PlotAxes.scatterx¶

PlotAxes.scatterx(*args, **kwargs)[source]¶

Plot markers with flexible keyword arguments.

Parameters

*args (x or y, x) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only x coordinates are passed, try to infer the y coordinates from the Series or DataFrame indices or the DataArray coordinates. Otherwise, the y coordinates are np.arange(0, x.shape[0]).
- If the x coordinates are a 2D array, plot each column of data in succession (except where each column of data represents a statistical distribution, as with boxplot, violinplot, or when using means=True or medians=True).
- If any arguments are pint.Quantity, auto-add the pint unit registry to matplotlib’s unit registry using setup_matplotlib. A pint.Quantity embedded in an xarray.DataArray is also supported.
s, size, ms, markersize (float or list of float, optional) – The marker size(s). If this is an array matching the shape of x and y, the units are scaled by smin and smax.
c, color, colors, mc, markercolor, markercolors (color-spec or list thereof, or array, optional) – The marker fill color(s). If this is an array matching the shape of x and y, the colors are generated using cmap, norm, vmin, and vmax.
smin, smax (float, optional) – The minimum and maximum marker size in units points**2 used to scale s. If not provided, the marker sizes are equivalent to the values in s.
vmin, vmax (float, optional) – Used to determine level locations if levels or values is an integer. Actual levels may not fall exactly on vmin and vmax, but the minimum level will be no smaller than vmin and the maximum level will be no larger than vmax. If vmin or vmax are not provided, the minimum and maximum data values are used.
data (dict-like, optional) – A dict-like dataset container (e.g., DataFrame or DataArray). If passed, positional arguments can optionally be string data keys and the arrays used for plotting are retrieved with data[key]. This is a native matplotlib feature.
autoformat (bool, optional) – Whether the x axis labels, y axis labels, axis formatters, axes titles, legend titles, and colorbar labels are automatically configured when a Series, DataFrame, DataArray, or Quantity is passed to the plotting command. Default is rc.autoformat = True.

Other Parameters

lw, linewidth, linewidths, markeredgewidth, markeredgewidths (float or list thereof, optional) – The marker edge width.
edgecolors, markeredgecolor, markeredgecolors (color-spec or list thereof, optional) – The marker edge color.
cmap (colormap spec, optional) – The colormap specifer, passed to the Colormap constructor function.
cmap_kw (dict-like, optional) – Passed to Colormap.
norm (normalizer spec, optional) – The continuous colormap normalizer, passed to the Norm constructor function. If discrete is True this is also used to normalize values passed to DiscreteNorm before colors is selected.
norm_kw (dict-like, optional) – Passed to Norm.
discrete (bool, optional) – If False, then DiscreteNorm is not applied to the colormap. Instead, for non-contour plots, the number of levels will be roughly controlled by rc['cmap.lut']. This has a similar effect to using levels=large_number but it may improve rendering speed. Default is False for imshow, matshow, spy, hexbin, hist2d, and heatmap plots, but True otherwise.
sequential (bool, optional) – Use rc['cmap.sequential'] = 'fire' as the default colormap.
diverging (bool, optional) – Use rc['cmap.diverging'] = 'negpos' as the default colormap and use DivergingNorm as the default continuous normalizer. This will also ensure auto-generated levels include a value at zero.
cyclic (bool, optional) – Use rc['cmap.cyclic'] = 'twilight' as the default colormap and modify the default arguments passed to DiscreteNorm so that colors on either end are distinct.
sequential, diverging, cyclic, qualitative (bool, optional) – Boolean arguments used if cmap is not passed. Set these to True to use the default rc['cmap.sequential'], rc['cmap.diverging'], rc['cmap.cyclic'], and rc['cmap.qualitative'] colormaps. The latter three options also change level- and norm-generation behavior.
extend ({{'neither', 'min', 'max', 'both'}}, optional) – Whether to assign unique colors to out-of-bounds data and draw colorbar “extensions” when a colorbar is drawn.
N – Shorthand for levels.
levels (int or list of float, optional) – The number of level edges or a list of level edges. If the former, locator is used to generate this many level edges at “nice” intervals. If the latter, the levels should be monotonically increasing or decreasing (note that decreasing levels will only work with pcolor plots, not contour plots). Default is rc['cmap.levels'] = 11.
values (int or list of float, optional) – The number of level centers or a list of level centers. If the former, locator is used to generate this many level centers at “nice” intervals. If the latter, levels are inferred using edges. This will override any levels input.
robust (bool, float, or 2-tuple, optional) – If True and vmin or vmax were not provided, they are determined from the 2nd and 98th data percentiles rather than the minimum and maximum. If float, this percentile range is used (for example, 90 corresponds to the 5th to 95th percentiles). If 2-tuple of float, these specific percentiles should be used. This feature is useful when your data has large outliers. Default is rc['cmap.robust'] = False.
inbounds (bool, optional) – If True and vmin or vmax were not provided, when axis limits have been explicitly restricted with set_xlim or set_ylim, out-of-bounds data is ignored. Default is rc['cmap.inbounds'] = True. See also rc['axes.inbounds'].
locator (locator-spec, optional) – The locator used to determine level locations if levels or values is an integer. Passed to the Locator constructor. Default is MaxNLocator with levels integer levels.
locator_kw (dict-like, optional) – Passed to Locator.
symmetric (bool, optional) – If True, automatically generated levels are symmetric about zero. Default is always False.
positive (bool, optional) – If True, automatically generated levels are positive with a minimum at zero. Default is always False.
negative (bool, optional) – If True, automatically generated levels are negative with a maximum at zero. Default is always False.
nozero (bool, optional) – If True, 0 is removed from the level list. This is mainly useful for single-color contour plots.
cycle (cycle-spec, optional) – The cycle specifer, passed to the Cycle constructor. 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, use cycle=False, cycle='none', or cycle=() (analogous to disabling ticks with e.g. xformatter='none'). To restore the default property cycler, use cycle=True.
cycle_kw (dict-like, optional) – Passed to Cycle.
label, value (float or str, optional) – The single legend label or colorbar coordinate to be used for this plotted element. This is generally used with 1D input coordinates.
labels, values (list of float or list of str, 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 input coordinates.
colorbar (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inset or panel colorbar from the resulting object(s). If True, the default rc['colorbar.loc'] = 'right' is used. Valid locations are described in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inset or panel legend from the resulting object(s). If True, the default rc['legend.loc'] = 'best' is used. Valid locations are described in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
mean, means (bool, optional) – Whether to plot the means of each column for 2D x coordinates. Means are calculated with numpy.nanmean. If no other arguments are specified, this also sets barstd=True (and boxstd=True for violin plots).
median, medians (bool, optional) – Whether to plot the medians of each column for 2D x coordinates. Medians are calculated with numpy.nanmedian. If no other arguments arguments are specified, this also sets barstd=True (and boxstd=True for violin plots).
barstd, barstds (bool, float, or 2-tuple of float, optional) – Valid only if `mean` or `median` is ``True``. Standard deviation multiples for thin error bars with optional whiskers (i.e., caps). If scalar, then +/- that multiple is used. If True, the default standard deviation range of +/-3 is used.
barpctile, barpctiles (bool, float, or 2-tuple of float, optional) – Valid only if `mean` or `median` is ``True``. As with barstd, but instead using percentiles for the error bars. If scalar, that percentile range is used (e.g., 90 shows the 5th to 95th percentiles). If True, the default percentile range of 0 to 100 is used.
bardata (2 x N array or 1D array, optional) – Valid only if `mean` and `median` are ``False``. 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.
boxstd, boxstds, boxpctile, boxpctiles, boxdata (optional) – As with barstd, barpctile, and bardata, but for thicker error bars representing a smaller interval than the thin error bars. If boxstd is True, the default standard deviation range of +/-1 is used. If boxpctiles is True, 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 is rc['errorbar.capsize'] = 3.0.
barz, barzorder, boxz, boxzorder (float, optional) – The “zorder” for the thin and thick error bars. Default is 2.5.
barc, barcolor, boxc, boxcolor (color-spec, optional) – Colors for the thin and thick error bars. Default is rc['boxplot.whiskerprops.color'] = 'black'.
barlw, barlinewidth, boxlw, boxlinewidth (float, optional) – Line widths for the thin and thick error bars, in points. The defaults rc['boxplot.whiskerprops.linewidth'] = 1.0 (bars) and four times that value (boxes).
boxm, boxmarker (bool or marker-spec, optional) – Whether to draw a small marker in the middle of the box denoting the mean or median position. Ignored if boxes is False. Default is 'o'.
boxms, boxmarkersize (size-spec, optional) – The marker size for the boxmarker marker 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 the boxmarker marker. Default color and edge color are 'w'.
shadestd, shadestds, shadepctile, shadepctiles, shadedata (optional) – As with barstd, barpctile, and bardata, but using shading to indicate the error range. If shadestds is True, the default standard deviation range of +/-2 is used. If shadepctiles is True, the default percentile range of 10 to 90 is used.
fadestd, fadestds, fadepctile, fadepctiles, fadedata (optional) – As with shadestd, shadepctile, and shadedata, but for an additional, more faded, secondary shaded region. If fadestds is True, the default standard deviation range of +/-3 is used. If fadepctiles is True, the default percentile range of 0 to 100 is used.
shadec, shadecolor, fadec, fadecolor (color-spec, optional) – Colors for the different shaded regions. Default is to inherit the parent color.
shadez, shadezorder, fadez, fadezorder (float, optional) – The “zorder” for the different shaded regions. Default is 1.5.
shadea, shadealpha, fadea, fadealpha (float, optional) – The opacity for the different shaded regions. Defaults are 0.4 and 0.2.
shadelw, shadelinewidth, fadelw, fadelinewidth (float, optional) – The edge line width for the shading patches. Default is rc['patch.linewidth'] = 0.6.
shdeec, shadeedgecolor, fadeec, fadeedgecolor (float, optional) – The edge color for the shading patches. Default is 'none'.
shadelabel, fadelabel (bool or str, optional) – Labels for the shaded regions to be used as separate legend entries. To toggle labels “on” and apply a default label, use e.g. shadelabel=True. To apply a custom label, use e.g. shadelabel='label'. Otherwise, the shading is drawn underneath the line and/or marker in the legend entry.
inbounds (bool, optional) – Whether to restrict the default y (x) axis limits to account for only in-bounds data when the x (y) axis limits have been locked. Default is rc['axes.inbounds'] = True. See also rc['cmap.inbounds'].
**kwargs – Passed to scatter.