Polar Scatter Plot
Polar scatter plots are a data visualization method that represents data points on a polar coordinate system. They display individual data points as dots or markers in a circular plot, providing a means to visualize the distribution, relationships, or patterns in data with angular or directional dependencies. Polar scatter plots are particularly useful for exploring data within a circular context, where the angle or periodic nature of the data is a significant aspect.
Polar scatter plots are appropriate when the data contain a continuous variable represented in polar coordinates, with a radial and an angular component instead of the typical x and y components.
What are polar scatter plots useful for?
- Analyzing cyclical data: Polar scatter plots are valuable for analyzing data with cyclical or periodic patterns, as they enable the visualization of cyclic trends and periodic variations within the data.
- Representing directional data: They are used to represent directional data, such as wind directions, compass bearings, or angular measurements, providing a visual means to explore data with specific orientations.
- Angular or Periodic Data Relationships: Polar scatter plots aid in exploring relationships and correlations in data with angular or periodic dependencies, making them suitable for applications where understanding circular patterns is essential.
Examples
A basic polar scatter plot
Visualize a dataset in polar coordinates by passing column names to the r
and theta
arguments. theta
may be a string of cardinal directions, as in this case. theta
also supports the use of numeric types that may represent radians or degrees, depending on how the range_theta
argument is supplied.
import deephaven.plot.express as dx
wind = dx.data.wind()
# `by` is used to separate data by groups
polar_scatter_plot = dx.scatter_polar(wind, r="Frequency", theta="Direction", by="Strength")
API Reference
Returns a polar scatter chart
Returns: DeephavenFigure
A DeephavenFigure that contains the polar scatter chart
Parameters | Type | Default | Description |
---|---|---|---|
table | PartitionedTable | Table | DataFrame | A table to pull data from. | |
r | str | None | None | A column that contains r values. |
theta | str | None | None | A column that contains theta 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. |
direction | str | 'clockwise' | Which direction points are drawn. Can be 'clockwise' or 'counterclockwise' |
start_angle | int | 90 | Sets start angle. |
range_r | list[int] | None | None | A list of two numbers that specify the range of r. |
range_theta | list[int] | None | None | A list of two numbers that specify the range of theta. |
log_r | bool | False | A boolean that specifies if the corresponding axis is a log axis or not. |
title | str | None | None | The title of the chart |
template | str | None | None | The template for the chart. |
render_mode | str | 'webgl' | Either "svg" or "webgl". The default is "webgl" as it leads to a more performant plot but there may be graphical bugs, in which case it is recommended to switch to "svg" |
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. |