PlotAxes.scatterx¶
- PlotAxes.scatterx(*args, **kwargs)[source]¶
Plot markers with flexible keyword arguments.
- Parameters
*args (
x
ory
,x
) – The data passed as positional or keyword arguments. Interpreted as follows:If only
x
coordinates are passed, try to infer they
coordinates from theSeries
orDataFrame
indices or theDataArray
coordinates. Otherwise, they
coordinates arenp.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 withboxplot
,violinplot
, or when usingmeans=True
ormedians=True
).If any arguments are
pint.Quantity
, auto-add the pint unit registry to matplotlib’s unit registry usingsetup_matplotlib
. Apint.Quantity
embedded in anxarray.DataArray
is also supported.
s, size, ms, markersize (
float
or array-like orunit-spec
, optional) – The marker size area(s). If this is an array matching the shape ofx
andy
, the units are scaled bysmin
andsmax
. If this contains unit string(s), it is processed byunits
and represents the width rather than area.c, color, colors, mc, markercolor, markercolors, fc, facecolor, facecolors (array-like or
color-spec
, optional) – The marker color(s). If this is an array matching the shape ofx
andy
, the colors are generated usingcmap
,norm
,vmin
, andvmax
. Otherwise, this should be a valid matplotlib color.smin, smax (
float
, optional) – The minimum and maximum marker size area in unitspoints ** 2
. Ignored ifabsolute_size
isTrue
. Default value forsmin
is1
and forsmax
is the square ofrc['lines.markersize']
=6.0
.absolute_size (
bool
, optional) – Whethers
should be taken to represent “absolute” marker size areas in unitspoints ** 2
or “relative” marker size areas scaled bysmin
andsmax
. Default isTrue
ifs
is scalar andFalse
ifs
is array-like.vmin, vmax (
float
, optional) – The minimum and maximum color scale values used with thenorm
normalizer. Ifdiscrete
isFalse
these are the absolute limits, and ifdiscrete
isTrue
these are the approximate limits used to automatically determinelevels
orvalues
lists at “nice” intervals. Iflevels
orvalues
were already passed as lists, these are ignored, andvmin
andvmax
are set to the minimum and maximum of the lists. Ifrobust
was passed, the defaultvmin
andvmax
are some percentile range of the data values. Otherwise, the defaultvmin
andvmax
are the minimum and maximum of the data values.data (dict-like, optional) – A dict-like dataset container (e.g.,
DataFrame
orDataset
). If passed, each data argument can optionally be a stringkey
and the arrays used for plotting are retrieved withdata[key]
. This is a native matplotlib feature.autoformat (
bool
, optional) – Whether thex
axis labels,y
axis labels, axis formatters, axes titles, legend titles, and colorbar labels are automatically configured when aSeries
,DataFrame
,DataArray
, orQuantity
is passed to the plotting command. Default isrc.autoformat
=True
. Formatting ofpint.Quantity
unit strings is controlled byrc.unitformat
='L'
.
- Other Parameters
cmap (
colormap-spec
, optional) – The colormap specifer, passed to theColormap
constructor function.c, color, colors (
color-spec
or sequence ofcolor-spec
, optional) – The color(s) used to create aDiscreteColormap
. If not passed,cmap
is used.norm (
norm-spec
, optional) – The data value normalizer, passed to theNorm
constructor function. Ifdiscrete
isTrue
then 1) this affects the default level-generation algorithm (e.g.norm='log'
builds levels in log-space) and 2) this is passed toDiscreteNorm
to scale the colors before they are discretized (ifnorm
is not already aDiscreteNorm
).extend (
{'neither', 'both', 'min', 'max'}
, optional) – Direction for drawing colorbar “extensions” (i.e. color keys for out-of-bounds data on the end of the colorbar). Default is'neither'
.discrete (
bool
, optional) – IfFalse
, thenDiscreteNorm
is not applied to the colormap. Instead, for non-contour plots, the number of levels will be roughly controlled byrc['cmap.lut']
. This has a similar effect to usinglevels=large_number
but it may improve rendering speed. Default isTrue
for only contour-plotting commands likecontourf
and pseudocolor-plotting commands likepcolor
.sequential, diverging, cyclic, qualitative (
bool
, optional) – Boolean arguments used ifcmap
is not passed. Set these toTrue
to use the defaultrc['cmap.sequential']
,rc['cmap.diverging']
,rc['cmap.cyclic']
, andrc['cmap.qualitative']
colormaps. Thediverging
option also appliesDivergingNorm
as the default continuous normalizer.N – Shorthand for
levels
.levels (
int
or sequence offloat
, optional) – The number of level edges or a sequence 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 decreasing levels fail withcontour
plots). Default isrc['cmap.levels']
=11
.values (
int
or sequence offloat
, optional) – The number of level centers or a sequence of level centers. If the former,locator
is used to generate this many level centers at “nice” intervals. If the latter, levels are inferred usingedges
. This will override anylevels
input.robust (
bool
,float
, or2-tuple
, optional) – IfTrue
andvmin
orvmax
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 isrc['cmap.robust']
=False
.inbounds (
bool
, optional) – IfTrue
andvmin
orvmax
were not provided, when axis limits have been explicitly restricted withset_xlim
orset_ylim
, out-of-bounds data is ignored. Default isrc['cmap.inbounds']
=True
. See alsorc['axes.inbounds']
.locator (
locator-spec
, optional) – The locator used to determine level locations iflevels
orvalues
were not already passed as lists. Passed to theLocator
constructor. Default isMaxNLocator
withlevels
integer levels.locator_kw (dict-like, optional) – Keyword arguments passed to
matplotlib.ticker.Locator
class.symmetric (
bool
, optional) – IfTrue
, the normalization range or discrete colormap levels are symmetric about zero. Default is alwaysFalse
.positive (
bool
, optional) – IfTrue
, the normalization range or discrete colormap levels are positive with a minimum at zero. Default is alwaysFalse
.negative (
bool
, optional) – IfTrue
, the normaliation range or discrete colormap levels are negative with a minimum at zero. Default is alwaysFalse
.nozero (
bool
, optional) – IfTrue
,0
is removed from the level list. This is mainly useful for single-colorcontour
plots.cycle (
cycle-spec
, optional) – The cycle specifer, passed to theCycle
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, 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, mew, markeredgewidth, markeredgewidths (
float
or sequence, optional) – The marker edge width(s).edgecolors, markeredgecolor, markeredgecolors (
color-spec
or sequence, optional) – The marker edge color(s).mean, means (
bool
, optional) – Whether to plot the means of each column for 2Dx
coordinates. Means are calculated withnumpy.nanmean
. If no other arguments are specified, this also setsbarstd=True
(andboxstd=True
for violin plots).median, medians (
bool
, optional) – Whether to plot the medians of each column for 2Dx
coordinates. Medians are calculated withnumpy.nanmedian
. If no other arguments arguments are specified, this also setsbarstd=True
(andboxstd=True
for violin plots).bars (
bool
, optional) – Shorthand forbarstd
,barstds
.barstd, barstds (
bool
,float
, or2-tuple
offloat
, optional) – Valid only ifmean
ormedian
isTrue
. 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-tuple
offloat
, optional) – Valid only ifmean
ormedian
isTrue
. As withbarstd
, but instead using percentiles for the error bars. If scalar, that percentile range is used (e.g.,90
shows the 5th to 95th percentiles). IfTrue
, the default percentile range of 0 to 100 is used.bardata (array-like, optional) – Valid only if
mean
andmedian
areFalse
. 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. Ifboxstds
isTrue
, the default standard deviation range of +/-1 is used. Ifboxpctiles
isTrue
, 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 (
bool
ormarker-spec
, optional) – Whether to draw a small marker in the middle of the box denoting the mean or median position. Ignored ifboxes
isFalse
. Default is'o'
.boxms, boxmarkersize (
size-spec
, optional) – The marker size for theboxmarker
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 theboxmarker
marker. Default color and edge color are'w'
.shade (
bool
, optional) – Shorthand forshadestd
.shadestd, shadestds, shadepctile, shadepctiles, shadedata (optional) – As with
barstd
,barpctile
, andbardata
, but using shading to indicate the error range. Ifshadestds
isTrue
, the default standard deviation range of +/-2 is used. Ifshadepctiles
isTrue
, the default percentile range of 10 to 90 is used.fade (
bool
, optional) – Shorthand forfadestd
.fadestd, fadestds, fadepctile, fadepctiles, fadedata (optional) – As with
shadestd
,shadepctile
, andshadedata
, but for an additional, more faded, secondary shaded region. Iffadestds
isTrue
, the default standard deviation range of +/-3 is used. Iffadepctiles
isTrue
, 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 is1.5
.shadea, shadealpha, fadea, fadealpha (
float
, optional) – The opacity for the different shaded regions. Defaults are0.4
and0.2
.shadelw, shadelinewidth, fadelw, fadelinewidth (
float
, optional) – The edge line width for the shading patches. Default isrc['patch.linewidth']
=0.6
.shdeec, shadeedgecolor, fadeec, fadeedgecolor (
float
, optional) – The edge color for the shading patches. Default is'none'
.shadelabel, fadelabel (
bool
orstr
, 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 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 (
float
orstr
, 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
float
or 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
scatter
.