For regular data consisting of values, the data range is taken to be integer values:

Provide an explicit data range by using DataRange:

Plot multiple sets of regular data:

For irregular data consisting of , value pairs, the data range is inferred from data:

Plot multiple sets of irregular data:

Plot multiple sets of data, regular or irregular, using DataRange to map them to the same range:

Ranges where the data is nonpositive are 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 reverse the plot on the y axis:

Use a Log scale for the x axis:

Get tabular data:

Plot reported losses on a log scale against the years:

Plot adjusted losses and reported losses separately:

Plot all the data in TimeSeries or EventSeries:

Plot a specific component of a TimeSeries or EventSeries:

Plot multiple components:

Use Quantity to include units with the data:

Include different units for the and coordinates:

Plot data in a QuantityArray:

Specify the units used with TargetUnits:

Plot data with uncertainty:

Use intervals:

Specify strings to use as labels:

Specify a location for labels:

Numeric values in an Association are used as the coordinates:

Numeric keys and values in an Association are used as the and coordinates:

Plot TimeSeries directly:

Plot data in a SparseArray:

The weights in WeightedData are ignored:

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

Wrappers can be nested:

Use the value of each point as a tooltip:

Use a specific label for all the points:

Labels points with automatically positioned text:

Use PopupWindow to provide additional drilldown information:

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 an value:

Use a scaled position:

Specify the text position relative to the point:

Specify the maximum size of labels:

Use the full label:

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

Increasing the size of the plot will show more labels:

Label data automatically with Callout:

Place a label with a specific location:

Specify label names with LabelingFunction:

Include legends for each curve:

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:

Including specific wrappers or interactions, such as tooltips, turns off the interactive features:

Choose from multiple interactive highlighting effects:

Use Highlighted to emphasize specific points in a plot:

Highlight multiple points:

Multiple datasets are automatically colored to be distinct:

Provide explicit styling to different sets:

Include legends for each curve:

Use Legended to provide a legend for a specific dataset:

Add labels:

Provide an interactive Tooltip for the data:

Create filled plots:

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:

Use a theme with detailed frame ticks and grid lines:

Use a theme with a dark background and vibrant colors:

Plot the data in a stacked layout:

Plot the data as percentiles of the total of the values:

ClippingStyle only applies to Joined datasets:

Omit clipped regions of the plot:

Show clipped regions like the rest of the curve:

Show clipped regions with red lines:

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

Show clipped regions as red and thick:

ColorFunction only applies to Joined datasets:

Color by scaled and coordinates:

Color with a named color scheme:

Fill with the color used for the curve:

ColorFunction has higher priority than PlotStyle for coloring the curve:

Use Automatic in MeshShading to use ColorFunction:

ColorFunctionScaling only applies to Joined datasets:

Use no argument scaling on the left and automatic scaling on the right:

Scaling is done on a linear scale in the original coordinates:

Use a color function that is red at powers of 10:

Lists of height values are displayed against the number of elements:

Rescale to the sampling space:

Each dataset is scaled to the same domain:

Pairs are interpreted as , coordinates:

Specifying DataRange in this case has no effect, since values are part of the data:

Force interpretation as multiple datasets:

Use symbolic or explicit values for "stem" filling:

Fill between corresponding points in two datasets:

Fill between datasets using a particular style:

Fill between datasets 1 and 2; use red when 1 is less than 2 and blue otherwise:

Fill to the axis for irregularly sampled data:

Use several irregular datasets, filling between them:

Joined datasets fill with solid areas:

The type of filling depends on whether the first set is joined:

Fill with blue "stems":

Fill with dashed magenta "stems":

Fill with red below , and blue above:

Filling is solid when Joined->True:

Lines created with Joined can be interpolated:

By default, linear interpolation is used:

Use zero-order or piecewise-constant interpolation:

Use third-order spline interpolation:

Interpolation order 0 to 5:

By default, uncertainties are capped:

Use bars to denote uncertainties without caps:

Use bands to represent uncertainties:

Uncertainties automatically inherit the plot style:

Specify the style for uncertainties:

Join the dataset with a line:

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:

TimeSeries is shown as continuous lines:

EventSeries is shown as discrete points:

The type of filling depends on whether the set is joined:

By default, points are automatically labeled with strings:

Use LabelingFunction->None to suppress the labels:

Put the labels above the points:

Put them in a tooltip:

Use callouts to label the points:

Label the points with their values:

Label the points with their indices:

Textual labels are shown at their actual sizes:

Image labels are automatically resized:

Specify a maximum size for textual labels:

Specify a maximum size for image labels:

Show image labels at their natural sizes:

Labels are automatically placed to maximize readability:

Show all labels:

Use a denser layout for the labels:

Show the quarter of the labels that are easiest to read:

Only allow labels that are orthogonal to the points:

Only allow labels that are diagonal to the points:

Restrict labels to be above or to the right of the points:

Allow labels to obscure other points:

Allow labels to be clipped by the edges of the plot:

All points are included by default:

Uniformly spaced data is downsampled:

Nonuniform data is topologically subsampled to preserve features:

Mesh only applies to Joined datasets:

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 only applies to Joined datasets:

Use a mesh evenly spaced in the direction and unscaled in the direction:

Use a mesh logarithmically spaced in the direction:

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

MeshShading only applies to Joined datasets:

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 for styling the curve:

Use PlotStyle for some segments by setting MeshShading to Automatic:

MeshShading can be used with ColorFunction and has higher priority:

MeshStyle only applies to Joined datasets:

Color the mesh the same color as the plot:

Use a red mesh in the direction:

Use a red mesh in the direction and a blue mesh in the direction:

Use big red mesh points in the direction:

Automatically fit a model to the data:

Fit a straight line to the data:

Fit a quadratic curve to the data:

Use LogModel to approximate the data:

By default, the fitted model is shown with the data points:

Plot confidence bands for the data, with a default confidence level of 0.95:

Use a confidence level of 0.5 for the bands:

Show residual lines from the data points to the fitted curve:

Combine the original points with red residual lines:

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 ball and label to highlight a specific point in the plot:

Move the mouse over the plot to highlight it with a slice showing values corresponding to the position:

Highlight a particular set of points at a fixed value:

Move the mouse over the plot to highlight it with a slice showing values corresponding to the position:

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:

Plots have interactive highlighting by default:

Turn off all the interactive elements:

Allow provided interactive elements and disable automatic ones:

Add an overall label to the plot:

Specify text to label sets of points:

Use an Association form to specify labels:

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:

By default, curves are overlaid on each other:

Plot the data in a stacked layout:

Plot the data as percentiles of the total of the values:

Use rows instead of columns:

Generate a legend using labels:

Use an Association form to specify legends:

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 PointLegend to change the legend appearance:

ListLogPlot 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:

PlotRange is automatically calculated:

Show the whole dataset:

Use different style directives:

By default, different styles are chosen for multiple datasets:

Explicitly specify the style for different datasets:

PlotStyle applies to both lines and points:

Use the association-based syntax to set a base style for all data:

Use a different style for each of the datasets:

Provide an overall base style as well as styles for each dataset:

PlotStyle can be combined with ColorFunction and has lower priority:

PlotStyle can be combined with MeshShading and has lower priority:

MeshStyle by default uses the same style as PlotStyle:

Use a theme with simple ticks and plot markers in a bright color scheme:

Change the plot markers:

By default, the y axis has a log scale:

Reverse the direction of the y scale:

Reverse both sets of axes: