PlotAxes.bar¶
- PlotAxes.bar(*args, **kwargs)[source]¶
Plot individual, grouped, or stacked bars.
- Parameters
*args (
yorx,y) – The data passed as positional or keyword arguments. Interpreted as follows:If only
ycoordinates are passed, try to infer thexcoordinates from theSeriesorDataFrameindices or theDataArraycoordinates. Otherwise, thexcoordinates arenp.arange(0, y.shape[0]).If the
ycoordinates are a 2D array, plot each column of data in succession (except where each column of data represents a statistical distribution, as withboxplot,violinplot, or when usingmeans=Trueormedians=True).If any arguments are
pint.Quantity, auto-add the pint unit registry to matplotlib’s unit registry usingsetup_matplotlib. Apint.Quantityembedded in anxarray.DataArrayis also supported.
width (
floator array-like, optional) – The width(s) of the bars relative to the x coordinate step size. Can be passed as a third positional argument.bottom (
floator array-like, optional) – The coordinate(s) of the bottom edge of the bars. Default is0. Can be passed as a fourth positinal argument.absolute_width (
bool, optional) – Whether to make thewidthunits absolute. IfTrue, this restores the default matplotlib behavior. Default isFalse.stack, stacked (
bool, optional) – Whether to “stack” bars from successive columns of y data or plot bars side-by-side in groups. Default isFalse.data (dict-like, optional) – A dict-like dataset container (e.g.,
DataFrameorDataset). If passed, each data argument can optionally be a stringkeyand the arrays used for plotting are retrieved withdata[key]. This is a native matplotlib feature.autoformat (
bool, optional) – Whether thexaxis labels,yaxis labels, axis formatters, axes titles, legend titles, and colorbar labels are automatically configured when aSeries,DataFrame,DataArray, orQuantityis passed to the plotting command. Default isrc.autoformat=True. Formatting ofpint.Quantityunit strings is controlled byrc.unitformat='L'.
- Other Parameters
cycle (
cycle-spec, optional) – The cycle specifer, passed to theCycleconstructor. If the returned cycler is unchanged from the current cycler, the axes cycler will not be reset to its first position. To disable property cycling and just use black for the default color, usecycle=False,cycle='none', orcycle=()(analogous to disabling ticks with e.g.xformatter='none'). To restore the default property cycler, usecycle=True.lw, linewidth, linewidths (
unit-spec, optional) – The edge width of the patch(es). Default isrc['patch.linewidth']=0.6. If float, units are points. If string, interpreted byunits.ls, linestyle, linestyles (
str, optional) – The edge style of the patch(es). Default is'-'.ec, edgecolor, edgecolors (
color-spec, optional) – The edge color of the patch(es). Default is'none'.fc, facecolor, facecolors, fillcolor, fillcolors (
color-spec, optional) – The face color of the patch(es). Default is to use the propertycycle.a, alpha, alphas (
float, optional) – The opacity of the patch(es).negpos (
bool, optional) – Whether to shade bars whereheight >= 0withposcolorand whereheight < 0withnegcolor. Default isFalse. IfTruethis function will return a 2-tuple of values.negcolor, poscolor (
color-spec, optional) – Colors to use for the negative and positive bars. Ignored ifnegposisFalse. Defaults arerc.negcolor='blue7'andrc.poscolor='red7'.edgefix (
boolorfloat, optional) – Whether to fix the common issue where white lines appear between adjacent patches in saved vector graphics (this can slow down figure rendering). See this stackoverflow post for a demonstration of the problem. Default isrc.edgefix=True. IfTrue, a small default linewidth is used to cover up the white lines. If float (e.g.edgefix=0.5), this specific linewidth is used to cover up the white lines. This feature is automatically disabled when the patches have transparency.mean, means (
bool, optional) – Whether to plot the means of each column for 2Dycoordinates. Means are calculated withnumpy.nanmean. If no other arguments are specified, this also setsbarstd=True(andboxstd=Truefor violin plots).median, medians (
bool, optional) – Whether to plot the medians of each column for 2Dycoordinates. Medians are calculated withnumpy.nanmedian. If no other arguments arguments are specified, this also setsbarstd=True(andboxstd=Truefor violin plots).bars (
bool, optional) – Shorthand forbarstd,barstds.barstd, barstds (
bool,float, or2-tupleoffloat, optional) – Valid only ifmeanormedianisTrue. Standard deviation multiples for thin error bars with optional whiskers (i.e., caps). If scalar, then +/- that multiple is used. IfTrue, the default standard deviation range of +/-3 is used.barpctile, barpctiles (
bool,float, or2-tupleoffloat, optional) – Valid only ifmeanormedianisTrue. As withbarstd, but instead using percentiles for the error bars. If scalar, that percentile range is used (e.g.,90shows the 5th to 95th percentiles). IfTrue, the default percentile range of 0 to 100 is used.bardata (array-like, optional) – Valid only if
meanandmedianareFalse. If shape is 2 x N, these are the lower and upper bounds for the thin error bars. If shape is N, these are the absolute, symmetric deviations from the central points.boxes (
bool, optional) – Shorthand forboxstd,boxstds.boxstd, boxstds, boxpctile, boxpctiles, boxdata (optional) – As with
barstd,barpctile, andbardata, but for thicker error bars representing a smaller interval than the thin error bars. IfboxstdsisTrue, the default standard deviation range of +/-1 is used. IfboxpctilesisTrue, the default percentile range of 25 to 75 is used (i.e., the interquartile range). When “boxes” and “bars” are combined, this has the effect of drawing miniature box-and-whisker plots.capsize (
float, optional) – The cap size for thin error bars in points. Default isrc['errorbar.capsize']=3.0.barz, barzorder, boxz, boxzorder (
float, optional) – The “zorder” for the thin and thick error bars. Default is2.5.barc, barcolor, boxc, boxcolor (
color-spec, optional) – Colors for the thin and thick error bars. Default isrc['boxplot.whiskerprops.color']='black'.barlw, barlinewidth, boxlw, boxlinewidth (
float, optional) – Line widths for the thin and thick error bars, in points. The defaultsrc['boxplot.whiskerprops.linewidth']=1.0(bars) and four times that value (boxes).boxm, boxmarker (
boolormarker-spec, optional) – Whether to draw a small marker in the middle of the box denoting the mean or median position. Ignored ifboxesisFalse. Default is'o'.boxms, boxmarkersize (
size-spec, optional) – The marker size for theboxmarkermarker in points ** 2. Default size is equal to(2 * boxlinewidth) ** 2.boxmc, boxmarkercolor, boxmec, boxmarkeredgecolor (
color-spec, optional) – Color, face color, and edge color for theboxmarkermarker. Default color and edge color are'w'.inbounds (
bool, optional) – Whether to restrict the defaulty(x) axis limits to account for only in-bounds data when thex(y) axis limits have been locked. Default isrc['axes.inbounds']=True. See alsorc['cmap.inbounds'].label, value (
floatorstr, optional) – The single legend label or colorbar coordinate to be used for this plotted element. Can be numeric or string. This is generally used with 1D positional arguments.labels, values (sequence of
floator sequence ofstr, optional) – The legend labels or colorbar coordinates used for each plotted element. Can be numeric or string, and must match the number of plotted elements. This is generally used with 2D positional arguments.colorbar (
bool,int, orstr, optional) – If notNone, this is a location specifying where to draw an inset or outer colorbar from the resulting object(s). IfTrue, the defaultrc['colorbar.loc']='right'is used. If the same location is used in successive plotting calls, object(s) will be added to the existing colorbar in that location (valid for colorbars built from lists of artists). Valid locations are shown in incolorbar.colorbar_kw (dict-like, optional) – Extra keyword args for the call to
colorbar.legend (
bool,int, orstr, optional) – Location specifying where to draw an inset or outer legend from the resulting object(s). IfTrue, the defaultrc['legend.loc']='best'is used. If the same location is used in successive plotting calls, object(s) will be added to existing legend in that location. Valid locations are shown inlegend.legend_kw (dict-like, optional) – Extra keyword args for the call to
legend.**kwargs – Passed to
bar.