2015-04-01 23:39:33 +02:00
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[[line-chart]]
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2015-03-09 06:30:42 +01:00
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=== Line Charts
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This chart's Y axis is the _metrics_ axis. The following aggregations are available for this axis:
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include::y-axis-aggs.asciidoc[]
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Before you choose a buckets aggregation, specify if you are splitting slices within a single chart or splitting into
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multiple charts. A multiple chart split must run before any other aggregations. When you split a chart, you can change
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if the splits are displayed in a row or a column by clicking the *Rows | Columns* selector.
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include::x-axis-aggs.asciidoc[]
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You can click the *Advanced* link to display more customization options for your metrics or bucket aggregation:
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*Exclude Pattern*:: Specify a pattern in this field to exclude from the results.
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*Exclude Pattern Flags*:: A standard set of Java flags for the exclusion pattern.
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*Include Pattern*:: Specify a pattern in this field to include in the results.
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*Include Pattern Flags*:: A standard set of Java flags for the inclusion pattern.
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*JSON Input*:: A text field where you can add specific JSON-formatted properties to merge with the aggregation
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definition, as in the following example:
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[source,shell]
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{ "script" : "doc['grade'].value * 1.2" }
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NOTE: In Elasticsearch releases 1.4.3 and later, this functionality requires you to enable
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2015-04-02 01:53:00 +02:00
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{ref}/modules-scripting.html[dynamic Groovy scripting].
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2015-03-09 06:30:42 +01:00
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The availability of these options varies depending on the aggregation you choose.
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2015-05-12 06:03:19 +02:00
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Select the *Options* tab to change the following aspects of the chart:
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2015-05-20 03:49:07 +02:00
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*Y-Axis Scale*:: You can select *linear*, *log*, or *square root* scales for the chart's Y axis. You can use a log
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scale to display data that varies exponentially, such as a compounding interest chart, or a square root scale to
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regularize the display of data sets with variabilities that are themselves highly variable. This kind of data, where
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the variability is itself variable over the domain being examined, is known as _heteroscedastic_ data. For example, if
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a data set of height versus weight has a relatively narrow range of variability at the short end of height, but a wider
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range at the taller end, the data set is heteroscedastic.
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*Smooth Lines*:: Check this box to curve the line from point to point. Bear in mind that smoothed lines necessarily
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affect the representation of your data and create a potential for ambiguity.
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*Show Connecting Lines*:: Check this box to draw lines between the points on the chart.
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*Show Circles*:: Check this box to draw each data point on the chart as a small circle.
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2015-05-20 03:49:07 +02:00
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*Current time marker*:: For charts of time-series data, check this box to draw a red line on the current time.
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*Set Y-Axis Extents*:: Check this box and enter values in the *y-max* and *y-min* fields to set the Y axis to specific
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values.
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2015-03-09 06:30:42 +01:00
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*Show Tooltip*:: Check this box to enable the display of tooltips.
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*Show Legend*:: Check this box to enable the display of a legend next to the chart.
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2015-05-12 06:03:19 +02:00
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*Scale Y-Axis to Data Bounds*:: The default Y-axis bounds are zero and the maximum value returned in the data. Check
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this box to change both upper and lower bounds to match the values returned in the data.
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After changing options, click the green *Apply changes* button to update your visualization, or the grey *Discard
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changes* button to keep your visualization in its current state.
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[float]
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[[bubble-chart]]
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2015-11-24 17:25:14 +01:00
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==== Bubble Charts
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2015-05-12 06:03:19 +02:00
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You can convert a line chart visualization to a bubble chart by performing the following steps:
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. Click *Add Metrics* for the visualization's Y axis, then select *Dot Size*.
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. Select a metric aggregation from the drop-down list.
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. In the *Options* tab, uncheck the *Show Connecting Lines* box.
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2015-05-18 04:31:43 +02:00
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. Click the *Apply changes* button.
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2015-11-24 17:25:14 +01:00
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[float]
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[[line-viewing-detailed-information]]
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==== Viewing Detailed Information
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include::visualization-raw-data.asciidoc[]
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