Ternary Scatter Plot
Ternary scatter plots are a data visualization method used to represent data within a triangular coordinate system. They display individual data points as markers or dots in the triangular space, offering a means to visualize the distribution, relationships, or patterns in data that consist of three mutually exclusive components. Ternary scatter plots are particularly useful when analyzing compositional data or data involving proportions that sum to a constant total.
Ternary scatter plots are appropriate when the data contain three interrelated mutually exclusive categories whose relationships can be quantified with a continuous variable.
What are ternary scatter plots useful for?
- Compositional data analysis: Ternary scatter plots are useful for analyzing data where proportions of three components add up to a constant total. They help visualize the distribution of these components and their relationships within the composition.
- Exploring multivariate data: They can be applied in multivariate data analysis to visualize relationships, patterns, and trends among three variables or components, particularly when these components are interrelated.
- Optimization studies: Ternary scatter plots aid in optimization studies to understand how adjustments in the proportions of three components impact the overall composition, making them valuable in informed decision-making processes.
Examples
A basic ternary scatter plot
Visualize a ternary dataset by passing column names to each of the a, b, and c arguments.
import deephaven.plot.express as dx
election = dx.data.election()
# create a ternary scatter plot by specifying the columns for the three points of the triangle
ternary_scatter_plot = dx.scatter_ternary(election, a="Joly", b="Coderre", c="Bergeron")
API Reference
Returns a ternary scatter chart
Returns: DeephavenFigure A DeephavenFigure that contains the ternary scatter chart
| Parameters | Type | Default | Description |
|---|---|---|---|
| table | PartitionedTable | Table | DataFrame | A table to pull data from. | |
| a | str | None | None | A column that contains a-axis values. |
| b | str | None | None | A column that contains b-axis values. |
| c | str | None | None | A column that contains c-axis values. |
| by | str | list[str] | None | None | A column or list of columns that contain values to plot the figure traces by. All values or combination of values map to a unique design. The variable by_vars specifies which design elements are used. This is overriden if any specialized design variables such as color are specified |
| by_vars | str | list[str] | 'color' | A string or list of string that contain design elements to plot by. Can contain size, line_dash, width, color, and symbol. If associated maps or sequences are specified, they are used to map by column values to designs. Otherwise, default values are used. |
| color | str | list[str] | None | None | A column or list of columns that contain color values. If only one column is passed, and it contains numeric values, the value is used as a value on a continuous color scale. Otherwise, the value is used for a plot by on color. See color_discrete_map for additional behaviors. |
| symbol | str | list[str] | None | None | A column or list of columns that contain symbol values. The value is used for a plot by on symbol. See color_discrete_map for additional behaviors. |
| size | str | None | None | A column or list of columns that contain size values. If only one column is passed, and it contains numeric values, the value is used as a size. Otherwise, the value is used for a plot by on size. See size_map for additional behaviors. |
| text | str | None | None | A column that contains text annotations. |
| hover_name | str | None | None | A column that contains names to bold in the hover tooltip. |
| labels | dict[str, str] | None | None | A dictionary of labels mapping columns to new labels. |
| color_discrete_sequence | list[str] | None | None | A list of colors to sequentially apply to the series. The colors loop, so if there are more series than colors, colors will be reused. |
| color_discrete_map | str | tuple[str, dict[str | tuple[str], dict[str | tuple[str], str]]] | dict[str | tuple[str], str] | None | None | If dict, the keys should be strings of the column values (or a tuple of combinations of column values) which map to colors. If "identity", the values are taken as literal colors. If "by" or ("by", dict) where dict is as described above, the colors are forced to by |
| symbol_sequence | list[str] | None | None | A list of symbols to sequentially apply to the markers in the series. The symbols loop, so if there are more series than symbols, symbols will be reused. |
| symbol_map | str | tuple[str, dict[str | tuple[str], dict[str | tuple[str], str]]] | dict[str | tuple[str], str] | None | None | If dict, the keys should be strings of the column values (or a tuple of combinations of column values) which map to symbols. If "identity", the values are taken as literal symbols. If "by" or ("by", dict) where dict is as described above, the symbols are forced to by |
| size_sequence | list[int] | None | None | A list of sizes to sequentially apply to the markers in the series. The sizes loop, so if there are more series than symbols, sizes will be reused. This is overriden is "size" is specified. |
| size_map | str | tuple[str, dict[str | tuple[str], dict[str | tuple[str], str]]] | dict[str | tuple[str], str] | None | None | If dict, the keys should be strings of the column values (or a tuple of combinations of column values) which map to sizes. If "identity", the values are taken as literal sizes. If "by" or ("by", dict) where dict is as described above, the sizes are forced to by |
| color_continuous_scale | list[str] | None | None | A list of colors for a continuous scale |
| range_color | list[float] | None | None | A list of two numbers that form the endpoints of the color axis |
| color_continuous_midpoint | float | None | None | A number that is the midpoint of the color axis |
| opacity | float | None | None | Opacity to apply to all markers. 0 is completely transparent and 1 is completely opaque. |
| title | str | None | None | The title of the chart |
| template | str | None | None | The template for the chart. |
| unsafe_update_figure | Callable | <function default_callback> | An update function that takes a plotly figure as an argument and optionally returns a plotly figure. If a figure is not returned, the plotly figure passed will be assumed to be the return value. Used to add any custom changes to the underlying plotly figure. Note that the existing data traces should not be removed. This may lead to unexpected behavior if traces are modified in a way that break data mappings. |