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Calculated Shard: 70 (from laksa038)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa070.int.ahrefs:8124/' \
  -H 'Content-Type: text/plain' \
  -H 'X-ClickHouse-Database: crawler3' \
  -H 'Authorization: Basic YXBpOg==' \
  -d 'SELECT getAhrefsURLFromUnparsed(src_unparsed) AS found_url, ifNull(toUnixTimestamp(download_stamp), 0) AS crawl_time, ifNull(toUnixTimestamp(props_url_first_seen), 0) AS first_indexed_time, download_http_code AS http_code, src_unparsed AS src_unparsed, src_root_hash AS src_root_hash, history_drop_reason AS history_drop_reason, meta_title AS meta_title, meta_descriptions AS meta_descriptions, attrs_boilerpipe_text AS attrs_boilerpipe_text, attrs_markdown AS attrs_markdown, attrs_readable_markdown AS attrs_readable_markdown, meta_canonical AS meta_canonical FROM crawler3.page_info_local FINAL PREWHERE (src_root_hash, src_unparsed) IN ((getAhrefsRootHashFromUnparsed(getAhrefsUnparsedNoserviceFromURL(\'https://shiny.posit.co/py/components/outputs/plot-seaborn/\')), getAhrefsUnparsedNoserviceFromURL(\'https://shiny.posit.co/py/components/outputs/plot-seaborn/\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/shiny.posit.co\/py\/components\/outputs\/plot-seaborn\/","crawl_time":1775174237,"first_indexed_time":1734731726,"http_code":200,"src_unparsed":"co,posit!shiny,\/py\/components\/outputs\/plot-seaborn\/ s443","src_root_hash":"17512250694148690070","history_drop_reason":null,"meta_title":"Plot (Seaborn) – Shiny for Python","meta_descriptions":[],"attrs_boilerpipe_text":"#| '!! shinylive warning !!': |\n#|   shinylive does not work in self-contained HTML documents.\n#|   Please set `embed-resources: false` in your metadata.\n#| standalone: true\n#| components: [viewer]\n#| viewerHeight: 500\nimport seaborn as sns\nfrom palmerpenguins import load_penguins\nfrom shiny import App, render, ui\npenguins = load_penguins()\napp_ui = ui.page_fluid(\nui.input_slider(\"n\", \"Number of bins\", 1, 100, 20),\nui.output_plot(\"plot\"),\n)\ndef server(input, output, session):\n@render.plot(alt=\"A Seaborn histogram on penguin body mass in grams.\")\ndef plot():\nax = sns.histplot(data=penguins, x=\"body_mass_g\", bins=input.n())\nax.set_title(\"Palmer Penguins\")\nax.set_xlabel(\"Mass (g)\")\nax.set_ylabel(\"Count\")\nreturn ax\napp = App(app_ui, server, debug=True)\nExpress\nCore\nimport\nseaborn\nas\nsns\nfrom\npalmerpenguins\nimport\nload_penguins\nfrom\nshiny.express\nimport\ninput\n, render, ui\npenguins\n=\nload_penguins()\nui.input_slider(\n\"n\"\n,\n\"Number of bins\"\n,\n1\n,\n100\n,\n20\n)\n@render.plot\n(alt\n=\n\"A Seaborn histogram on penguin body mass in grams.\"\n)\ndef\nplot():\nax\n=\nsns.histplot(data\n=\npenguins, x\n=\n\"body_mass_g\"\n, bins\n=\ninput\n.n())\nax.set_title(\n\"Palmer Penguins\"\n)\nax.set_xlabel(\n\"Mass (g)\"\n)\nax.set_ylabel(\n\"Count\"\n)\nreturn\nax\nimport\nseaborn\nas\nsns\nfrom\npalmerpenguins\nimport\nload_penguins\nfrom\nshiny\nimport\nApp, render, ui\npenguins\n=\nload_penguins()\napp_ui\n=\nui.page_fluid(\nui.input_slider(\n\"n\"\n,\n\"Number of bins\"\n,\n1\n,\n100\n,\n20\n),\nui.output_plot(\n\"plot\"\n),\n)\ndef\nserver(\ninput\n, output, session):\n@render.plot\n(alt\n=\n\"A Seaborn histogram on penguin body mass in grams.\"\n)\ndef\nplot():\nax\n=\nsns.histplot(data\n=\npenguins, x\n=\n\"body_mass_g\"\n, bins\n=\ninput\n.n())\nax.set_title(\n\"Palmer Penguins\"\n)\nax.set_xlabel(\n\"Mass (g)\"\n)\nax.set_ylabel(\n\"Count\"\n)\nreturn\nax\napp\n=\nApp(app_ui, server, debug\n=\nTrue\n)\nNo matching items\nRelevant Functions\nui.output_plot\nui.output_plot(id, width='100%', height='400px', *, inline=False, click=False, dblclick=False, hover=False, brush=False, fill=MISSING)\n@render.plot\nrender.plot(_fn=None, *, alt=None, width=MISSING, height=MISSING, **kwargs)\nNo matching items\nDetails\nSeaborn is a statistical plotting library that builds on top of Matplotlib.\nFollow these steps to display a Seaborn figure in your app:\nAdd\nui.output_plot()\nto the UI of your app to create a div in which to display the figure. Where you call this function will determine where the figure will appear within the layout of the app. The\nid\nparameter you provide will be used to link to other parts of the Shiny app.\nDefine a function within the\nserver()\nfunction that creates the figure.\nThe name of the function should be the same value you passed into the\nid\nparameter in your\nui.output_plot()\nfunction call in the UI.\nIf your function calls reactive values, Shiny will update your figure whenever those values change, in a\nreactive fashion\n.\nYour function should return one of the following objects:\nA\nmatplotlib.figure.Figure\ninstance\nA\nmatplotlib.artist.Artist\ninstance\nA list\/tuple of\nFigure\n\/\nArtist\ninstances\nAn object with a ‘figure’ attribute pointing to a\nmatplotlib.figure.Figure\ninstance\nA\nPIL.Image.Image\ninstance\nDecorate your plotting function with a\n@render.plot\ndecorator.\nIf your plotting function is not the same as the\nid\nyou used in the\nui.output_plot()\n, you can add an additional\n@output(id=...)\ndecorator.\nIf you use the\n@output()\ndecorator, make sure it is\nabove\nthe\n@render.plot\ndecorator.\nYou can use a plot as an input widget, collecting the locations of user clicks, double clicks, hovers, and brushes. To do this, follow the instructions provided for\nplots as inputs\n.","attrs_markdown":"[![The logo for Shiny for Python](https:\/\/shiny.posit.co\/py\/shiny-for-python.svg)](https:\/\/shiny.posit.co\/py\/index.html)   [Shiny for Python](https:\/\/shiny.posit.co\/py\/index.html)\n\n- [Get Started](https:\/\/shiny.posit.co\/py\/get-started\/index.html)\n- [Concepts](https:\/\/shiny.posit.co\/py\/docs\/overview.html)\n- [Components](https:\/\/shiny.posit.co\/py\/components\/outputs\/plot-seaborn\/)\n  - [Components](https:\/\/shiny.posit.co\/py\/components\/index.html)\n  - [Layouts](https:\/\/shiny.posit.co\/py\/layouts\/index.html)\n  - [Templates](https:\/\/shiny.posit.co\/py\/templates\/index.html)\n- [Gallery](https:\/\/shiny.posit.co\/py\/gallery\/index.html)\n- [Playground](https:\/\/shinylive.io\/py\/examples\/)\n- [Reference](https:\/\/shiny.posit.co\/py\/components\/outputs\/plot-seaborn\/)\n  - [Shiny Express](https:\/\/shiny.posit.co\/py\/api\/express\/index.html)\n  - [Shiny Core](https:\/\/shiny.posit.co\/py\/api\/core\/index.html)\n  - [Testing](https:\/\/shiny.posit.co\/py\/api\/testing\/index.html)\n\n1. [![](https:\/\/shiny.posit.co\/py\/images\/bar-chart-line-fill.svg)**Outputs**](https:\/\/shiny.posit.co\/py\/components\/outputs\/data-grid\/index.html)\n2. [Plot (Seaborn)](https:\/\/shiny.posit.co\/py\/components\/outputs\/plot-seaborn\/index.html)\n\n- [![](https:\/\/shiny.posit.co\/py\/images\/blank-pixel.png)**COMPONENTS**](https:\/\/shiny.posit.co\/py\/components\/)\n- [![](https:\/\/shiny.posit.co\/py\/images\/sliders.svg)**Inputs**]()\n  - [Action Button](https:\/\/shiny.posit.co\/py\/components\/inputs\/action-button\/index.html)\n  - [Action Link](https:\/\/shiny.posit.co\/py\/components\/inputs\/action-link\/index.html)\n  - [Checkbox](https:\/\/shiny.posit.co\/py\/components\/inputs\/checkbox\/index.html)\n  - [Checkbox Group](https:\/\/shiny.posit.co\/py\/components\/inputs\/checkbox-group\/index.html)\n  - [Dark Mode Switch](https:\/\/shiny.posit.co\/py\/components\/inputs\/dark-mode\/index.html)\n  - [Date Range Selector](https:\/\/shiny.posit.co\/py\/components\/inputs\/date-range-selector\/index.html)\n  - [Date Selector](https:\/\/shiny.posit.co\/py\/components\/inputs\/date-selector\/index.html)\n  - [File Input](https:\/\/shiny.posit.co\/py\/components\/inputs\/file\/index.html)\n  - [Numeric Input](https:\/\/shiny.posit.co\/py\/components\/inputs\/numeric-input\/index.html)\n  - [Password Field](https:\/\/shiny.posit.co\/py\/components\/inputs\/password-field\/index.html)\n  - [Radio Buttons](https:\/\/shiny.posit.co\/py\/components\/inputs\/radio-buttons\/index.html)\n  - [Select (Single)](https:\/\/shiny.posit.co\/py\/components\/inputs\/select-single\/index.html)\n  - [Select (Multiple)](https:\/\/shiny.posit.co\/py\/components\/inputs\/select-multiple\/index.html)\n  - [Selectize (Single)](https:\/\/shiny.posit.co\/py\/components\/inputs\/selectize-single\/index.html)\n  - [Selectize (Multiple)](https:\/\/shiny.posit.co\/py\/components\/inputs\/selectize-multiple\/index.html)\n  - [Slider](https:\/\/shiny.posit.co\/py\/components\/inputs\/slider\/index.html)\n  - [Slider Range](https:\/\/shiny.posit.co\/py\/components\/inputs\/slider-range\/index.html)\n  - [Switch](https:\/\/shiny.posit.co\/py\/components\/inputs\/switch\/index.html)\n  - [Text Area](https:\/\/shiny.posit.co\/py\/components\/inputs\/text-area\/index.html)\n  - [Text Box](https:\/\/shiny.posit.co\/py\/components\/inputs\/text-box\/index.html)\n  - [Toolbar Button](https:\/\/shiny.posit.co\/py\/components\/inputs\/toolbar-button\/index.html)\n  - [Toolbar Select](https:\/\/shiny.posit.co\/py\/components\/inputs\/toolbar-select\/index.html)\n- [![](https:\/\/shiny.posit.co\/py\/images\/bar-chart-line-fill.svg)**Outputs**]()\n  - [Data Grid](https:\/\/shiny.posit.co\/py\/components\/outputs\/data-grid\/index.html)\n  - [Data Table](https:\/\/shiny.posit.co\/py\/components\/outputs\/data-table\/index.html)\n  - [Image](https:\/\/shiny.posit.co\/py\/components\/outputs\/image\/index.html)\n  - [Map (ipyleaflet)](https:\/\/shiny.posit.co\/py\/components\/outputs\/map-ipyleaflet\/index.html)\n  - [Plot (Matplotlib)](https:\/\/shiny.posit.co\/py\/components\/outputs\/plot-matplotlib\/index.html)\n  - [Plot (Plotly)](https:\/\/shiny.posit.co\/py\/components\/outputs\/plot-plotly\/index.html)\n  - [Plot (Seaborn)](https:\/\/shiny.posit.co\/py\/components\/outputs\/plot-seaborn\/index.html)\n  - [Text](https:\/\/shiny.posit.co\/py\/components\/outputs\/text\/index.html)\n  - [UI](https:\/\/shiny.posit.co\/py\/components\/outputs\/ui\/index.html)\n  - [Value Box](https:\/\/shiny.posit.co\/py\/components\/outputs\/value-box\/index.html)\n  - [Verbatim Text](https:\/\/shiny.posit.co\/py\/components\/outputs\/verbatim-text\/index.html)\n- [![](https:\/\/shiny.posit.co\/py\/images\/chat-dots-fill.svg)**Display Messages**]()\n  - [Chat](https:\/\/shiny.posit.co\/py\/components\/display-messages\/chat\/index.html)\n  - [Modal](https:\/\/shiny.posit.co\/py\/components\/display-messages\/modal\/index.html)\n  - [Notifications](https:\/\/shiny.posit.co\/py\/components\/display-messages\/notifications\/index.html)\n  - [Progress Bar](https:\/\/shiny.posit.co\/py\/components\/display-messages\/progress-bar\/index.html)\n  - [Tooltips](https:\/\/shiny.posit.co\/py\/components\/display-messages\/tooltips\/index.html)\n- [![](https:\/\/shiny.posit.co\/py\/images\/cards-blue.svg)**Layout**]()\n  - [Card](https:\/\/shiny.posit.co\/py\/components\/layout\/cards\/index.html)\n  - [Toolbar](https:\/\/shiny.posit.co\/py\/components\/layout\/toolbar\/index.html)\n\n1. [![](https:\/\/shiny.posit.co\/py\/images\/bar-chart-line-fill.svg)**Outputs**](https:\/\/shiny.posit.co\/py\/components\/outputs\/data-grid\/index.html)\n2. [Plot (Seaborn)](https:\/\/shiny.posit.co\/py\/components\/outputs\/plot-seaborn\/index.html)\n# Plot (Seaborn)\n\n```\n\n```\n- [Express]()\n- [Core]()\n\n```\n\n```\n```\n\n```\n\nNo matching items\n\n## Relevant Functions\n- [ui.output\\_plot](https:\/\/shiny.posit.co\/py\/api\/ui.output_plot.html)   \n   `ui.output_plot(id, width='100%', height='400px', *, inline=False, click=False, dblclick=False, hover=False, brush=False, fill=MISSING)`\n- [@render.plot](https:\/\/shiny.posit.co\/py\/api\/render.plot.html)   \n   `render.plot(_fn=None, *, alt=None, width=MISSING, height=MISSING, **kwargs)`\n\nNo matching items\n\n## Details\nSeaborn is a statistical plotting library that builds on top of Matplotlib.\n\nFollow these steps to display a Seaborn figure in your app:\n\n1. Add `ui.output_plot()` to the UI of your app to create a div in which to display the figure. Where you call this function will determine where the figure will appear within the layout of the app. The `id` parameter you provide will be used to link to other parts of the Shiny app.\n2. Define a function within the `server()` function that creates the figure.\n   - The name of the function should be the same value you passed into the `id` parameter in your `ui.output_plot()` function call in the UI.\n   - If your function calls reactive values, Shiny will update your figure whenever those values change, in a [reactive fashion](https:\/\/shiny.posit.co\/py\/docs\/reactive-programming.html).\n   - Your function should return one of the following objects:\n     - A `matplotlib.figure.Figure` instance\n     - A `matplotlib.artist.Artist` instance\n     - A list\/tuple of `Figure`\/`Artist` instances\n     - An object with a ‘figure’ attribute pointing to a `matplotlib.figure.Figure` instance\n     - A `PIL.Image.Image` instance\n3. Decorate your plotting function with a `@render.plot` decorator.\n   - If your plotting function is not the same as the `id` you used in the `ui.output_plot()`, you can add an additional `@output(id=...)` decorator.\n   - If you use the `@output()` decorator, make sure it is **above** the `@render.plot` decorator.\n\nYou can use a plot as an input widget, collecting the locations of user clicks, double clicks, hovers, and brushes. To do this, follow the instructions provided for [plots as inputs](https:\/\/shiny.posit.co\/py\/components\/outputs\/plot-seaborn\/plot-matplotlib.html#plots-as-inputs).\n\n[Plot (Plotly)](https:\/\/shiny.posit.co\/py\/components\/outputs\/plot-plotly\/index.html)\n\n[Text](https:\/\/shiny.posit.co\/py\/components\/outputs\/text\/index.html)\n\nProudly supported by [![Posit](https:\/\/shiny.posit.co\/py\/images\/posit-logo-black.svg)](https:\/\/www.posit.co\/)","attrs_readable_markdown":"```\n#| '!! shinylive warning !!': |\n#|   shinylive does not work in self-contained HTML documents.\n#|   Please set `embed-resources: false` in your metadata.\n#| standalone: true\n#| components: [viewer]\n#| viewerHeight: 500\n\nimport seaborn as sns\nfrom palmerpenguins import load_penguins\nfrom shiny import App, render, ui\n\npenguins = load_penguins()\n\napp_ui = ui.page_fluid(\n    ui.input_slider(\"n\", \"Number of bins\", 1, 100, 20),\n    ui.output_plot(\"plot\"),  \n)\n\ndef server(input, output, session):\n    @render.plot(alt=\"A Seaborn histogram on penguin body mass in grams.\")  \n    def plot():  \n        ax = sns.histplot(data=penguins, x=\"body_mass_g\", bins=input.n())  \n        ax.set_title(\"Palmer Penguins\")\n        ax.set_xlabel(\"Mass (g)\")\n        ax.set_ylabel(\"Count\")\n        return ax  \n\napp = App(app_ui, server, debug=True)\n```\n- [Express]()\n- [Core]()\n\n```\nimport seaborn as sns\nfrom palmerpenguins import load_penguins\nfrom shiny.express import input, render, ui\n\npenguins = load_penguins()\n\nui.input_slider(\"n\", \"Number of bins\", 1, 100, 20)\n\n@render.plot(alt=\"A Seaborn histogram on penguin body mass in grams.\")  \ndef plot():  \n    ax = sns.histplot(data=penguins, x=\"body_mass_g\", bins=input.n())  \n    ax.set_title(\"Palmer Penguins\")\n    ax.set_xlabel(\"Mass (g)\")\n    ax.set_ylabel(\"Count\")\n    return ax\n```\n```\nimport seaborn as sns\nfrom palmerpenguins import load_penguins\nfrom shiny import App, render, ui\n\npenguins = load_penguins()\n\napp_ui = ui.page_fluid(\n    ui.input_slider(\"n\", \"Number of bins\", 1, 100, 20),\n    ui.output_plot(\"plot\"),  \n)\n\ndef server(input, output, session):\n    @render.plot(alt=\"A Seaborn histogram on penguin body mass in grams.\")  \n    def plot():  \n        ax = sns.histplot(data=penguins, x=\"body_mass_g\", bins=input.n())  \n        ax.set_title(\"Palmer Penguins\")\n        ax.set_xlabel(\"Mass (g)\")\n        ax.set_ylabel(\"Count\")\n        return ax  \n\napp = App(app_ui, server, debug=True)\n```\n\nNo matching items\n\n## Relevant Functions\n- [ui.output\\_plot](https:\/\/shiny.posit.co\/py\/api\/ui.output_plot.html)   \n   `ui.output_plot(id, width='100%', height='400px', *, inline=False, click=False, dblclick=False, hover=False, brush=False, fill=MISSING)`\n- [@render.plot](https:\/\/shiny.posit.co\/py\/api\/render.plot.html)   \n   `render.plot(_fn=None, *, alt=None, width=MISSING, height=MISSING, **kwargs)`\n\nNo matching items\n\n## Details\nSeaborn is a statistical plotting library that builds on top of Matplotlib.\n\nFollow these steps to display a Seaborn figure in your app:\n\n1. Add `ui.output_plot()` to the UI of your app to create a div in which to display the figure. Where you call this function will determine where the figure will appear within the layout of the app. The `id` parameter you provide will be used to link to other parts of the Shiny app.\n2. Define a function within the `server()` function that creates the figure.\n   - The name of the function should be the same value you passed into the `id` parameter in your `ui.output_plot()` function call in the UI.\n   - If your function calls reactive values, Shiny will update your figure whenever those values change, in a [reactive fashion](https:\/\/shiny.posit.co\/py\/docs\/reactive-programming.html).\n   - Your function should return one of the following objects:\n     - A `matplotlib.figure.Figure` instance\n     - A `matplotlib.artist.Artist` instance\n     - A list\/tuple of `Figure`\/`Artist` instances\n     - An object with a ‘figure’ attribute pointing to a `matplotlib.figure.Figure` instance\n     - A `PIL.Image.Image` instance\n3. Decorate your plotting function with a `@render.plot` decorator.\n   - If your plotting function is not the same as the `id` you used in the `ui.output_plot()`, you can add an additional `@output(id=...)` decorator.\n   - If you use the `@output()` decorator, make sure it is **above** the `@render.plot` decorator.\n\nYou can use a plot as an input widget, collecting the locations of user clicks, double clicks, hovers, and brushes. To do this, follow the instructions provided for [plots as inputs](https:\/\/shiny.posit.co\/py\/components\/outputs\/plot-seaborn\/plot-matplotlib.html#plots-as-inputs).","meta_canonical":"co,posit!shiny,\/components\/outputs\/plot-seaborn\/ s443"}

3. Robots.txt Check

Query:

Response:

4. Spam/Ban Check

Query:

Response:

5. Seen Status Check

ℹ️ Skipped - page is already crawled

🚫

NOT INDEXABLE

✅

CRAWLED

11 days ago

🤖

ROBOTS ALLOWED

Page Info Filters

Filter	Status	Condition	Details
HTTP status	PASS	`download_http_code = 200`	HTTP 200
Age cutoff	PASS	`download_stamp > now() - 6 MONTH`	0.4 months ago
History drop	PASS	`isNull(history_drop_reason)`	No drop reason
Spam/ban	PASS	`fh_dont_index != 1 AND ml_spam_score = 0`	ml_spam_score=0
Canonical	FAIL	`meta_canonical IS NULL OR = '' OR = src_unparsed`	co,posit!shiny,/components/outputs/plot-seaborn/ s443

Page Details

Property	Value
URL	https://shiny.posit.co/py/components/outputs/plot-seaborn/
Last Crawled	2026-04-02 23:57:17 (11 days ago)
First Indexed	2024-12-20 21:55:26 (1 year ago)
HTTP Status Code	200
Meta Title	Plot (Seaborn) – Shiny for Python
Meta Description	null
Meta Canonical	co,posit!shiny,/components/outputs/plot-seaborn/ s443
Boilerpipe Text	#\| '!! shinylive warning !!': \| #\| shinylive does not work in self-contained HTML documents. #\| Please set `embed-resources: false` in your metadata. #\| standalone: true #\| components: [viewer] #\| viewerHeight: 500 import seaborn as sns from palmerpenguins import load_penguins from shiny import App, render, ui penguins = load_penguins() app_ui = ui.page_fluid( ui.input_slider("n", "Number of bins", 1, 100, 20), ui.output_plot("plot"), ) def server(input, output, session): @render.plot(alt="A Seaborn histogram on penguin body mass in grams.") def plot(): ax = sns.histplot(data=penguins, x="body_mass_g", bins=input.n()) ax.set_title("Palmer Penguins") ax.set_xlabel("Mass (g)") ax.set_ylabel("Count") return ax app = App(app_ui, server, debug=True) Express Core import seaborn as sns from palmerpenguins import load_penguins from shiny.express import input , render, ui penguins = load_penguins() ui.input_slider( "n" , "Number of bins" , 1 , 100 , 20 ) @render.plot (alt = "A Seaborn histogram on penguin body mass in grams." ) def plot(): ax = sns.histplot(data = penguins, x = "body_mass_g" , bins = input .n()) ax.set_title( "Palmer Penguins" ) ax.set_xlabel( "Mass (g)" ) ax.set_ylabel( "Count" ) return ax import seaborn as sns from palmerpenguins import load_penguins from shiny import App, render, ui penguins = load_penguins() app_ui = ui.page_fluid( ui.input_slider( "n" , "Number of bins" , 1 , 100 , 20 ), ui.output_plot( "plot" ), ) def server( input , output, session): @render.plot (alt = "A Seaborn histogram on penguin body mass in grams." ) def plot(): ax = sns.histplot(data = penguins, x = "body_mass_g" , bins = input .n()) ax.set_title( "Palmer Penguins" ) ax.set_xlabel( "Mass (g)" ) ax.set_ylabel( "Count" ) return ax app = App(app_ui, server, debug = True ) No matching items Relevant Functions ui.output_plot ui.output_plot(id, width='100%', height='400px', , inline=False, click=False, dblclick=False, hover=False, brush=False, fill=MISSING) @render.plot render.plot(_fn=None, , alt=None, width=MISSING, height=MISSING, **kwargs) No matching items Details Seaborn is a statistical plotting library that builds on top of Matplotlib. Follow these steps to display a Seaborn figure in your app: Add ui.output_plot() to the UI of your app to create a div in which to display the figure. Where you call this function will determine where the figure will appear within the layout of the app. The id parameter you provide will be used to link to other parts of the Shiny app. Define a function within the server() function that creates the figure. The name of the function should be the same value you passed into the id parameter in your ui.output_plot() function call in the UI. If your function calls reactive values, Shiny will update your figure whenever those values change, in a reactive fashion . Your function should return one of the following objects: A matplotlib.figure.Figure instance A matplotlib.artist.Artist instance A list/tuple of Figure / Artist instances An object with a ‘figure’ attribute pointing to a matplotlib.figure.Figure instance A PIL.Image.Image instance Decorate your plotting function with a @render.plot decorator. If your plotting function is not the same as the id you used in the ui.output_plot() , you can add an additional @output(id=...) decorator. If you use the @output() decorator, make sure it is above the @render.plot decorator. You can use a plot as an input widget, collecting the locations of user clicks, double clicks, hovers, and brushes. To do this, follow the instructions provided for plots as inputs .
Markdown	[![The logo for Shiny for Python](https://shiny.posit.co/py/shiny-for-python.svg)](https://shiny.posit.co/py/index.html) [Shiny for Python](https://shiny.posit.co/py/index.html) - [Get Started](https://shiny.posit.co/py/get-started/index.html) - [Concepts](https://shiny.posit.co/py/docs/overview.html) - [Components](https://shiny.posit.co/py/components/outputs/plot-seaborn/) - [Components](https://shiny.posit.co/py/components/index.html) - [Layouts](https://shiny.posit.co/py/layouts/index.html) - [Templates](https://shiny.posit.co/py/templates/index.html) - [Gallery](https://shiny.posit.co/py/gallery/index.html) - [Playground](https://shinylive.io/py/examples/) - [Reference](https://shiny.posit.co/py/components/outputs/plot-seaborn/) - [Shiny Express](https://shiny.posit.co/py/api/express/index.html) - [Shiny Core](https://shiny.posit.co/py/api/core/index.html) - [Testing](https://shiny.posit.co/py/api/testing/index.html) 1. [![](https://shiny.posit.co/py/images/bar-chart-line-fill.svg)Outputs](https://shiny.posit.co/py/components/outputs/data-grid/index.html) 2. [Plot (Seaborn)](https://shiny.posit.co/py/components/outputs/plot-seaborn/index.html) - [![](https://shiny.posit.co/py/images/blank-pixel.png)COMPONENTS](https://shiny.posit.co/py/components/) - [![](https://shiny.posit.co/py/images/sliders.svg)Inputs]() - [Action Button](https://shiny.posit.co/py/components/inputs/action-button/index.html) - [Action Link](https://shiny.posit.co/py/components/inputs/action-link/index.html) - [Checkbox](https://shiny.posit.co/py/components/inputs/checkbox/index.html) - [Checkbox Group](https://shiny.posit.co/py/components/inputs/checkbox-group/index.html) - [Dark Mode Switch](https://shiny.posit.co/py/components/inputs/dark-mode/index.html) - [Date Range Selector](https://shiny.posit.co/py/components/inputs/date-range-selector/index.html) - [Date Selector](https://shiny.posit.co/py/components/inputs/date-selector/index.html) - [File Input](https://shiny.posit.co/py/components/inputs/file/index.html) - [Numeric Input](https://shiny.posit.co/py/components/inputs/numeric-input/index.html) - [Password Field](https://shiny.posit.co/py/components/inputs/password-field/index.html) - [Radio Buttons](https://shiny.posit.co/py/components/inputs/radio-buttons/index.html) - [Select (Single)](https://shiny.posit.co/py/components/inputs/select-single/index.html) - [Select (Multiple)](https://shiny.posit.co/py/components/inputs/select-multiple/index.html) - [Selectize (Single)](https://shiny.posit.co/py/components/inputs/selectize-single/index.html) - [Selectize (Multiple)](https://shiny.posit.co/py/components/inputs/selectize-multiple/index.html) - [Slider](https://shiny.posit.co/py/components/inputs/slider/index.html) - [Slider Range](https://shiny.posit.co/py/components/inputs/slider-range/index.html) - [Switch](https://shiny.posit.co/py/components/inputs/switch/index.html) - [Text Area](https://shiny.posit.co/py/components/inputs/text-area/index.html) - [Text Box](https://shiny.posit.co/py/components/inputs/text-box/index.html) - [Toolbar Button](https://shiny.posit.co/py/components/inputs/toolbar-button/index.html) - [Toolbar Select](https://shiny.posit.co/py/components/inputs/toolbar-select/index.html) - [![](https://shiny.posit.co/py/images/bar-chart-line-fill.svg)Outputs]() - [Data Grid](https://shiny.posit.co/py/components/outputs/data-grid/index.html) - [Data Table](https://shiny.posit.co/py/components/outputs/data-table/index.html) - [Image](https://shiny.posit.co/py/components/outputs/image/index.html) - [Map (ipyleaflet)](https://shiny.posit.co/py/components/outputs/map-ipyleaflet/index.html) - [Plot (Matplotlib)](https://shiny.posit.co/py/components/outputs/plot-matplotlib/index.html) - [Plot (Plotly)](https://shiny.posit.co/py/components/outputs/plot-plotly/index.html) - [Plot (Seaborn)](https://shiny.posit.co/py/components/outputs/plot-seaborn/index.html) - [Text](https://shiny.posit.co/py/components/outputs/text/index.html) - [UI](https://shiny.posit.co/py/components/outputs/ui/index.html) - [Value Box](https://shiny.posit.co/py/components/outputs/value-box/index.html) - [Verbatim Text](https://shiny.posit.co/py/components/outputs/verbatim-text/index.html) - [![](https://shiny.posit.co/py/images/chat-dots-fill.svg)Display Messages]() - [Chat](https://shiny.posit.co/py/components/display-messages/chat/index.html) - [Modal](https://shiny.posit.co/py/components/display-messages/modal/index.html) - [Notifications](https://shiny.posit.co/py/components/display-messages/notifications/index.html) - [Progress Bar](https://shiny.posit.co/py/components/display-messages/progress-bar/index.html) - [Tooltips](https://shiny.posit.co/py/components/display-messages/tooltips/index.html) - [![](https://shiny.posit.co/py/images/cards-blue.svg)Layout]() - [Card](https://shiny.posit.co/py/components/layout/cards/index.html) - [Toolbar](https://shiny.posit.co/py/components/layout/toolbar/index.html) 1. [![](https://shiny.posit.co/py/images/bar-chart-line-fill.svg)Outputs](https://shiny.posit.co/py/components/outputs/data-grid/index.html) 2. [Plot (Seaborn)](https://shiny.posit.co/py/components/outputs/plot-seaborn/index.html) # Plot (Seaborn) ``` ``` - [Express]() - [Core]() ``` ``` ``` ``` No matching items ## Relevant Functions - [ui.output\_plot](https://shiny.posit.co/py/api/ui.output_plot.html) `ui.output_plot(id, width='100%', height='400px', , inline=False, click=False, dblclick=False, hover=False, brush=False, fill=MISSING)` - [@render.plot](https://shiny.posit.co/py/api/render.plot.html) `render.plot(_fn=None, , alt=None, width=MISSING, height=MISSING, kwargs)` No matching items ## Details Seaborn is a statistical plotting library that builds on top of Matplotlib. Follow these steps to display a Seaborn figure in your app: 1. Add `ui.output_plot()` to the UI of your app to create a div in which to display the figure. Where you call this function will determine where the figure will appear within the layout of the app. The `id` parameter you provide will be used to link to other parts of the Shiny app. 2. Define a function within the `server()` function that creates the figure. - The name of the function should be the same value you passed into the `id` parameter in your `ui.output_plot()` function call in the UI. - If your function calls reactive values, Shiny will update your figure whenever those values change, in a [reactive fashion](https://shiny.posit.co/py/docs/reactive-programming.html). - Your function should return one of the following objects: - A `matplotlib.figure.Figure` instance - A `matplotlib.artist.Artist` instance - A list/tuple of `Figure`/`Artist` instances - An object with a ‘figure’ attribute pointing to a `matplotlib.figure.Figure` instance - A `PIL.Image.Image` instance 3. Decorate your plotting function with a `@render.plot` decorator. - If your plotting function is not the same as the `id` you used in the `ui.output_plot()`, you can add an additional `@output(id=...)` decorator. - If you use the `@output()` decorator, make sure it is above** the `@render.plot` decorator. You can use a plot as an input widget, collecting the locations of user clicks, double clicks, hovers, and brushes. To do this, follow the instructions provided for [plots as inputs](https://shiny.posit.co/py/components/outputs/plot-seaborn/plot-matplotlib.html#plots-as-inputs). [Plot (Plotly)](https://shiny.posit.co/py/components/outputs/plot-plotly/index.html) [Text](https://shiny.posit.co/py/components/outputs/text/index.html) Proudly supported by [![Posit](https://shiny.posit.co/py/images/posit-logo-black.svg)](https://www.posit.co/)
Readable Markdown	``` #\| '!! shinylive warning !!': \| #\| shinylive does not work in self-contained HTML documents. #\| Please set `embed-resources: false` in your metadata. #\| standalone: true #\| components: [viewer] #\| viewerHeight: 500 import seaborn as sns from palmerpenguins import load_penguins from shiny import App, render, ui penguins = load_penguins() app_ui = ui.page_fluid( ui.input_slider("n", "Number of bins", 1, 100, 20), ui.output_plot("plot"), ) def server(input, output, session): @render.plot(alt="A Seaborn histogram on penguin body mass in grams.") def plot(): ax = sns.histplot(data=penguins, x="body_mass_g", bins=input.n()) ax.set_title("Palmer Penguins") ax.set_xlabel("Mass (g)") ax.set_ylabel("Count") return ax app = App(app_ui, server, debug=True) ``` - [Express]() - [Core]() ``` import seaborn as sns from palmerpenguins import load_penguins from shiny.express import input, render, ui penguins = load_penguins() ui.input_slider("n", "Number of bins", 1, 100, 20) @render.plot(alt="A Seaborn histogram on penguin body mass in grams.") def plot(): ax = sns.histplot(data=penguins, x="body_mass_g", bins=input.n()) ax.set_title("Palmer Penguins") ax.set_xlabel("Mass (g)") ax.set_ylabel("Count") return ax ``` ``` import seaborn as sns from palmerpenguins import load_penguins from shiny import App, render, ui penguins = load_penguins() app_ui = ui.page_fluid( ui.input_slider("n", "Number of bins", 1, 100, 20), ui.output_plot("plot"), ) def server(input, output, session): @render.plot(alt="A Seaborn histogram on penguin body mass in grams.") def plot(): ax = sns.histplot(data=penguins, x="body_mass_g", bins=input.n()) ax.set_title("Palmer Penguins") ax.set_xlabel("Mass (g)") ax.set_ylabel("Count") return ax app = App(app_ui, server, debug=True) ``` No matching items ## Relevant Functions - [ui.output\_plot](https://shiny.posit.co/py/api/ui.output_plot.html) `ui.output_plot(id, width='100%', height='400px', , inline=False, click=False, dblclick=False, hover=False, brush=False, fill=MISSING)` - [@render.plot](https://shiny.posit.co/py/api/render.plot.html) `render.plot(_fn=None, , alt=None, width=MISSING, height=MISSING, kwargs)` No matching items ## Details Seaborn is a statistical plotting library that builds on top of Matplotlib. Follow these steps to display a Seaborn figure in your app: 1. Add `ui.output_plot()` to the UI of your app to create a div in which to display the figure. Where you call this function will determine where the figure will appear within the layout of the app. The `id` parameter you provide will be used to link to other parts of the Shiny app. 2. Define a function within the `server()` function that creates the figure. - The name of the function should be the same value you passed into the `id` parameter in your `ui.output_plot()` function call in the UI. - If your function calls reactive values, Shiny will update your figure whenever those values change, in a [reactive fashion](https://shiny.posit.co/py/docs/reactive-programming.html). - Your function should return one of the following objects: - A `matplotlib.figure.Figure` instance - A `matplotlib.artist.Artist` instance - A list/tuple of `Figure`/`Artist` instances - An object with a ‘figure’ attribute pointing to a `matplotlib.figure.Figure` instance - A `PIL.Image.Image` instance 3. Decorate your plotting function with a `@render.plot` decorator. - If your plotting function is not the same as the `id` you used in the `ui.output_plot()`, you can add an additional `@output(id=...)` decorator. - If you use the `@output()` decorator, make sure it is above** the `@render.plot` decorator. You can use a plot as an input widget, collecting the locations of user clicks, double clicks, hovers, and brushes. To do this, follow the instructions provided for [plots as inputs](https://shiny.posit.co/py/components/outputs/plot-seaborn/plot-matplotlib.html#plots-as-inputs).
Shard	70 (laksa)
Root Hash	17512250694148690070
Unparsed URL	co,posit!shiny,/py/components/outputs/plot-seaborn/ s443