matplotlib 3.5.1

Other ParametersParametersReturnsBackRef
errorbar(self, x, y, yerr=None, xerr=None, fmt='', ecolor=None, elinewidth=None, capsize=None, barsabove=False, lolims=False, uplims=False, xlolims=False, xuplims=False, errorevery=1, capthick=None, *, data=None, **kwargs)

x, y define the data locations, xerr, yerr define the errorbar sizes. By default, this draws the data markers/lines as well the errorbars. Use fmt='none' to draw errorbars without any data markers.

Other Parameters

data : indexable object, optional

If given, the following parameters also accept a string s , which is interpreted as data[s] (unless this raises an exception):

x, y, xerr, yerr

**kwargs :

All other keyword arguments are passed on to the ~.Axes.plot call drawing the markers. For example, this code makes big red squares with thick green edges:

x, y, yerr = rand(3, 10)
errorbar(x, y, yerr, marker='s', mfc='red',
         mec='green', ms=20, mew=4)

where mfc, mec, ms and mew are aliases for the longer property names, markerfacecolor, markeredgecolor, markersize and markeredgewidth.

Valid kwargs for the marker properties are .Line2D properties:

Properties: agg_filter: a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array alpha: scalar or None animated: bool antialiased or aa: bool clip_box: .Bbox clip_on: bool clip_path: Patch or (Path, Transform) or None color or c: color dash_capstyle: .CapStyle or {'butt', 'projecting', 'round'} dash_joinstyle: .JoinStyle or {'miter', 'round', 'bevel'} dashes: sequence of floats (on/off ink in points) or (None, None) data: (2, N) array or two 1D arrays drawstyle or ds: {'default', 'steps', 'steps-pre', 'steps-mid', 'steps-post'}, default: 'default' figure: .Figure fillstyle: {'full', 'left', 'right', 'bottom', 'top', 'none'} gid: str in_layout: bool label: object linestyle or ls: {'-', '--', '-.', ':', '', (offset, on-off-seq), ...} linewidth or lw: float marker: marker style string, ~.path.Path or ~.markers.MarkerStyle markeredgecolor or mec: color markeredgewidth or mew: float markerfacecolor or mfc: color markerfacecoloralt or mfcalt: color markersize or ms: float markevery: None or int or (int, int) or slice or list[int] or float or (float, float) or list[bool] path_effects: .AbstractPathEffect picker: float or callable[[Artist, Event], tuple[bool, dict]] pickradius: float rasterized: bool sketch_params: (scale: float, length: float, randomness: float) snap: bool or None solid_capstyle: .CapStyle or {'butt', 'projecting', 'round'} solid_joinstyle: .JoinStyle or {'miter', 'round', 'bevel'} transform: unknown url: str visible: bool xdata: 1D array ydata: 1D array zorder: float

Parameters

x, y : float or array-like

The data positions.

xerr, yerr : float or array-like, shape(N,) or shape(2, N), optional

The errorbar sizes:

  • scalar: Symmetric +/- values for all data points.

  • shape(N,): Symmetric +/-values for each data point.

  • shape(2, N): Separate - and + values for each bar. First row contains the lower errors, the second row contains the upper errors.

  • None: No errorbar.

Note that all error arrays should have positive values.

See /gallery/statistics/errorbar_features for an example on the usage of xerr and yerr .

fmt : str, default: ''

The format for the data points / data lines. See :None:None:`.plot` for details.

Use 'none' (case insensitive) to plot errorbars without any data markers.

ecolor : color, default: None

The color of the errorbar lines. If None, use the color of the line connecting the markers.

elinewidth : float, default: None

The linewidth of the errorbar lines. If None, the linewidth of the current style is used.

capsize : float, default: :rc:`errorbar.capsize`

The length of the error bar caps in points.

capthick : float, default: None

An alias to the keyword argument markeredgewidth (a.k.a. mew). This setting is a more sensible name for the property that controls the thickness of the error bar cap in points. For backwards compatibility, if mew or markeredgewidth are given, then they will over-ride capthick. This may change in future releases.

barsabove : bool, default: False

If True, will plot the errorbars above the plot symbols. Default is below.

lolims, uplims, xlolims, xuplims : bool, default: False

These arguments can be used to indicate that a value gives only upper/lower limits. In that case a caret symbol is used to indicate this. lims-arguments may be scalars, or array-likes of the same length as xerr and yerr. To use limits with inverted axes, :None:None:`~.Axes.set_xlim` or :None:None:`~.Axes.set_ylim` must be called before errorbar . Note the tricky parameter names: setting e.g. lolims to True means that the y-value is a lower limit of the True value, so, only an upward-pointing arrow will be drawn!

errorevery : int or (int, int), default: 1

draws error bars on a subset of the data. errorevery =N draws error bars on the points (x[::N], y[::N]). errorevery =(start, N) draws error bars on the points (x[start::N], y[start::N]). e.g. errorevery=(6, 3) adds error bars to the data at (x[6], x[9], x[12], x[15], ...). Used to avoid overlapping error bars when two series share x-axis values.

Returns

`.ErrorbarContainer`

The container contains:

  • plotline: .Line2D instance of x, y plot markers and/or line.

  • caplines: A tuple of .Line2D instances of the error bar caps.

  • barlinecols: A tuple of .LineCollection with the horizontal and vertical error ranges.

Plot y versus x as lines and/or markers with attached errorbars.

Examples

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

matplotlib.pyplot.barh matplotlib.pyplot.bar matplotlib.container.ErrorbarContainer matplotlib.axes._axes.Axes.barh matplotlib.axes._axes.Axes.bar matplotlib.markers

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


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