_And_xytext\"><\/span>Separate xy And xytext<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>xy identifies what the annotation explains, while xytext identifies where the label sits. Moving text away from the point prevents overlap. arrowprops can add a visible connector and use an arrow style that survives the output size.<\/p>\n<div class=\"pythonpool-code-scroll\" style=\"max-width:100%;overflow-x:auto;-webkit-overflow-scrolling:touch;\">\n<pre><code class=\"language-python\">import matplotlib.pyplot as plt\n\nfig, ax = plt.subplots()\nax.scatter([1, 2, 3], [2, 5, 3])\nax.annotate(\"highest value\", xy=(2, 5), xytext=(2.4, 6), arrowprops={\"arrowstyle\": \"-&gt;\"})\nfig.tight_layout()<\/code><\/pre>\n<\/div>\n<figure class=\"pythonpool-article-visual pythonpool-supporting-visual\"><img src=\"https:\/\/www.pythonpool.com\/wp-content\/uploads\/2026\/07\/annotate-check-b148.png\" alt=\"Python Pool infographic testing transforms, multiple labels, savefig, resize, and rendered output\" width=\"1536\" height=\"1054\" loading=\"lazy\" decoding=\"async\"><figcaption>Annotation checks: Transforms, multiple labels, savefig, resize, and rendered output.<\/figcaption><\/figure>\n<h2><span class=\"ez-toc-section\" id=\"Choose_Coordinate_Systems\"><\/span>Choose Coordinate Systems<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>By default, xy and xytext use data coordinates. axes fraction, figure fraction, offset points, and other coordinate systems are useful when a label should stay near a corner or use a fixed visual offset. Set the coordinate systems explicitly when their meanings differ.<\/p>\n<div class=\"pythonpool-code-scroll\" style=\"max-width:100%;overflow-x:auto;-webkit-overflow-scrolling:touch;\">\n<pre><code class=\"language-python\">import matplotlib.pyplot as plt\n\nfig, ax = plt.subplots()\nax.plot([0, 1], [0, 1])\nax.annotate(\"axes note\", xy=(0.8, 0.8), xycoords=\"data\", xytext=(0.05, 0.95), textcoords=\"axes fraction\", arrowprops={\"arrowstyle\": \"-&gt;\"})<\/code><\/pre>\n<\/div>\n<h2><span class=\"ez-toc-section\" id=\"Prevent_Clipping_And_Overlap\"><\/span>Prevent Clipping And Overlap<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>An annotation can be clipped by the axes, hidden behind another artist, or cut off by the saved bounding box. Use annotation_clip deliberately, reserve layout space, and render the final PNG or PDF at its actual dimensions. A label should explain data without covering the point or neighboring labels.<\/p>\n<div class=\"pythonpool-code-scroll\" style=\"max-width:100%;overflow-x:auto;-webkit-overflow-scrolling:touch;\">\n<pre><code class=\"language-python\">import matplotlib.pyplot as plt\n\nfig, ax = plt.subplots(figsize=(6, 4), constrained_layout=True)\nax.plot([1, 2, 3], [1, 4, 2])\nax.annotate(\"callout\", xy=(2, 4), xytext=(2.5, 4.5), annotation_clip=False)\nfig.savefig(\"callout.png\", dpi=160, bbox_inches=\"tight\")\nplt.close(fig)<\/code><\/pre>\n<\/div>\n<p>Matplotlib&#8217;s official <a href=\"https:\/\/matplotlib.org\/stable\/api\/_as_gen\/matplotlib.axes.Axes.annotate.html\">Axes.annotate() reference<\/a> defines xy, xytext, coordinate systems, arrowprops, and clipping. Treat annotations as part of the figure layout, not as an afterthought added after export.<\/p>\n<p>For related chart labeling and layout, compare <a href=\"https:\/\/www.pythonpool.com\/resolved-no-handles-with-labels-found-to-put-in-legend\/\">legend handle fixes<\/a>, <a href=\"https:\/\/www.pythonpool.com\/matplotlib-gca\/\">current Axes inspection<\/a>, and <a href=\"https:\/\/www.pythonpool.com\/matplotlib-vertical-lines\/\">vertical plot markers<\/a> when placing callouts that should remain readable.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Frequently_Asked_Questions\"><\/span>Frequently Asked Questions<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h3>What does Matplotlib annotate() do?<\/h3>\n<p>It adds text at or near a plot location and can draw an arrow from the text to a target point.<\/p>\n<h3>What is the difference between xy and xytext?<\/h3>\n<p>xy identifies the point being annotated, while xytext identifies where the annotation text should be placed.<\/p>\n<h3>How do I add an arrow to an annotation?<\/h3>\n<p>Pass an arrowprops dictionary, usually with arrowstyle and connection settings, to draw a pointer between the text and target.<\/p>\n<h3>Why is a Matplotlib annotation not visible?<\/h3>\n<p>Check coordinate systems, axis limits, clipping, text color, layout, and whether the annotation is outside the saved figure bounds.<\/p>\n<p><script type=\"application\/ld+json\">{\"@context\":\"https:\/\/schema.org\",\"@type\":\"FAQPage\",\"mainEntity\":[{\"@type\":\"Question\",\"name\":\"What does Matplotlib annotate() do?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"It adds text at or near a plot location and can draw an arrow from the text to a target point.\"}},{\"@type\":\"Question\",\"name\":\"What is the difference between xy and xytext?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"xy identifies the point being annotated, while xytext identifies where the annotation text should be 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