# ListLogPlot

ListLogPlot[{y1,y2,}]

makes a log plot of the yi, assumed to correspond to x coordinates 1, 2, .

ListLogPlot[{{x1,y1},{x2,y2},}]

makes a log plot of the specified list of x and y values.

ListLogPlot[{data1,data2,}]

plots data from all the datai.

ListLogPlot[{,w[datai,],}]

plots datai with features defined by the symbolic wrapper w.

# Details and Options

• ListLogPlot is also known as semi-logarithmic or semi-log plot since it has one logarithmic axis and one linear axis.
• ListLogPlot effectively plots points based on Log[yi], but with tick marks indicating the unscaled values yi
• ListLogPlot makes exponentials appear as straight lines.
• When given a list of heights, ListLogPlot 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:
•  xi a 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 preceding form are taken to be missing and are not shown.
• The datai have the following forms and interpretations:
•  <|"k1"y1,"k2"y2,…|> values {y1,y2,…} <|x1y1,x2y2,…|> key-value pairs {{x1,y1},{x2,y2},…} {y1"lbl1",y2"lbl2",…}, {y1,y2,…}{"lbl1","lbl2",…} values {y1,y2,…} with labels {lbl1,lbl2,…} SparseArray values as a normal array TimeSeries, EventSeries time-value pairs QuantityArray magnitudes WeightedData unweighted 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 allow the following positions:
•  Automatic automatically placed labels Above, Below, Before, After positions around the data x near the data at a position x Scaled[s] scaled position s along the data {s,Above},{s,Below},… relative position at position s along the data {pos,epos} epos in label placed at relative position pos of the data
• ListLogPlot has the same options as Graphics, with the following additions and changes:
•  AspectRatio 1/GoldenRatio ratio of height to width Axes True whether to draw axes DataRange Automatic the range of x values to assume for data IntervalMarkers Automatic how to render uncertainty IntervalMarkersStyle Automatic style for uncertainty elements Filling None how to fill in stems for each point FillingStyle Automatic style to use for filling Joined False whether to join points LabelingFunction Automatic how to label points LabelingSize Automatic maximum size of callouts and labels PerformanceGoal \$PerformanceGoal aspects of performance to try to optimize PlotLabel None overall label for the plot PlotLabels None labels for data PlotLayout "Overlaid" how to position data PlotLegends None legends for data PlotMarkers None markers to use to indicate each point PlotRange Automatic range of values to include PlotRangeClipping True whether to clip at the plot range PlotStyle Automatic graphics directives to determine styles of points PlotTheme \$PlotTheme overall theme for the plot ScalingFunctions None how to scale individual coordinates TargetUnits Automatic units to display in the plot
• DataRange determines how values {y1,,yn} are interpreted into {{x1,y1},,{xn,yn}}. Possible settings include:
•  Automatic,All uniform 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 forces it to be interpreted as multiple datai {{y11,y12},{y21,y23},}.
• 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.
• Possible settings for PlotLayout that show multiple curves in a single plot panel include:
•  "Overlaid" show all the data overlapping "Stacked" accumulate the data "Percentile" accumulate and normalize the data
• Possible settings for PlotLayout that show single curves in multiple plot panels include:
•  "Column" use separate curves in a column of panels "Row" use separate curves in a row of panels {"Column",k},{"Row",k} use k columns or rows {"Column",UpTo[k]},{"Row",UpTo[k]} use at most k columns or rows
• Typical settings for PlotLegends include:
•  None no legend Automatic automatically determine legend {lbl1,lbl2,…} use lbl1, lbl2, … as legend labels Placed[lspec,…] specify placement for legend
• Possible settings for ScalingFunctions include:
•  sy scale y axis {sx,sy} scale x and y axes
• Common built-in scaling functions s include:
•  "Reverse" reverse the coordinate direction "Infinite" infinite scale
• Scales for the y axis are applied after default log scale has been applied.

# Examples

open allclose all

## Basic Examples(5)

Plot a list of values with logarithmic scaling:

Join the points with a line:

Plot a list of , pairs using logarithmic scaling of :

Plot multiple sets of data with a legend:

Label each curve:

Generate filled plots:

## 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:

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:

### Special Data(9)

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:

### 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 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:

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:

### Presentation(13)

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:

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:

## Options(113)

### ClippingStyle(6)

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(6)

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(3)

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:

### 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:

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 , and blue above:

Filling is solid when :

### InterpolationOrder(5)

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:

### IntervalMarkers(3)

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:

### 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 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(3)

All points are included by default:

Uniformly spaced data is downsampled:

Nonuniform data is topologically subsampled to preserve features:

### Mesh(6)

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(3)

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(5)

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:

### 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:

### PlotLegends(6)

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)

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(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 and has lower priority:

PlotStyle can be combined with MeshShading and has lower priority:

MeshStyle by default uses the same style as PlotStyle:

### PlotTheme(1)

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

Change the plot markers:

### ScalingFunctions(2)

By default, the y axis has a log scale:

Reverse the direction of the y scale:

Reverse both sets of axes:

## Applications(2)

Generate a Collatz-like sequence:

Plot the spectrum of a sequence:

## Properties & Relations(11)

ListLogPlot is a special case of ListPlot:

Use LogPlot for functions:

Use ListLogLogPlot and ListLogLinearPlot for logarithmic plots in the direction:

Use ListPlot and ListLinePlot for unscaled plots:

Use ListPolarPlot for polar plots:

Use DateListPlot to show data over time:

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:

Wolfram Research (2007), ListLogPlot, Wolfram Language function, https://reference.wolfram.com/language/ref/ListLogPlot.html (updated 2022).

#### Text

Wolfram Research (2007), ListLogPlot, Wolfram Language function, https://reference.wolfram.com/language/ref/ListLogPlot.html (updated 2022).

#### CMS

Wolfram Language. 2007. "ListLogPlot." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2022. https://reference.wolfram.com/language/ref/ListLogPlot.html.

#### APA

Wolfram Language. (2007). ListLogPlot. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/ListLogPlot.html

#### BibTeX

@misc{reference.wolfram_2022_listlogplot, author="Wolfram Research", title="{ListLogPlot}", year="2022", howpublished="\url{https://reference.wolfram.com/language/ref/ListLogPlot.html}", note=[Accessed: 21-March-2023 ]}

#### BibLaTeX

@online{reference.wolfram_2022_listlogplot, organization={Wolfram Research}, title={ListLogPlot}, year={2022}, url={https://reference.wolfram.com/language/ref/ListLogPlot.html}, note=[Accessed: 21-March-2023 ]}