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Copy file name to clipboardExpand all lines: doc/python/dumbbell-plots.md
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## Basic Dumbbell Plot
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Dumbbell plots are useful for demonstrating change between two sets of data points, for example, the population change for a selection of countries for two different years
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Dumbbell plots are useful for demonstrating change between two sets of data points, for example, the population change for a selection of countries for two different years.
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In this example, we compare life expectancy in 1952 with life expectancy in 2002 for countries in Europe.
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*Note: The `arrow`, `angleref`, and `standoff` properties used on the `marker` in this example are new in 5.11*
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In this example, we add arrow markers to the plot. The first trace adds the lines connecting the data points and arrow markers.
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In this example, we add arrow markers to the plot. The first trace adds the lines connecting the data points and arrow markers.
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The second trace adds circle markers. On the first trace, we use `standoff=8` to position the arrow marker back from the data point.
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For the arrow marker to point directly at the circle marker, this value should be half the circle marker size.
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For the arrow marker to point directly at the circle marker, this value should be half the circle marker size.
Copy file name to clipboardExpand all lines: doc/python/legend.md
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*New in 5.11*
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Set the width of hozitonal legend entries by setting `entrywidth`. Here we set it to `70` pixels. Pixels is the default unit for `entrywidth`, but you can set it to be a fraction of the plot width using `entrywidthmode='fraction`.
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Set the width of horizontal legend entries by setting `entrywidth`. Here we set it to `70` pixels. Pixels is the default unit for `entrywidth`, but you can set it to be a fraction of the plot width using `entrywidthmode='fraction`.
Copy file name to clipboardExpand all lines: doc/python/scattermapbox.md
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*New in 5.11*
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Display clusters of data points by setting `cluster`. Here, we enable clusters with `enabled=True`. You can also enable clusters by setting other `cluster` properties. Other available properties include `color` (for setting the color of the clusters), `size` (for setting the size of a cluster step), and `step` (for configuring how many points it takes to create a cluster or advance to the next cluster step.
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Display clusters of data points by setting `cluster`. Here, we enable clusters with `enabled=True`. You can also enable clusters by setting other `cluster` properties. Other available properties include `color` (for setting the color of the clusters), `size` (for setting the size of a cluster step), and `step` (for configuring how many points it takes to create a cluster or advance to the next cluster step).
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