plots points {1,y1},{2,y2},.


plots a list of points with specified x and y coordinates.


plots data from all the datai.


plots datai with features defined by the symbolic wrapper w.

Details and Options

  • ListPlot is also known as a point plot when given a list of heights yi and as a scatter plot when given pairs of coordinates {xi,yi}.
  • When given a list of heights, ListPlot plots the points in the order they were given, showing the trend of the data.
  • With a set of pairs, the points are placed at the given coordinates. Since the location is entirely determined by the data, it does not need to be in any particular order.
  • Data values xi and yi can be given in the following forms:
  • xia real-valued number
    Quantity[xi,unit]a quantity with a unit
    Around[xi,ei]value xi with uncertainty ei
    Interval[{xmin,xmax}]values between xmin and xmax
  • Values xi and yi that are not of the form above are taken to be missing and are not shown.
  • The datai have the following forms and interpretations:
  • <|"k1"y1,"k2"y2,|>values {y1,y2,}
    <|x1y1,x2y2,|>key-value pairs {{x1,y1},{x2,y2},}
    {y1"lbl1",y2"lbl2",}, {y1,y2,}{"lbl1","lbl2",}values {y1,y2,} with labels {lbl1,lbl2,}
    SparseArrayvalues as a normal array
    TimeSeries, EventSeriestime-value pairs
    WeightedDataunweighted values
  • The following wrappers w can be used for the datai:
  • Annotation[datai,label]provide an annotation for the data
    Button[datai,action]define an action to execute when the data is clicked
    Callout[datai,label]label the data with a callout
    Callout[datai,label,pos]place the callout at relative position pos
    EventHandler[datai,]define a general event handler for the data
    Hyperlink[datai,uri]make the data a hyperlink
    Labeled[datai,label]label the data
    Labeled[datai,label,pos]place the label at relative position pos
    Legended[datai,label]identify the data in a legend
    PopupWindow[datai,cont]attach a popup window to the data
    StatusArea[datai,label]display in the status area on mouseover
    Style[datai,styles]show the data using the specified styles
    Tooltip[datai,label]attach a tooltip to the data
    Tooltip[datai]use data values as tooltips
  • Wrappers w can be applied at multiple levels:
  • {,w[yi],}wrap the value yi in data
    {,w[{xi,yi}],}wrap the point {xi,yi}
    w[datai]wrap the data
    w[{data1,}]wrap a collection of datai
    w1[w2[]]use nested wrappers
  • Callout, Labeled, and Placed can use the following positions pos:
  • Automaticautomatically placed labels
    Abovepositions above data or point
    Belowpositions below data or point
    Beforepositions before data or point
    Afterpositions after data or point
    {pos,epos}epos in label placed at relative position pos of the data
  • ListPlot has the same options as Graphics, with the following additions and changes:
  • AspectRatio1/GoldenRatioratio of height to width
    AxesTruewhether to draw axes
    DataRangeAutomaticthe range of x values to assume for data
    IntervalMarkersAutomatichow to render uncertainty
    IntervalMarkersStyleAutomaticstyle for uncertainty elements
    FillingNonehow to fill in stems for each point
    FillingStyleAutomaticstyle to use for filling
    JoinedFalsewhether to join points
    LabelingFunctionAutomatichow to label points
    LabelingSizeAutomaticmaximum size of callouts and labels
    PerformanceGoal$PerformanceGoalaspects of performance to try to optimize
    PlotLabelNoneoverall label for the plot
    PlotLabelsNonelabels for data
    PlotLayout"Overlaid"how to position data
    PlotLegendsNonelegends for data
    PlotMarkersNonemarkers to use to indicate each point
    PlotRangeAutomaticrange of values to include
    PlotRangeClippingTruewhether to clip at the plot range
    PlotStyleAutomaticgraphics directives to determine styles of points
    PlotTheme$PlotThemeoverall theme for the plot
    ScalingFunctionsNonehow to scale individual coordinates
    TargetUnitsAutomaticunits to display in the plot
  • DataRange determines how values {y1,,yn} are interpreted into {{x1,y1},,{xn,yn}}. Possible settings include:
  • Automatic,Alluniform from 1 to n
    {xmin,xmax}uniform from xmin to xmax
  • In general a list of pairs {{x1,y1},{x2,y2},} is interpreted as a list of points, but the setting DataRangeAll forces it to be interpreted as multiple datai {{y11,y12},{y21,y23},}. »
  • LabelingFunction->f specifies that each point should have a label given by f[value,index,lbls], where value is the value associated with the point, index is its position in the data, and lbls is the list of relevant labels.
  • The following settings for PlotLayout can be used to display multiple sets of data:
  • "Overlaid"show all the data overlapping
    "Stacked"accumulate the data per axis
    "Percentile"accumulate and normalize the data per axis
    "Column"use separate plots in a column
    "Row"use separate plots in a row
    {"Column",n},{"Row",n}use n columns or rows
    {"Column",UpTo[n]},{"Row",UpTo[n]}use at most n columns or rows
  • Typical settings for PlotLegends include:
  • Noneno legend
    Automaticautomatically determine legend
    {lbl1,lbl2,}use lbl1, lbl2, as legend labels
    Placed[lspec,]specify placement for legend
  • ScalingFunctions->"scale" scales the coordinate; ScalingFunctions{"scalex","scaley"} scales both the and coordinates.


open allclose all

Basic Examples  (7)

Plot a list of values:

Plot a list of , pairs:

Plot several datai with a legend:

Label each point:

Label each datai:

Plot values including units:

Use individual colors for each point:

Scope  (52)

General Data  (11)

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:

Include units with the 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 nonreal 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 scale the axes:

Special Data  (9)

Use Quantity to include units with the data:

Include different units for the x and y 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:

Data Wrappers  (6)

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:

Labeling and Legending  (13)

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 x 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:

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:

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:

Presentation  (13)

Multiple datasets are automatically colored to be distinct:

Provide explicit styling to different sets:

Use a plot theme:

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:

Plot the data in a stacked layout:

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

Options  (121)

AspectRatio  (2)

Choose the ratio of height to width from the actual plot values:

Set the ratio to 1:

AxesLabel  (1)

Specify labels for the and axes:

AxesOrigin  (1)

The locations of the axes are determined automatically:

Specify where the axes cross:

ClippingStyle  (6)

ClippingStyle requires at least one dataset to be Joined:

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  (5)

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  (3)

ColorFunctionScaling requires at least one dataset to be Joined:

Color the line based on the scaled value:

Color the line based on the unscaled value:

DataRange  (5)

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:

Filling  (8)

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 will use the first as the reference:

Joined datasets fill with solid areas:

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

FillingStyle  (4)

Fill with blue "stems":

Fill with dashed magenta "stems":

Fill with red below the axis, and with blue above:

Filling is solid when Joined->True:

ImageSize  (1)

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  (5)

Joined lines 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:

IntervalMarkers  (3)

By default, uncertainties are capped:

Use bars to denote uncertainties without caps:

Use bands to represent uncertainties:

IntervalMarkersStyle  (2)

Uncertainties automatically inherit the plot style:

Specify the style for uncertainties:

Joined  (4)

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:

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

LabelingFunction  (6)

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:

LabelingSize  (4)

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:

MaxPlotPoints  (1)

Mesh  (6)

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  (3)

MeshFunctions requires at least one dataset to be Joined:

Use a mesh evenly spaced in the and directions:

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

MeshShading  (7)

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 for styling the curve:

Use PlotStyle for some segments by setting MeshShading to Automatic:

MeshShading can be used with ColorFunction:

PlotLabel  (1)

Add an overall label to the plot:

PlotLabels  (5)

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:

PlotLayout  (1)

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:

Place each curve in a separate panel using shared axes:

Use rows instead of columns:

PlotLegends  (7)

No legend is used, by default:

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 PointLegend to change the legend appearance:

PlotMarkers  (8)

ListPlot 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  (2)

PlotRange is automatically calculated:

Show the whole dataset:

PlotStyle  (7)

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:

PlotStyle can be combined with ColorFunction:

PlotStyle can be combined with MeshShading:

MeshStyle by default uses the same style as PlotStyle:

PlotTheme  (2)

Use a theme with simple ticks and grid lines in a bright color scheme:

Change the color scheme:

ScalingFunctions  (9)

By default, plots have linear scales in each direction:

Use a log scale in the direction:

Use a linear scale in the direction that shows smaller numbers at the top:

Use a reciprocal scale in the direction:

Use different scales in the and directions:

Reverse the axis without changing the axis:

Use a scale defined by a function and its inverse:

Positions in Ticks and GridLines are automatically scaled:

PlotRange and AxesOrigin are automatically scaled:

TargetUnits  (2)

Automatically detect units:

Specify alternate units:

Applications  (9)

Compare the n^(th) prime to an estimate:

Show the evaluation points in the order used by a numerical function:

Show both evaluation points and value used by a numerical function:

Plot life expectancy against birth rates for all the countries:

Show the linear relationship between enthalpy of vaporization and boiling point:

Plot a discrete-time signal and its spectrum:

Plot the probability mass function for a distribution:

Plot the empirical probability mass function:

Plot a solution sequence to a difference equation:

Plot randomly sampled properties:

Plot uncertainties in the mass and radius of exoplanets:

Properties & Relations  (13)

By default pairs are interpreted as values:

Interpret the data as multiple datai:

ListLinePlot is a special case of ListPlot:

Use Plot for functions:

Use ListLogPlot, ListLogLogPlot, and ListLogLinearPlot for logarithmic plots:

Use ListPolarPlot for polar plots:

Use DateListPlot to show data over time:

Use ComplexListPlot to plot complex numbers using their real and imaginary parts:

Use ListPointPlot3D to show three-dimensional points:

Use ListPlot3D to create surfaces from data:

Use ListContourPlot to create contours from continuous data:

Use ListDensityPlot to create densities from continuous data:

Use ArrayPlot and MatrixPlot for arrays of discrete values:

Use ParametricPlot for parametric curves:

Wolfram Research (1988), ListPlot, Wolfram Language function, (updated 2019).


Wolfram Research (1988), ListPlot, Wolfram Language function, (updated 2019).


@misc{reference.wolfram_2020_listplot, author="Wolfram Research", title="{ListPlot}", year="2019", howpublished="\url{}", note=[Accessed: 21-January-2021 ]}


@online{reference.wolfram_2020_listplot, organization={Wolfram Research}, title={ListPlot}, year={2019}, url={}, note=[Accessed: 21-January-2021 ]}


Wolfram Language. 1988. "ListPlot." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2019.


Wolfram Language. (1988). ListPlot. Wolfram Language & System Documentation Center. Retrieved from