A list of complex values is plotted as a list of pairs:

Plot multiple sets of regular data:

Non-numeric and missing data is excluded:

Use MaxPlotPoints to limit the number of points used:

PlotRange is selected automatically:

Use PlotRange to focus on areas of interest:

Use ScalingFunctions to scale the axes:

Get tabular data of the results of running Newton's method to solve with random starting seeds:

Plot all the points in the table:

Use PivotToColumns to generate columns for each basin of attraction:

Plot each number per region separately:

Specify strings to use as labels:

Specify a location for labels:

Numeric values in an Association are used as the coordinates:

Plot data in a SparseArray:

Use wrappers on individual data, datasets or collections of datasets:

Wrappers can be nested:

Use a specific label for all of the points:

Label points with automatically positioned text:

Use PopupWindow to click an eigenvalue to see a corresponding eigenvector:

Button can be used to trigger any action:

Label points with automatically positioned text:

Place the labels relative to the points:

Label data with Labeled:

Label data with PlotLabels:

Place the label near the points at a particular value:

Use a scaled position:

Specify the text position relative to the point:

Label data automatically with Callout:

Place a label with a specific location:

Specify label names with LabelingFunction:

For dense sets of points, some labels may be turned into tooltips by default:

Increasing the size of the plot will show more labels:

Include legends for each data_i:

Use Legended to provide a legend for a specific dataset:

Use Placed to change the legend location:

Use association keys as labels:

Plots usually have interactive callouts showing the coordinates when you mouse over them:

Multiple datasets are automatically colored to be distinct:

Provide explicit styling to different sets:

Use a plot theme:

Include legends for each dataset:

Use Legended to provide a legend for a specific dataset:

Provide an interactive Tooltip for the data:

Use shapes to distinguish different datasets:

Use labels to distinguish different datasets:

Use Joined to connect datasets with lines:

Use InterpolationOrder to smooth joined data:

By default, the ratio of the height to width for the plot is determined automatically:

Use numerical value to specify the height to width ratio:

Make the height the same as the width with AspectRatio1:

AspectRatioFull adjusts the height and width to tightly fit inside other constructs:

By default, ComplexListPlot draws axes:

Use AxesOrigin to specify where the axes intersect:

Turn each axis on individually:

No axes labels are drawn by default:

Place a label on the axis:

Specify axes labels:

The position of the axes is determined automatically:

Specify an explicit origin for the axes:

Change the style for the axes:

Specify the style of each axis:

Use different styles for the ticks and the axes:

Use different styles for the labels and the axes:

ClippingStyle requires at least one dataset to be Joined:

Omit clipped regions of the plot:

Show clipped regions as red at the bottom and thick at the top:

Show clipped regions as red and thick:

Color by scaled , , and coordinates:

ColorFunction has higher priority than PlotStyle for coloring the curve:

Use Automatic in MeshShading to use ColorFunction:

ColorFunctionScaling requires at least one dataset to be Joined:

Color the curve based on the scaled value:

Color the curve based on the unscaled value:

Color by unscaled , , and coordinates:

Draw a frame around the plot:

Draw a frame on the left and right edges:

Draw a frame on the left and bottom edges:

Place a label along the bottom edge of the frame:

Place labels on the bottom and left edges:

Place labels on each of the edges in the frame:

Use a customized style for both labels and frame tick labels:

Specify a style for the frame:

Specify a style for each frame edge:

Frame ticks are placed automatically by default:

Use a frame with no ticks:

Use frame ticks on the bottom edge:

By default, the top and right edges have tick marks but no tick labels:

Use All to include tick labels on all edges:

Place tick marks at specific positions:

Draw frame tick marks at specified positions with specific labels:

Specify the lengths for tick marks as a fraction of the graphics size:

Use different sizes in the positive and negative directions for each tick mark:

Specify a style for each frame tick:

Construct a function that places frame ticks at the midpoint and extremes of the frame edge:

By default, frame ticks and frame tick labels use the same styles as the frame:

Specify an overall style for the ticks, including the labels:

Use different styles for the different frame edges:

Use named sizes such as Tiny, Small, Medium and Large:

Specify the width of the plot:

Specify the height of the plot:

Allow the width and height to be up to a certain size:

Specify the width and height for a graphic, padding with space if necessary:

Setting AspectRatioFull will fill the available space:

Use maximum sizes for the width and height:

Use ImageSizeFull to fill the available space in an object:

Specify the image size as a fraction of the available space:

The number of points that are labeled directly may depend on the image size:

Smaller graphics will have fewer labeled points:

Larger graphics will have more labeled points:

InterpolationOrder requires at least one dataset to be Joined:

By default, linear interpolation is used:

Use zero-order or piecewise-constant interpolation:

Interpolation order 0 to 3:

Join the points in a dataset:

Join the first dataset with a line, but use points for the second dataset:

Join the dataset with a line and show the original points:

A Rule can be used to label points if the lists of values and labels are the same length:

A list of rules and values can be used to label selected points:

Use LabelingFunctionNone to suppress the labels:

Put the labels above the points:

Put them in a Tooltip:

Label the points as ordered pairs:

Label the points with their indices:

Textual labels are shown at their actual sizes:

Specify a maximum size for textual labels:

Image labels are automatically resized:

Specify a maximum size for image labels:

Show image labels at their natural sizes:

Use MaxPlotPoints to limit the number of points used:

Mesh requires at least one dataset to be Joined:

The initial and final sampling meshes are typically the same:

Interpolated data may introduce points:

Use 20 mesh levels evenly spaced in the direction:

Use an explicit list of values for the mesh in the direction:

Use explicit styles at specific points:

MeshFunctions requires at least one dataset to be Joined:

Show 5 mesh levels in the direction (red) and 10 in the direction (blue):

Use a mesh evenly spaced in the , , and directions:

MeshShading requires at least one dataset to be Joined:

Alternate red and blue segments of equal width in the direction:

Use None to remove segments:

MeshShading can be used with PlotStyle:

MeshShading has higher priority than PlotStyle:

Use PlotStyle for some segments by setting MeshShading to Automatic:

MeshShading can be used with ColorFunction:

Plots have interactive coordinate callouts with the default setting PlotHighlightingAutomatic:

Use PlotHighlightingNone to disable the highlighting for the entire plot:

Use Highlighted[…,None] to disable highlighting for a single set:

Move the mouse over a set of points to highlight it using arbitrary graphics directives:

Move the mouse over the points to highlight them with balls and labels:

Move the mouse over the curve to highlight it with a label and droplines to the axes:

Use a component that shows the points on the plot closest to the position of the mouse cursor:

Specify the style for the points:

Use a component that shows the coordinates on the points closest to the mouse cursor:

Use Callout options to change the appearance of the label:

Combine components to create a custom effect:

Add an overall label to the plot:

Specify text to label sets of points:

Place the labels above the points:

Use callouts to identify the points:

Use the keys from an Association as labels:

Use None to not add a label:

Generate a legend using labels:

Generate a legend using placeholders:

Legends use the same styles as the plot:

Use Placed to specify the legend placement:

Place the legend inside the plot:

Use PlotLegends to change the appearance:

ComplexListPlot normally uses distinct colors to distinguish different sets of data:

Automatically use colors and shapes to distinguish sets of data:

Use shapes only:

Change the size of the default plot markers:

Use arbitrary text for plot markers:

Use explicit graphics for plot markers:

Use the same symbol for all the sets of data:

Explicitly use a symbol and size: