x : scalar or array-like
y : scalar or array-like
xerr/yerr : scalar or array-like, shape(N,) or shape(2,N), optional
If a scalar number, len(N) array-like object, or a N-element
array-like object, errorbars are drawn at +/-value relative
to the data. Default is None.
If a sequence of shape 2xN, errorbars are drawn at -row1
and +row2 relative to the data.
fmt : plot format string, optional, default: None
The plot format symbol. If fmt is ‘none’ (case-insensitive),
only the errorbars are plotted. This is used for adding
errorbars to a bar plot, for example. Default is ‘’,
an empty plot format string; properties are
then identical to the defaults for plot() .
ecolor : mpl color, optional, default: None
A matplotlib color arg which gives the color the errorbar lines;
if None, use the color of the line connecting the markers.
elinewidth : scalar, optional, default: None
The linewidth of the errorbar lines. If None, use the linewidth.
capsize : scalar, optional, default: None
The length of the error bar caps in points; if None, it will
take the value from errorbar.capsize
rcParam .
capthick : scalar, optional, default: None
An alias kwarg to 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, optional, default: False
if True , will plot the errorbars above the plot
symbols. Default is below.
lolims / uplims / xlolims / xuplims : bool, optional, default:None
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 of the same
type as xerr and yerr. To use limits with inverted
axes, set_xlim() or set_ylim() must be called
before errorbar() .
errorevery : positive integer, optional, default:1
subsamples the errorbars. e.g., if errorevery=5, errorbars for
every 5-th datapoint will be plotted. The data plot itself still
shows all data points.
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