x, y : scalar or array-like
xerr, yerr : scalar 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.
See Different ways of specifying error bars
for an example on the usage of xerr and yerr.
fmt : plot format string, optional, default: ''
The format for the data points / data lines. See plot for
details.
Use 'none' (case insensitive) to plot errorbars without any data
markers.
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, the linewidth of
the current style is used.
capsize : scalar, optional, default: None
The length of the error bar caps in points. If None, it will take
the value from rcParams["errorbar.capsize"].
capthick : scalar, optional, 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, 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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