Add Radar Plot Visualization Operator #3500
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I think it works well! I’ve left a few comments that need to be resolved. Also, please add your dataset for testing in the description of this PR. |
QZT168
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Jun 24, 2025
...ator/src/main/scala/edu/uci/ics/amber/operator/visualization/radarPlot/RadarPlotOpDesc.scala
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yunyad
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Jun 24, 2025
...ator/src/main/scala/edu/uci/ics/amber/operator/visualization/radarPlot/RadarPlotOpDesc.scala
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...ator/src/main/scala/edu/uci/ics/amber/operator/visualization/radarPlot/RadarPlotOpDesc.scala
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yunyad
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...ator/src/main/scala/edu/uci/ics/amber/operator/visualization/radarPlot/RadarPlotOpDesc.scala
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…electedAttributes is empty
yunyad
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Jun 24, 2025
...ator/src/main/scala/edu/uci/ics/amber/operator/visualization/radarPlot/RadarPlotOpDesc.scala
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…f max normalization specifically
…prove readability
…Frame, and handle None values
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Looks good to me! After Yunyan approves your PR, you can merge it. |
yunyad
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Jun 30, 2025
...ator/src/main/scala/edu/uci/ics/amber/operator/visualization/radarPlot/RadarPlotOpDesc.scala
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yunyad
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Jun 30, 2025
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Code quality looks much better overall. Since Plotly’s scatterpolar supports various display modes, I suggest supporting a few more commonly used ones to give users some flexibility. Full coverage isn’t necessary, but handling a few typical types (for example, color fill or not) would improve usability.
…isconnected trace lines
yunyad
reviewed
Jul 9, 2025
| override def operatorInfo: OperatorInfo = | ||
| OperatorInfo( | ||
| "Radar Plot", | ||
| "View the result in a radar plot. A radar plot displays multivariate data on multiple axes arranged in a circular layout, allowing for comparison between different entities.", |
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Just checked, I think "View the result in a radar plot." is enough.
yunyad
reviewed
Jul 9, 2025
| @AutofillAttributeNameList | ||
| var selectedAttributes: List[String] = _ | ||
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| @JsonProperty(value = "traceNameAttribute", defaultValue = "-- No Selection --", required = false) |
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remove "--", just "No Selection"
yunyad
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Jul 9, 2025
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| @JsonProperty( | ||
| value = "traceColorAttribute", | ||
| defaultValue = "-- No Selection --", |
yunyad
reviewed
Jul 9, 2025
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| val attrList = selectedAttributes.map(attr => s""""$attr"""").mkString(", ") | ||
| val traceNameCol = traceNameAttribute match { | ||
| case "" | "-- No Selection --" => "None" |
yunyad
reviewed
Jul 9, 2025
| case col => s"'$col'" | ||
| } | ||
| val traceColorCol = traceColorAttribute match { | ||
| case "" | "-- No Selection --" => "None" |
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This PR introduces a new visualization operator for a Radar Plot (also known as a spider plot). Radar plots are used to visualize multivariate data, allowing for comparison of different entities across the multiple variables. Typically, they are used to determine strengths and weaknesses of entities compared to one another (e.g. how our product compares to a competitor’s). They are also effective in showing outliers and commonalities across the entities. This Radar Plot visualization operator allows the user to select which numeric columns will be used as the radar axes, and optionally select a column whose value will be used to determine the name or color for the corresponding radar trace (the visual representation of that entity in the plot). Users can also toggle other customization features, such as to normalize the values for each radar axis, in order to prevent a representation that skews towards axes with higher values.
Changed files:
Property Selection:
Normalized Result:
Non-Normalized Result:
Additional Example:
Testing Datasets:
diabetes_mini.csv
diabetes_mini_missing_column.csv
diabetes_mini_missing_values.csv
product_data.csv