Plot Types allow you to select a specific visualization to explore and analyze your data. There are a wide variety of options built into Virtualitics Explore Desktop, ranging from Histograms to a 3D Globe. Once you've chosen your plot type, be sure to review the rest of the available parameters in the Mapping Panel.
Changing your Plot Type
- Navigate to the Top Toolbar.
- Click the Select Plot Type drop-down.
- Click the Plot Type you'd like to use.
Available Plot Types
Geospatial Plots
A 2D Map is a way of visualizing geospatial data, or data with locations. This is especially useful for detailed views of street-level data or city-level data. For larger-scale, more global data, consider using a 3D Globe. |
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Create a 2D Map
You can also add features to the Color, Size and Shape dimensions to pack a lot of information onto an easily digestible map. Plot SettingsThe 2D Map plot has a number of settings that can be changed. To do so:
ViewZoom: Click the + or - sign to zoom in or out. You can also scroll on your mouse to do the same. Select: Select an area of the map on which to focus. Click Start, make a selection on the map, and click Apply. Map ServiceChoose which mapping Provider to use and choose a map display Style (Topographic, Ocean, Imagery, or Gray). You can also add a Custom Map provider. To do so:
HeatmapBy default, each point will be visualized individually on the map. Explore offers a Heatmap to view areas of higher or lower concentrations of points. |
A 3D Globe is a way of examining geospatial data, or data with locations. This is great for visualizing global trends or country-level data. For smaller-scale, more local data, consider using a 2D Map. |
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Create a 3D Globe
Plot SettingsThe 3D Globe plot has a number of settings that can be changed. To do so:
View
Zoom: Click the + or - sign to zoom in or out. You can also scroll on your mouse to do the same. Select: Select an area of the map on which to focus. Click Start, make a selection on the map, and click Apply. This will automatically convert the plot to a 2D Map of the selected area. DisplayClick the checkboxes to toggle the visibility of longitude/latitude lines, country outlines, and country labels. HeatmapBy default, each point will be visualized individually on the map. Explore offers a Heatmap to view areas of higher or lower concentrations of points. |
Scatter-based Plots
A Scatter Plot is a common plot type that visualizes each row in your dataset as a single point on either a 2D or 3D plot. This is most helpful to view how numerical features relate to each other. By adding even more dimensions like Color, Size, and Shape to your Scatter Plots, you can recognize very complex relationships in your data. |
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Create a Scatter Plot
Additional dimensions that work well with Scatter Plots are Size, Shape, Group By, Playback, Halo, and Pulsation. For very large datasets (in the millions of points), you may want to change the Shape Options to Point Cloud to improve performance. Plot SettingsThe Scatter Plot has additional settings that can be changed. To do so:
View PointsChoose whether to Show Points or Hide Points. |
A Convex Hull Plot is based on a Scatter Plot and adds shapes that outline all points of each color, allowing you to visualize groups of data on a single plot and identify regions of overlap or separation. |
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Create a Convex Hull Plot
Plot SettingsThe Convex Hull Plot has additional settings that can be changed. To do so:
View PointsChoose whether to Show Points or Hide Points. |
An Ellipsoid is based on a Scatter Plot and adds confidence intervals displayed as 2D or 3D ellipsoids. This is one way of visualizing the most common distributions in your data with respect to your features of interest. |
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Create an Ellipsoid Plot
Plot SettingsThe Ellipsoid Plot has additional settings that can be changed. To do so:
View PointsChoose whether to Show Points or Hide Points. ConfidenceThe default confidence interval is 95%. Here, you can adjust the confidence level (a higher confidence will result in a larger ellipsoid, while a lower confidence will result in a smaller ellipsoid). |
A Violin Plot, based on a Scatter Plot, spreads out overlapping points so that you can better see areas of high concentrations of points. They are useful in visualizing distributions of Scatter Plot data. |
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Create a Violin Plot
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Other Plots
A Histogram is a very common plot type used to group rows in your data into different bins. Grouping your data into different bins can help you identify patterns, especially which combinations of factors commonly occur together. Histograms can be used in either 1D, 2D, or 3D. |
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Create a Histogram
Plot SettingsThe Histogram has additional settings that can be changed. To do so:
Number of BinsChoose the number of bins that should be included for each dimension. Height/Volume ByBy default, the height (or volume in 3D) of each bin corresponds to the number of rows in that bin. If you place a feature on the Size dimension, you can choose to set the height (or volume) to correspond to the Count, Average, or Sum of the features on the Size dimension (you can also set to Uniform). This can add even more context to your plot (also called a Bar Plot). Access this by clicking the Menu icon ( ) in the Plot Settings panel. Clicking Auto Plot Setting Change will enable automatic plot updates based on changes made in the Plot Settings window so there isn't a need to click the Apply button after each change. |
A Line Plot allows you to track how certain metrics change with respect to another feature, with your data points connected by straight lines. Line Plots are commonly used to create time series plots, helping you to view changes in your data over time. |
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Create a Line Plot
Plot SettingsThe Line Plot has a number of settings that can be changed. To do so:
View PointsChoose to Show All, Hide Points, Hide Lines, or Hide Points and Lines. View ByIf you've added a feature to either Color or Group By, here you can choose how to primarily visualize the plot. |
A Surface Plot creates a continuous surface from your data in either 2D or 3D to view how one feature is affected by two others. Note: To be able to create a Surface plot, your dataset should be structured so that you have one feature which represents a function of two other features, or Y = f(X, Z).To ensure this requirement, check that the total number of points in your dataset equals the number of unique values in X multiplied by the number of unique values in Z. The Group By dimension can also be used if there are multiple surfaces described in the data. In this case, each category in the feature mapped to Group By must individually satisfy the above criteria. |
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Create a Surface Plot
Plot SettingsThe Surface Plot has additional settings that can be changed. To do so:
View PointsChoose to Show Points or Hide Points. |