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‎CHANGELOG.md

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All notable changes to this project will be documented in this file.
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This project adheres to [Semantic Versioning](http://semver.org/).
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## UNRELEASED
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### Updated
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- Updated Plotly.js to from version 2.12.1 to version 2.13.2. See the [plotly.js CHANGELOG](https://github.com/plotly/plotly.js/blob/master/CHANGELOG.md#2132----2022-07-21) for more information. Notable changes include:
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- Add `selections`, `newselection` and `activeselection` layout attributes to have persistent and editable selections over cartesian subplots
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- Add `unselected.line.color` and `unselected.line.opacity` options to `parcoords` trace
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- Display Plotly's new logo in the modebar
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## [5.9.0] - 2022-06-23
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‎doc/python/hover-text-and-formatting.md

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### Customizing hover text with a hovertemplate
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To customize the tooltip on your graph you can use the [hovertemplate](https://plotly.com/python/reference/pie/#pie-hovertemplate) attribute of `graph_objects` tracces, which is a template string used for rendering the information that appear on hoverbox.
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To customize the tooltip on your graph you can use the [hovertemplate](https://plotly.com/python/reference/pie/#pie-hovertemplate) attribute of `graph_objects` traces, which is a template string used for rendering the information that appear on hoverbox.
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This template string can include `variables` in %{variable} format, `numbers` in [d3-format's syntax](https://github.com/d3/d3-3.x-api-reference/blob/master/Formatting.md#d3_format), and `date` in [d3-time-format's syntax](https://github.com/d3/d3-time-format). In the example below, the empty `<extra></extra>` tag removes the part of the hover where the trace name is usually displayed in a contrasting color. The `<extra>` tag can be used to display other parts of the hovertemplate, it is not reserved for the trace name.
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Note that a hovertemplate customizes the tooltip text, while a [texttemplate](https://plotly.com/python/reference/pie/#pie-texttemplate) customizes the text that appears on your chart. <br>

‎packages/javascript/jupyterlab-plotly/package-lock.json

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‎packages/javascript/jupyterlab-plotly/package.json

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"@lumino/messaging": "^1.2.3",
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"@lumino/widgets": "^1.8.1",
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"lodash": "^4.17.4",
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"plotly.js": "^2.12.1"
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"plotly.js": "^2.13.2"
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},
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"jupyterlab": {
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"extension": "lib/jupyterlab-plugin",

‎packages/python/plotly/codegen/resources/plot-schema.json

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‎packages/python/plotly/plotly/graph_objs/_box.py

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Sets the method used to compute the sample's Q1 and Q3
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quartiles. The "linear" method uses the 25th percentile for Q1
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and 75th percentile for Q3 as computed using method #10 (listed
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on http://www.amstat.org/publications/jse/v14n3/langford.html).
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The "exclusive" method uses the median to divide the ordered
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dataset into two halves if the sample is odd, it does not
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include the median in either half - Q1 is then the median of
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the lower half and Q3 the median of the upper half. The
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"inclusive" method also uses the median to divide the ordered
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dataset into two halves but if the sample is odd, it includes
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the median in both halves - Q1 is then the median of the lower
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half and Q3 the median of the upper half.
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on http://jse.amstat.org/v14n3/langford.html). The "exclusive"
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method uses the median to divide the ordered dataset into two
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halves if the sample is odd, it does not include the median in
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either half - Q1 is then the median of the lower half and Q3
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the median of the upper half. The "inclusive" method also uses
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the median to divide the ordered dataset into two halves but if
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the sample is odd, it includes the median in both halves - Q1
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is then the median of the lower half and Q3 the median of the
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upper half.
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The 'quartilemethod' property is an enumeration that may be specified as:
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- One of the following enumeration values:
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Sets the method used to compute the sample's Q1 and Q3
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quartiles. The "linear" method uses the 25th percentile
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for Q1 and 75th percentile for Q3 as computed using
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method #10 (listed on http://www.amstat.org/publication
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s/jse/v14n3/langford.html). The "exclusive" method uses
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the median to divide the ordered dataset into two
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halves if the sample is odd, it does not include the
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median in either half - Q1 is then the median of the
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lower half and Q3 the median of the upper half. The
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"inclusive" method also uses the median to divide the
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ordered dataset into two halves but if the sample is
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odd, it includes the median in both halves - Q1 is then
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the median of the lower half and Q3 the median of the
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upper half.
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method #10 (listed on
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http://jse.amstat.org/v14n3/langford.html). The
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"exclusive" method uses the median to divide the
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ordered dataset into two halves if the sample is odd,
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it does not include the median in either half - Q1 is
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then the median of the lower half and Q3 the median of
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the upper half. The "inclusive" method also uses the
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median to divide the ordered dataset into two halves
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but if the sample is odd, it includes the median in
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both halves - Q1 is then the median of the lower half
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and Q3 the median of the upper half.
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sd
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Sets the standard deviation values. There should be as
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many items as the number of boxes desired. This
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Sets the method used to compute the sample's Q1 and Q3
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quartiles. The "linear" method uses the 25th percentile
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for Q1 and 75th percentile for Q3 as computed using
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method #10 (listed on http://www.amstat.org/publication
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s/jse/v14n3/langford.html). The "exclusive" method uses
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the median to divide the ordered dataset into two
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halves if the sample is odd, it does not include the
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median in either half - Q1 is then the median of the
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lower half and Q3 the median of the upper half. The
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"inclusive" method also uses the median to divide the
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ordered dataset into two halves but if the sample is
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odd, it includes the median in both halves - Q1 is then
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the median of the lower half and Q3 the median of the
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upper half.
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method #10 (listed on
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http://jse.amstat.org/v14n3/langford.html). The
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"exclusive" method uses the median to divide the
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ordered dataset into two halves if the sample is odd,
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it does not include the median in either half - Q1 is
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then the median of the lower half and Q3 the median of
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the upper half. The "inclusive" method also uses the
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median to divide the ordered dataset into two halves
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but if the sample is odd, it includes the median in
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both halves - Q1 is then the median of the lower half
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and Q3 the median of the upper half.
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sd
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Sets the standard deviation values. There should be as
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many items as the number of boxes desired. This

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