Charts cards

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Cards in this section are used to visualize data. Some of these cards aggregate (“group by”) the data by category, and the output aggregations can be used as inputs to other cards. Review the documentation on creating and configuring charts for more information.

• Bar chart
• Line chart
• Overlay chart
• Pie chart
• Categorical formula plot
• Function on objects plot
• Segment formula plot
• Transform table plot
• Categorical scatter plot
• Numerical scatter plot
• Scatter plot regression
• Time series scatter plot
• Events timeline
• Time series distribution
• Correlation matrix
• Heat grid
• Time series heat grid
• Map
• Media property
• Vega plot

Bar chart

Create a horizontal or vertically oriented bar plot of your objects. Bar chart categories are determined by your object properties, and you can set values to count objects or show an aggregation of a property value or values. You can also use a bar chart to convert data into a time series.

• Supported aggregation metrics: min, max, sum, average, count, unique count, percentile, standard deviation, and variance
• Percentile, standard deviation, and variance metrics are not supported for object types backed by Object Storage V1 (Phonograph).

Line chart

Create a line plot with categories determined by your object properties. Set values to count objects or an aggregation of a property value or values.

• Supported aggregation metrics: min, max, sum, average, count, unique count, percentile, standard deviation, and variance
• Percentile, standard deviation, and variance metrics are not supported for object types backed by Object Storage V1 (Phonograph).

Overlay chart

Combine line charts, bar charts and categorical scatter plots on the same set of axes. The overlay plot will not mandate using the same set of axes, but using consistent categories is recommended.

Pie chart

Create a pie chart with categories determined by your object properties. Set values to count objects or show an aggregation of a property value or values.

• Supported aggregation metrics: min, max, sum, average, count, unique count, percentile, standard deviation, and variance
• Percentile, standard deviation, and variance metrics are not supported for object types backed by Object Storage V1 (Phonograph).

Categorical formula plot

Create a new categorical (bar, line, scatter) plot by computing a function on overlapping categories of existing categorical plots. Numerics, from aggregations or parameters, can also be in the formula.

• In the example below, we add two bar plots together and multiply by the value of a numeric parameter. When writing formulas here, computation between bar plots will be run on matching segments and group-by categories. Single numerical values will be applied to all bars.

Function on objects plot

Use a Function to create a categorical chart (bar, line, scatter) in Quiver.

Segment formula plot

Create a new categorical plot by applying formulas to specific segments shown in a categorical plot (for example, to scale certain segments by certain scalar values). Numbers, from aggregations or parameters, can also be in the formula.

Transform table plot

Create a categorical chart (bar, line, or scatter) using data from a transform table. In the editor, use the Data tab to select the input transform table, and define the groups as well as segments (optional). Use the Display tab to change the visualization type and other display options.

• Supported aggregation metrics: min, max, sum, average, count, unique count, percentile, standard deviation, and variance

Categorical scatter plot

Create a line plot with categories determined by your object properties. Set values to count objects, or show an aggregation of a property value or values.

• Supported aggregation metrics: min, max, sum, average, count, unique count, percentile, standard deviation, and variance
• Percentile, standard deviation, and variance metrics are not supported for object types backed by Object Storage V1 (Phonograph).

Numerical scatter plot

Plot any pair of numerical properties against one another.

Scatter plot regression

Scatter plot regression is used to view the best-fit regression line over a time series scatter plot.

• Linear, polynomial (of degree 0-13), or exponential regression fits can be chosen.
• The time range used to compute the best fit line is set by default to be the source plot zoom range, but can be modified to match a range instead.

Time series scatter plot

Scatter plots can be used to plot two series against each other. Points of the underlying series will automatically be aggregated (using the average value over buckets that are 1/1000 of the underlying time range) before plotting.

• Both the bucketing strategy (the number of buckets and points per bucket), and the bucket value (for example, average, sum, max) can be specified.
• The range for each series included in the cross plot is automatically set to underlying the plot zoom range, but can be modified to a manual range instead.

Events timeline

View an object set of events through time, segmented into categories if desired.

Does not support transform tables and only takes in an event sets as input. Consider using Vega plots as an alternative visualization for an events timeline.

Time series distribution

Distribution charts show the aggregate counts of the y-axis value of series.

• By default, the entire time range is used, but a time range parameter can be used to specify a certain time range.
• The number of bins can also be specified to change the frequency of the graph.

Correlation matrix

Create a correlation matrix between properties of an object set. Select the correlation type (Pearson or Spearman) in the Display tab.

Heat grid

Display a chart in three dimensions, showing two categorical dimensions and an aggregate dimension by color.

• Supported aggregation metrics: min, max, sum, average, count, unique count, percentile, standard deviation, and variance
• Percentile, standard deviation, and variance metrics are not supported for object types backed by Object Storage V1 (Phonograph).

Time series heat grid

Heat grids display a two-dimensional aggregate value grid of two time series. Heat grids are similar to scatter plots, but instead color by the density of points appearing in the same bucket.

Map

Visualize one or more object sets on a map. Maps are backed by geospatial data (geohashes, GeoJSON, and region codes) that can be charted in a variety of ways. You can find a detailed description of map layer configurations in the Workshop map widget documentation.

• Point layers plot each object at a specific location on the map.
• Clusters take a group of points and dynamically combine them based on zoom level.
• Choropleth layers can aggregate an entire region to plot shaded areas of the map.
• Line segments are used to connect multiple points using a collection of straight lines.

Media property

Render media attached to an object property.

Vega plot

Create fully customizable visualizations using the Vega and Vega-Lite libraries. See the Vega plot page for more details.