Plots List
Plots
This endpoint handles manipulation of Plotly plot files.
Reference
Authorization
Any user with or without a Plotly account may view public plots. For private plots, see authentication.
Actions
list
Listing all public plots can be done via a GET request to this endpoint.
By default, plots will be listed in order of date created. The order_by
query parameter is accepted at this endpoint. Currently, only ordering by
views is supported. It is possible to filter the plots by quality
with min_quality or max_quality as query parameter.
Example:
// GET https://api.plotly.com/v2/plots/ ---> 200
// GET https://api.plotly.com/v2/plots/?order_by=-views ---> 200
// GET https://api.plotly.com/v2/plots/?min_quality=5 ---> 200
// GET https://api.plotly.com/v2/plots/?max_quality=5 ---> 200
feed
Listing all handpicked feed plots can be done via a GET request to this endpoint. By default, plots will be listed in a random order.
Example:
// GET https://api.plotly.com/v2/plots/feed ---> 200
create
You can create new plot resources here. The only required field is 'figure'. Currently, the figure is restricted to only contain references to grid data. That is, this will fail if raw data arrays are passed in. To create and manipulate underlying grids for plots, see the grids endpoint.
Example:
// This fails because a figure field is required.
// POST https://api.plotly.com/v2/plots ---> 400 Bad Request
{}
// This fails because the figure has raw data
//POST https://api.plotly.com/v2/plots ---> 400 Bad Request
{
"figure": {"data": [{"y": ['this', 'is', 'raw', 'data']}]}
}
// This succeeds because the figure has src keys, not raw data.
//POST https://api.plotly.com/v2/plots ---> 200 OK
{
"figure": {"data": [{"ysrc": "sven:88:u8nd62"}]}
}
When creating a grid, you can optionally specify a source_fid to specify where a plot has come from:
- source_fid: the fid of a plot that was copied (and presumably edited) to produce this one
detail
There is a lot of meta information stored about plot files including filename, title, share_url, and content_url to name a few.
This information can only be reached with a GET to this endpoint.
Example:
// GET https://api.plotly.com/v2/plots/iheartgraphs:90
content
The contents of a plot can be downloaded via the content resource. The plot
content contains referenced grid/column data by default. If you wish to
return the raw grid/column data, the inline_data=true query must be included
in the request url. The Content-Type header will be appropriately set for the
response body.
Alternatively, you can set ?map_data=unreadable to append a mapping of
sources to data that belongs to grids which are unreadable for the
requestor. This is useful when you have read access to another users plot,
but that plot contains grid references which you don't have access to.
Examples:
// Returns referenced grid/column data
// GET https://api.plotly.com/v2/plots/iheartgraphs:90/content ---> 200 OK
// Returns full grid/column data
// GET https://api.plotly.com/v2/plots/iheartgraphs:90/content?inline_data=true ---> 200 OK
// Returns full grid/column data when requestor doesn't have permission
// to read the referenced grid.
// GET https://api.plotly.com/v2/plots/iheartgraphs:90/content?map_data=unreadable ---> 200 OK
GET /v2/plots?cursor=cD0yMDI1LTA5LTA4KzEwJTNBNDMlM0EzOC45NjYxMzElMkIwMCUzQTAw&format=api
{ "next": "https://api.plotly.com/v2/plots?cursor=cD0yMDI1LTA5LTA4KzA3JTNBNTAlM0EwMy44ODM5NDMlMkIwMCUzQTAw&format=api", "previous": "https://api.plotly.com/v2/plots?cursor=cj0xJnA9MjAyNS0wOS0wOCsxMCUzQTI5JTNBMzcuMDM1MTA1JTJCMDAlM0EwMA%3D%3D&format=api", "results": [ { "creation_time": "2025-09-08T10:29:37.035105Z", "comments": { "results": [], "count": 0 }, "parented": true, "embed_url": "https://chart-studio.plotly.com/~marsocca/40.embed", "fid": "marsocca:40", "filename": "CITOGEN 08.09", "filetype": "plot", "img_url": "https://storage.googleapis.com/plotly-prod-images/marsocca/40/9_OU5RQ45GLPI8FW98PZDFRLCV7JESY9.png", "image_urls": { "default": "https://storage.googleapis.com/plotly-prod-images/marsocca/40/2_T6YAHHGS0KBIA5SVJTVI56LRXRZQHY.png", "block-thumb": "https://storage.googleapis.com/plotly-prod-images/marsocca/40/8_KFL6ULT12N9X2V4ZPCYPLD887Q433G.png", "list-thumb": "https://storage.googleapis.com/plotly-prod-images/marsocca/40/9_OU5RQ45GLPI8FW98PZDFRLCV7JESY9.png" }, "api_urls": { "files": "https://api.plotly.com/v2/files/marsocca:40", "plots": "https://api.plotly.com/v2/plots/marsocca:40", "parent": "https://api.plotly.com/v2/folders/home?user=marsocca" }, "owner": "marsocca", "parent": -1, "preview": "", "referencers": [], "references": [], "title": "", "views": 4, "web_url": "https://chart-studio.plotly.com/~marsocca/40/", "world_readable": true, "date_modified": "2025-09-08T10:31:23.433Z", "stars": { "results": [], "count": 0 }, "collaborators": { "results": [], "count": 0 }, "subfolder_count": null, "refresh_interval": null, "organize_view_url": "https://chart-studio.plotly.com/~marsocca/40/", "current_user_permission": "read", "is_theme": null, "is_template": false, "autosize": true, "caption": "", "figure": { "data": [ { "meta": { "columnNames": { "ids": "A", "text": "", "labels": "D", "values": "C", "parents": "B" } }, "mode": "markers", "name": "<b>#75</b>", "sort": true, "type": "sunburst", "level": "0", "idssrc": "marsocca:39:81060f", "marker": { "line": { "color": "rgb(253, 252, 252)", "width": 3 } }, "rotation": 0, "textfont": { "size": 30, "color": "rgb(1, 10, 24)", "family": "Arial" }, "labelssrc": "marsocca:39:767188", "valuessrc": "marsocca:39:2636ca", "parentssrc": "marsocca:39:f26fa8", "branchvalues": "total", "texttemplate": "", "insidetextfont": { "size": 20, "family": "Arial Black" }, "outsidetextfont": { "size": 25, "family": "Arial Black" }, "insidetextorientation": "horizontal" } ], "frames": [], "layout": { "font": { "size": 20, "family": "Arial Black" }, "title": { "x": 0, "font": { "size": 18, "family": "\"Open Sans\", verdana, arial, sans-serif" }, "text": "" }, "xaxis": { "range": [ -1, 6 ], "autorange": true }, "yaxis": { "range": [ -1, 4 ], "autorange": true }, "images": [ { "x": 0.22, "y": 0.35, "sizex": 0.33, "sizey": 0.37, "source": 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