PlotAxes¶

class PlotAxes(*args, **kwargs)[source]¶

Bases: proplot.axes.base.Axes

The second lowest-level Axes subclass used by proplot. Implements all plotting overrides.

Parameters: *args, **kwargs – Passed to Axes.

Methods Summary

`area`(args, *kwargs)	Plot individual, grouped, or overlaid shading patches.
`areax`(args, *kwargs)	Plot individual, grouped, or overlaid shading patches.
`bar`(args, *kwargs)	Plot individual, grouped, or stacked bars.
`barbs`(x, y, u, v, c, **kwargs)	Plot wind barbs.
`barh`(args, *kwargs)	Plot individual, grouped, or stacked bars.
`box`(args, *kwargs)	Plot vertical boxes and whiskers with a nice default style.
`boxes`(*[, new_obj, message])
`boxh`(args, *kwargs)	Plot horizontal boxes and whiskers with a nice default style.
`boxplot`(args, *kwargs)	Plot vertical boxes and whiskers with a nice default style.
`boxploth`(args, *kwargs)	Plot horizontal boxes and whiskers with a nice default style.
`contour`(x, y, z, **kwargs)	Plot contour lines.
`contourf`(x, y, z, **kwargs)	Plot filled contours.
`fill_between`(args, *kwargs)	Plot individual, grouped, or overlaid shading patches.
`fill_betweenx`(args, *kwargs)	Plot individual, grouped, or overlaid shading patches.
`heatmap`(*args[, aspect])	Plot grid boxes with formatting suitable for heatmaps.
`hexbin`(x, y, weights, **kwargs)	Plot a 2D hexagonally binned histogram.
`hist`(args, *kwargs)	Plot vertical histograms.
`hist2d`(x, y, bins, **kwargs)	Plot a standard 2D histogram.
`histh`(args, *kwargs)	Plot horizontal histograms.
`hlines`(args, *kwargs)	Plot horizontal lines.
`imshow`(z, **kwargs)	Plot an image.
`line`(args, *kwargs)	Plot standard lines.
`linex`(args, *kwargs)	Plot standard lines.
`matshow`(z, **kwargs)	Plot a matrix.
`parametric`(x, y, c, *[, interp, scalex, scaley])	Plot a parametric line.
`pcolor`(x, y, z, **kwargs)	Plot irregular grid boxes.
`pcolorfast`(x, y, z, **kwargs)	Plot grid boxes quickly.
`pcolormesh`(x, y, z, **kwargs)	Plot regular grid boxes.
`pie`(x, explode, *[, labelpad, labeldistance])	Plot a pie chart.
`plot`(args, *kwargs)	Plot standard lines.
`plotx`(args, *kwargs)	Plot standard lines.
`quiver`(x, y, u, v, c, **kwargs)	Plot quiver arrows.
`scatter`(args, *kwargs)	Plot markers with flexible keyword arguments.
`scatterx`(args, *kwargs)	Plot markers with flexible keyword arguments.
`set_prop_cycle`(args, *kwargs)	Set the property cycle of the Axes.
`spy`(z, **kwargs)	Plot a sparcity pattern.
`stem`(args, *kwargs)	Plot stem lines.
`stemx`(args, *kwargs)	Plot stem lines.
`step`(args, *kwargs)	Plot step lines.
`stepx`(args, *kwargs)	Plot step lines.
`stream`(args, *kwargs)	Plot streamlines.
`streamplot`(x, y, u, v, c, **kwargs)	Plot streamlines.
`tricontour`(x, y, z, **kwargs)	Plot contour lines on a triangular grid.
`tricontourf`(x, y, z, **kwargs)	Plot filled contours on a triangular grid.
`tripcolor`(x, y, z, **kwargs)	Plot triangular grid boxes.
`violin`(args, *kwargs)	Plot vertical violins with a nice default style matching this matplotlib example.
`violinh`(args, *kwargs)	Plot horizontal violins with a nice default style matching this matplotlib example.
`violinplot`(args, *kwargs)	Plot vertical violins with a nice default style matching this matplotlib example.
`violinploth`(args, *kwargs)	Plot horizontal violins with a nice default style matching this matplotlib example.
`violins`(*[, new_obj, message])
`vlines`(args, *kwargs)	Plot vertical lines.

Methods Documentation

area(*args, **kwargs)[source]¶

Plot individual, grouped, or overlaid shading patches.

Parameters

*args (y2 or x, y2, or x, y1, y2) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only y coordinates are passed, try to infer the x coordinates from the Series or DataFrame indices or the DataArray coordinates. Otherwise, the x coordinates are np.arange(0, y2.shape[0]).
- If only x and y2 coordinates are passed, set the y1 coordinates to zero. This draws elements originating from the zero line.
- If both y1 and y2 are provided, draw elements between these points. If either are 2D, draw elements by iterating over each column.
- 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.
stack, stacked (bool, optional) – Whether to “stack” area patches from successive columns of y data or plot area patches on top of each other. Default is False.
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

where (ndarray, optional) – A boolean mask for the points that should be shaded. See this matplotlib example.
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.
lw, linewidth, linewidths (float, optional) – The edge width for the patches.
ls, linestyle, linestyles (str, optional) – The edge style for the patches.
ec, edgecolor, edgecolors (color-spec, optional) – The edge color for the patches.
fc, facecolor, facecolors, fillcolor, fillcolors (color-spec, optional) – The face color for the patches.
a, alpha, alphas (float, optional) – The face opacity for the patches.
negpos (bool, optional) – Whether to shade patches where y2 >= y1 with poscolor and where y2 < y1 with negcolor. Default is False. If True this function will return a 2-tuple of values.
negcolor, poscolor (color-spec, optional) – Colors to use for the negative and positive patches. Ignored if negpos is False. Defaults are rc.negcolor = 'blue7' and rc.poscolor = 'red7'.
edgefix (bool or float, optional) – Whether to fix the common issue where white lines appear between adjacent patches in saved vector graphics. This can slow down figure rendering. Default is rc.edgefix = True. If True, a small default linewidth is used to cover up the white lines. If float, this linewidth is used.
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'].
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 (sequence of float or sequence 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 inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to fill_between.

areax(*args, **kwargs)[source]¶

Plot individual, grouped, or overlaid shading patches.

Parameters

*args (x2 or y, x2, or y, x1, x2) – 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, x2.shape[0]).
- If only y and x2 coordinates are passed, set the x1 coordinates to zero. This draws elements originating from the zero line.
- If both x1 and x2 are provided, draw elements between these points. If either are 2D, draw elements by iterating over each column.
- 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.
stack, stacked (bool, optional) – Whether to “stack” area patches from successive columns of x data or plot area patches on top of each other. Default is False.
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

where (ndarray, optional) – A boolean mask for the points that should be shaded. See this matplotlib example.
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.
lw, linewidth, linewidths (float, optional) – The edge width for the patches.
ls, linestyle, linestyles (str, optional) – The edge style for the patches.
ec, edgecolor, edgecolors (color-spec, optional) – The edge color for the patches.
fc, facecolor, facecolors, fillcolor, fillcolors (color-spec, optional) – The face color for the patches.
a, alpha, alphas (float, optional) – The face opacity for the patches.
negpos (bool, optional) – Whether to shade patches where y2 >= y1 with poscolor and where y2 < y1 with negcolor. Default is False. If True this function will return a 2-tuple of values.
negcolor, poscolor (color-spec, optional) – Colors to use for the negative and positive patches. Ignored if negpos is False. Defaults are rc.negcolor = 'blue7' and rc.poscolor = 'red7'.
edgefix (bool or float, optional) – Whether to fix the common issue where white lines appear between adjacent patches in saved vector graphics. This can slow down figure rendering. Default is rc.edgefix = True. If True, a small default linewidth is used to cover up the white lines. If float, this linewidth is used.
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'].
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 (sequence of float or sequence 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 inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to fill_betweenx.

bar(*args, **kwargs)[source]¶

Plot individual, grouped, or stacked bars.

Parameters

*args (y or x, y) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only y coordinates are passed, try to infer the x coordinates from the Series or DataFrame indices or the DataArray coordinates. Otherwise, the x coordinates are np.arange(0, y.shape[0]).
- If the y 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.
width (float or 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 (float or array-like, optional) – The coordinate(s) of the bottom edge of the bars. Default is 0. Can be passed as a fourth positinal argument.
absolute_width (bool, optional) – Whether to make the width units absolute. If True, this restores the default matplotlib behavior. Default is False.
stack, stacked (bool, optional) – Whether to “stack” bars from successive columns of y data or plot bars side-by-side in groups. Default is False.
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

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.
lw, linewidth, linewidths (float, optional) – The edge width for the patches.
ls, linestyle, linestyles (str, optional) – The edge style for the patches.
ec, edgecolor, edgecolors (color-spec, optional) – The edge color for the patches.
fc, facecolor, facecolors, fillcolor, fillcolors (color-spec, optional) – The face color for the patches.
a, alpha, alphas (float, optional) – The face opacity for the patches.
negpos (bool, optional) – Whether to shade bars where height >= 0 with poscolor and where height < 0 with negcolor. Default is False. If True this function will return a 2-tuple of values.
negcolor, poscolor (color-spec, optional) – Colors to use for the negative and positive bars. Ignored if negpos is False. Defaults are rc.negcolor = 'blue7' and rc.poscolor = 'red7'.
edgefix (bool or float, optional) – Whether to fix the common issue where white lines appear between adjacent patches in saved vector graphics. This can slow down figure rendering. Default is rc.edgefix = True. If True, a small default linewidth is used to cover up the white lines. If float, this linewidth is used.
mean, means (bool, optional) – Whether to plot the means of each column for 2D y 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 y 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 (array-like, 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 boxstds 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'.
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'].
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 (sequence of float or sequence 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 inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to bar.

barbs(x, y, u, v, c, **kwargs)[source]¶

Plot wind barbs.

Parameters

*args (u, v or x, y, u, v) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only u and v coordinates are passed, try to infer the x and y coordinates from the DataFrame indices and columns or the DataArray coordinates. Otherwise, the y coordinates are np.arange(0, y.shape[0]) and the x coordinates are np.arange(0, y.shape[1]).
- For pcolor and pcolormesh, calculate coordinate edges using edges or edges2d if centers were provided. For all other methods, calculate coordinate centers if edges were provided.
- If the x or y coordinates are pint.Quantity, auto-add the pint unit registry to matplotlib’s unit registry using setup_matplotlib. If the u and v coordinates are pint.Quantity, pass the magnitude to the plotting command. A pint.Quantity embedded in an xarray.DataArray is also supported.
c, color, colors (array-like or color-spec, optional) – The colors of the wind barbs passed as either a keyword argument or a fifth positional argument. This can be a single color or a color array to be scaled by cmap and norm.
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.
transpose (bool, optional) – Whether to transpose the input data. This should be used when passing datasets with column-major dimension order (x, y). Otherwise row-major dimension order (y, x) is expected.
order ({{'C', 'F'}}, optional) – Alternative to transpose. 'C' corresponds to the default C-cyle row-major ordering (equivalent to transpose=False). 'F' corresponds to Fortran-style column-major ordering (equivalent to transpose=True).
globe (bool, optional) – For proplot.axes.GeoAxes only. Whether to enforce global coverage. Default is False. When set to True this does the following:
1. Interpolates input data to the North and South poles by setting the data values at the poles to the mean from latitudes nearest each pole.
2. Makes meridional coverage “circular”, i.e. the last longitude coordinate equals the first longitude coordinate plus 360°.
3. When basemap is the backend, cycles 1D longitude vectors to fit within the map edges. For example, if the central longitude is 90°, the data is shifted so that it spans -90° to 270°.

Other Parameters

cmap (colormap-spec, optional) – The colormap specifer, passed to the Colormap constructor function.
cmap_kw (dict-like, optional) – Passed to Colormap.
c, color, colors (color-spec or sequence of color-spec, optional) – The color(s) used to create a DiscreteColormap. If not passed, cmap is used.
norm (norm-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, 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 diverging option also applies DivergingNorm as the default continuous normalizer.
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 sequence of float, 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 that decreasing levels will only work with pcolor plots, not contour plots). Default is rc['cmap.levels'] = 11.
values (int or sequence of float, 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 using edges. This will override any levels input.
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.
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.
**kwargs – Passed to matplotlib.axes.Axes.barbs

barh(*args, **kwargs)[source]¶

Plot individual, grouped, or stacked bars.

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.
width (float or array-like, optional) – The width(s) of the bars relative to the y coordinate step size. Can be passed as a third positional argument.
left (float or array-like, optional) – The coordinate(s) of the left edge of the bars. Default is 0. Can be passed as a fourth positinal argument.
absolute_width (bool, optional) – Whether to make the width units absolute. If True, this restores the default matplotlib behavior. Default is False.
stack, stacked (bool, optional) – Whether to “stack” bars from successive columns of x data or plot bars side-by-side in groups. Default is False.
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

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.
lw, linewidth, linewidths (float, optional) – The edge width for the patches.
ls, linestyle, linestyles (str, optional) – The edge style for the patches.
ec, edgecolor, edgecolors (color-spec, optional) – The edge color for the patches.
fc, facecolor, facecolors, fillcolor, fillcolors (color-spec, optional) – The face color for the patches.
a, alpha, alphas (float, optional) – The face opacity for the patches.
negpos (bool, optional) – Whether to shade bars where height >= 0 with poscolor and where height < 0 with negcolor. Default is False. If True this function will return a 2-tuple of values.
negcolor, poscolor (color-spec, optional) – Colors to use for the negative and positive bars. Ignored if negpos is False. Defaults are rc.negcolor = 'blue7' and rc.poscolor = 'red7'.
edgefix (bool or float, optional) – Whether to fix the common issue where white lines appear between adjacent patches in saved vector graphics. This can slow down figure rendering. Default is rc.edgefix = True. If True, a small default linewidth is used to cover up the white lines. If float, this linewidth is used.
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 (array-like, 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 boxstds 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'.
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'].
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 (sequence of float or sequence 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 inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to barh.

box(*args, **kwargs)[source]¶

Plot vertical boxes and whiskers with a nice default style.

Parameters

*args (y or x, y) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only y coordinates are passed, try to infer the x coordinates from the Series or DataFrame indices or the DataArray coordinates. Otherwise, the x coordinates are np.arange(0, y.shape[0]).
- If the y 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.
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

fill (bool, optional) – Whether to fill the box with a color. Default is True.
mean, means (bool, optional) – If True, this passes showmeans=True and meanline=True to boxplot.
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.
lw, linewidth, linewidths (float, optional) – The edge width for the boxes. Default is rc['patch.linewidth'] = 0.6.
c, color, colors, ec, edgecolor, edgecolors (color-spec, optional) – The edge color for the boxes. Default is 'black'.
fc, facecolor, fillcolor, facecolors, fillcolors (color-spec, optional) – The fill color for the boxes. Default is to use the property cycle.
a, alpha, alphas (float, optional) – The opacity of the boxes. Default is 1.0.
m, marker, ms, markersize (float or str, optional) – Marker style and size for the ‘fliers’, i.e. outliers. Default is determined by rc['boxplot.flierprops'].
meanls, medianls, meanlinestyle, medianlinestyle, meanlinestyles, medianlinestyles (line style-spec, optional) – The line style for the mean and median lines drawn horizontally across the box.
boxc, capc, whiskerc, flierc, meanc, medianc, boxcolor, capcolor, whiskercolor, fliercolor, meancolor, mediancolor boxcolors, capcolors, whiskercolors, fliercolors, meancolors, mediancolors (color-spec or sequence, optional) – The color of various boxplot components. If a sequence, should be the same length as the number of boxes. These are shorthands so you don’t have to pass e.g. a boxprops dictionary.
boxlw, caplw, whiskerlw, flierlw, meanlw, medianlw, boxlinewidth, caplinewidth, meanlinewidth, medianlinewidth, whiskerlinewidth, flierlinewidth, boxlinewidths, caplinewidths, meanlinewidths, medianlinewidths, whiskerlinewidths, flierlinewidths (float, optional) – The line width of various boxplot components. These are shorthands so you don’t have to pass e.g. a boxprops dictionary.
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 (sequence of float or sequence 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.
**kwargs – Passed to matplotlib.axes.Axes.boxplot.

boxes(*, new_obj=<function PlotAxes.box>, message="'boxes' was deprecated in version 0.8 and will be removed in a future release. Please use 'box' instead.", **kwargs)¶

boxh(*args, **kwargs)[source]¶

Plot horizontal boxes and whiskers with a nice default style.

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.
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

fill (bool, optional) – Whether to fill the box with a color. Default is True.
mean, means (bool, optional) – If True, this passes showmeans=True and meanline=True to boxplot.
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.
lw, linewidth, linewidths (float, optional) – The edge width for the boxes. Default is rc['patch.linewidth'] = 0.6.
c, color, colors, ec, edgecolor, edgecolors (color-spec, optional) – The edge color for the boxes. Default is 'black'.
fc, facecolor, fillcolor, facecolors, fillcolors (color-spec, optional) – The fill color for the boxes. Default is to use the property cycle.
a, alpha, alphas (float, optional) – The opacity of the boxes. Default is 1.0.
m, marker, ms, markersize (float or str, optional) – Marker style and size for the ‘fliers’, i.e. outliers. Default is determined by rc['boxplot.flierprops'].
meanls, medianls, meanlinestyle, medianlinestyle, meanlinestyles, medianlinestyles (line style-spec, optional) – The line style for the mean and median lines drawn horizontally across the box.
boxc, capc, whiskerc, flierc, meanc, medianc, boxcolor, capcolor, whiskercolor, fliercolor, meancolor, mediancolor boxcolors, capcolors, whiskercolors, fliercolors, meancolors, mediancolors (color-spec or sequence, optional) – The color of various boxplot components. If a sequence, should be the same length as the number of boxes. These are shorthands so you don’t have to pass e.g. a boxprops dictionary.
boxlw, caplw, whiskerlw, flierlw, meanlw, medianlw, boxlinewidth, caplinewidth, meanlinewidth, medianlinewidth, whiskerlinewidth, flierlinewidth, boxlinewidths, caplinewidths, meanlinewidths, medianlinewidths, whiskerlinewidths, flierlinewidths (float, optional) – The line width of various boxplot components. These are shorthands so you don’t have to pass e.g. a boxprops dictionary.
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 (sequence of float or sequence 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.
**kwargs – Passed to matplotlib.axes.Axes.boxplot.

boxplot(*args, **kwargs)[source]¶

Plot vertical boxes and whiskers with a nice default style.

Parameters

*args (y or x, y) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only y coordinates are passed, try to infer the x coordinates from the Series or DataFrame indices or the DataArray coordinates. Otherwise, the x coordinates are np.arange(0, y.shape[0]).
- If the y 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.
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

fill (bool, optional) – Whether to fill the box with a color. Default is True.
mean, means (bool, optional) – If True, this passes showmeans=True and meanline=True to boxplot.
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.
lw, linewidth, linewidths (float, optional) – The edge width for the boxes. Default is rc['patch.linewidth'] = 0.6.
c, color, colors, ec, edgecolor, edgecolors (color-spec, optional) – The edge color for the boxes. Default is 'black'.
fc, facecolor, fillcolor, facecolors, fillcolors (color-spec, optional) – The fill color for the boxes. Default is to use the property cycle.
a, alpha, alphas (float, optional) – The opacity of the boxes. Default is 1.0.
m, marker, ms, markersize (float or str, optional) – Marker style and size for the ‘fliers’, i.e. outliers. Default is determined by rc['boxplot.flierprops'].
meanls, medianls, meanlinestyle, medianlinestyle, meanlinestyles, medianlinestyles (line style-spec, optional) – The line style for the mean and median lines drawn horizontally across the box.
boxc, capc, whiskerc, flierc, meanc, medianc, boxcolor, capcolor, whiskercolor, fliercolor, meancolor, mediancolor boxcolors, capcolors, whiskercolors, fliercolors, meancolors, mediancolors (color-spec or sequence, optional) – The color of various boxplot components. If a sequence, should be the same length as the number of boxes. These are shorthands so you don’t have to pass e.g. a boxprops dictionary.
boxlw, caplw, whiskerlw, flierlw, meanlw, medianlw, boxlinewidth, caplinewidth, meanlinewidth, medianlinewidth, whiskerlinewidth, flierlinewidth, boxlinewidths, caplinewidths, meanlinewidths, medianlinewidths, whiskerlinewidths, flierlinewidths (float, optional) – The line width of various boxplot components. These are shorthands so you don’t have to pass e.g. a boxprops dictionary.
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 (sequence of float or sequence 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.
**kwargs – Passed to matplotlib.axes.Axes.boxplot.

boxploth(*args, **kwargs)[source]¶

Plot horizontal boxes and whiskers with a nice default style.

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.
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

fill (bool, optional) – Whether to fill the box with a color. Default is True.
mean, means (bool, optional) – If True, this passes showmeans=True and meanline=True to boxplot.
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.
lw, linewidth, linewidths (float, optional) – The edge width for the boxes. Default is rc['patch.linewidth'] = 0.6.
c, color, colors, ec, edgecolor, edgecolors (color-spec, optional) – The edge color for the boxes. Default is 'black'.
fc, facecolor, fillcolor, facecolors, fillcolors (color-spec, optional) – The fill color for the boxes. Default is to use the property cycle.
a, alpha, alphas (float, optional) – The opacity of the boxes. Default is 1.0.
m, marker, ms, markersize (float or str, optional) – Marker style and size for the ‘fliers’, i.e. outliers. Default is determined by rc['boxplot.flierprops'].
meanls, medianls, meanlinestyle, medianlinestyle, meanlinestyles, medianlinestyles (line style-spec, optional) – The line style for the mean and median lines drawn horizontally across the box.
boxc, capc, whiskerc, flierc, meanc, medianc, boxcolor, capcolor, whiskercolor, fliercolor, meancolor, mediancolor boxcolors, capcolors, whiskercolors, fliercolors, meancolors, mediancolors (color-spec or sequence, optional) – The color of various boxplot components. If a sequence, should be the same length as the number of boxes. These are shorthands so you don’t have to pass e.g. a boxprops dictionary.
boxlw, caplw, whiskerlw, flierlw, meanlw, medianlw, boxlinewidth, caplinewidth, meanlinewidth, medianlinewidth, whiskerlinewidth, flierlinewidth, boxlinewidths, caplinewidths, meanlinewidths, medianlinewidths, whiskerlinewidths, flierlinewidths (float, optional) – The line width of various boxplot components. These are shorthands so you don’t have to pass e.g. a boxprops dictionary.
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 (sequence of float or sequence 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.
**kwargs – Passed to matplotlib.axes.Axes.boxplot.

contour(x, y, z, **kwargs)[source]¶

Plot contour lines.

Parameters

*args (z or x, y, z) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only z coordinates are passed, try to infer the x and y coordinates from the DataFrame indices and columns or the DataArray coordinates. Otherwise, the y coordinates are np.arange(0, y.shape[0]) and the x coordinates are np.arange(0, y.shape[1]).
- For pcolor and pcolormesh, calculate coordinate edges using edges or edges2d if centers were provided. For all other methods, calculate coordinate centers if edges were provided.
- If the x or y coordinates are pint.Quantity, auto-add the pint unit registry to matplotlib’s unit registry using setup_matplotlib. If the z coordinates are pint.Quantity, pass the magnitude to the plotting command. A pint.Quantity embedded in an xarray.DataArray is also supported.
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.
transpose (bool, optional) – Whether to transpose the input data. This should be used when passing datasets with column-major dimension order (x, y). Otherwise row-major dimension order (y, x) is expected.
order ({{'C', 'F'}}, optional) – Alternative to transpose. 'C' corresponds to the default C-cyle row-major ordering (equivalent to transpose=False). 'F' corresponds to Fortran-style column-major ordering (equivalent to transpose=True).
globe (bool, optional) – For proplot.axes.GeoAxes only. Whether to enforce global coverage. Default is False. When set to True this does the following:
1. Interpolates input data to the North and South poles by setting the data values at the poles to the mean from latitudes nearest each pole.
2. Makes meridional coverage “circular”, i.e. the last longitude coordinate equals the first longitude coordinate plus 360°.
3. When basemap is the backend, cycles 1D longitude vectors to fit within the map edges. For example, if the central longitude is 90°, the data is shifted so that it spans -90° to 270°.

Other Parameters

cmap (colormap-spec, optional) – The colormap specifer, passed to the Colormap constructor function.
cmap_kw (dict-like, optional) – Passed to Colormap.
c, color, colors (color-spec or sequence of color-spec, optional) – The color(s) used to create a DiscreteColormap. If not passed, cmap is used.
norm (norm-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, 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 diverging option also applies DivergingNorm as the default continuous normalizer.
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 sequence of float, 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 that decreasing levels will only work with pcolor plots, not contour plots). Default is rc['cmap.levels'] = 11.
values (int or sequence of float, 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 using edges. This will override any levels input.
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.
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.
lw, linewidth, linewidths (float, optional) – The width of the contour lines. For contourf plots, lines are added between the filled contours.
ls, linestyle, linestyles (str, optional) – The style of the contour lines. For contourf plots, lines are added between the filled contours.
ec, edgecolor, edgecolors (color-spec, optional) – The color for the contour lines. For contourf plots, lines are added between the filled contours.
a, alpha, alpha (float, optional) – The opacity of the contours.
labels (bool, optional) – Whether to apply labels to contours and grid boxes. The text will be white when the luminance of the underlying filled contour or grid box is less than 50 and black otherwise.
labels_kw (dict-like, optional) – Ignored if labels is False. Extra keyword args for the labels. For contour plots, this is passed to clabel. Otherwise, this is passed to text.
fmt (format-spec, optional) – Passed to the Norm constructor, used to format number labels. You can also use the precision keyword arg.
precision (int, optional) – Maximum number of decimal places for the number labels. Number labels are generated with the SimpleFormatter formatter, which permits limiting the precision.
label (str, optional) – The legend label to be used for this object. In the case of contours, this is paired with the the central artist in the artist list returned by matplotlib.contour.ContourSet.legend_elements.
colorbar (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to matplotlib.axes.Axes.contour.

contourf(x, y, z, **kwargs)[source]¶

Plot filled contours.

Parameters

*args (z or x, y, z) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only z coordinates are passed, try to infer the x and y coordinates from the DataFrame indices and columns or the DataArray coordinates. Otherwise, the y coordinates are np.arange(0, y.shape[0]) and the x coordinates are np.arange(0, y.shape[1]).
- For pcolor and pcolormesh, calculate coordinate edges using edges or edges2d if centers were provided. For all other methods, calculate coordinate centers if edges were provided.
- If the x or y coordinates are pint.Quantity, auto-add the pint unit registry to matplotlib’s unit registry using setup_matplotlib. If the z coordinates are pint.Quantity, pass the magnitude to the plotting command. A pint.Quantity embedded in an xarray.DataArray is also supported.
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.
transpose (bool, optional) – Whether to transpose the input data. This should be used when passing datasets with column-major dimension order (x, y). Otherwise row-major dimension order (y, x) is expected.
order ({{'C', 'F'}}, optional) – Alternative to transpose. 'C' corresponds to the default C-cyle row-major ordering (equivalent to transpose=False). 'F' corresponds to Fortran-style column-major ordering (equivalent to transpose=True).
globe (bool, optional) – For proplot.axes.GeoAxes only. Whether to enforce global coverage. Default is False. When set to True this does the following:
1. Interpolates input data to the North and South poles by setting the data values at the poles to the mean from latitudes nearest each pole.
2. Makes meridional coverage “circular”, i.e. the last longitude coordinate equals the first longitude coordinate plus 360°.
3. When basemap is the backend, cycles 1D longitude vectors to fit within the map edges. For example, if the central longitude is 90°, the data is shifted so that it spans -90° to 270°.

Other Parameters

cmap (colormap-spec, optional) – The colormap specifer, passed to the Colormap constructor function.
cmap_kw (dict-like, optional) – Passed to Colormap.
c, color, colors (color-spec or sequence of color-spec, optional) – The color(s) used to create a DiscreteColormap. If not passed, cmap is used.
norm (norm-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, 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 diverging option also applies DivergingNorm as the default continuous normalizer.
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 sequence of float, 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 that decreasing levels will only work with pcolor plots, not contour plots). Default is rc['cmap.levels'] = 11.
values (int or sequence of float, 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 using edges. This will override any levels input.
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.
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.
lw, linewidth, linewidths (float, optional) – The width of the contour lines. For contourf plots, lines are added between the filled contours.
ls, linestyle, linestyles (str, optional) – The style of the contour lines. For contourf plots, lines are added between the filled contours.
ec, edgecolor, edgecolors (color-spec, optional) – The color for the contour lines. For contourf plots, lines are added between the filled contours.
a, alpha, alpha (float, optional) – The opacity of the contours.edgefix : bool or float, optional Whether to fix the common issue where white lines appear between adjacent patches in saved vector graphics. This can slow down figure rendering. Default is rc.edgefix = True. If True, a small default linewidth is used to cover up the white lines. If float, this linewidth is used.
labels (bool, optional) – Whether to apply labels to contours and grid boxes. The text will be white when the luminance of the underlying filled contour or grid box is less than 50 and black otherwise.
labels_kw (dict-like, optional) – Ignored if labels is False. Extra keyword args for the labels. For contour plots, this is passed to clabel. Otherwise, this is passed to text.
fmt (format-spec, optional) – Passed to the Norm constructor, used to format number labels. You can also use the precision keyword arg.
precision (int, optional) – Maximum number of decimal places for the number labels. Number labels are generated with the SimpleFormatter formatter, which permits limiting the precision.
label (str, optional) – The legend label to be used for this object. In the case of contours, this is paired with the the central artist in the artist list returned by matplotlib.contour.ContourSet.legend_elements.
colorbar (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to matplotlib.axes.Axes.contourf.

fill_between(*args, **kwargs)[source]¶

Plot individual, grouped, or overlaid shading patches.

Parameters

*args (y2 or x, y2, or x, y1, y2) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only y coordinates are passed, try to infer the x coordinates from the Series or DataFrame indices or the DataArray coordinates. Otherwise, the x coordinates are np.arange(0, y2.shape[0]).
- If only x and y2 coordinates are passed, set the y1 coordinates to zero. This draws elements originating from the zero line.
- If both y1 and y2 are provided, draw elements between these points. If either are 2D, draw elements by iterating over each column.
- 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.
stack, stacked (bool, optional) – Whether to “stack” area patches from successive columns of y data or plot area patches on top of each other. Default is False.
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

where (ndarray, optional) – A boolean mask for the points that should be shaded. See this matplotlib example.
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.
lw, linewidth, linewidths (float, optional) – The edge width for the patches.
ls, linestyle, linestyles (str, optional) – The edge style for the patches.
ec, edgecolor, edgecolors (color-spec, optional) – The edge color for the patches.
fc, facecolor, facecolors, fillcolor, fillcolors (color-spec, optional) – The face color for the patches.
a, alpha, alphas (float, optional) – The face opacity for the patches.
negpos (bool, optional) – Whether to shade patches where y2 >= y1 with poscolor and where y2 < y1 with negcolor. Default is False. If True this function will return a 2-tuple of values.
negcolor, poscolor (color-spec, optional) – Colors to use for the negative and positive patches. Ignored if negpos is False. Defaults are rc.negcolor = 'blue7' and rc.poscolor = 'red7'.
edgefix (bool or float, optional) – Whether to fix the common issue where white lines appear between adjacent patches in saved vector graphics. This can slow down figure rendering. Default is rc.edgefix = True. If True, a small default linewidth is used to cover up the white lines. If float, this linewidth is used.
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'].
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 (sequence of float or sequence 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 inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to fill_between.

fill_betweenx(*args, **kwargs)[source]¶

Plot individual, grouped, or overlaid shading patches.

Parameters

*args (x2 or y, x2, or y, x1, x2) – 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, x2.shape[0]).
- If only y and x2 coordinates are passed, set the x1 coordinates to zero. This draws elements originating from the zero line.
- If both x1 and x2 are provided, draw elements between these points. If either are 2D, draw elements by iterating over each column.
- 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.
stack, stacked (bool, optional) – Whether to “stack” area patches from successive columns of x data or plot area patches on top of each other. Default is False.
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

where (ndarray, optional) – A boolean mask for the points that should be shaded. See this matplotlib example.
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.
lw, linewidth, linewidths (float, optional) – The edge width for the patches.
ls, linestyle, linestyles (str, optional) – The edge style for the patches.
ec, edgecolor, edgecolors (color-spec, optional) – The edge color for the patches.
fc, facecolor, facecolors, fillcolor, fillcolors (color-spec, optional) – The face color for the patches.
a, alpha, alphas (float, optional) – The face opacity for the patches.
negpos (bool, optional) – Whether to shade patches where y2 >= y1 with poscolor and where y2 < y1 with negcolor. Default is False. If True this function will return a 2-tuple of values.
negcolor, poscolor (color-spec, optional) – Colors to use for the negative and positive patches. Ignored if negpos is False. Defaults are rc.negcolor = 'blue7' and rc.poscolor = 'red7'.
edgefix (bool or float, optional) – Whether to fix the common issue where white lines appear between adjacent patches in saved vector graphics. This can slow down figure rendering. Default is rc.edgefix = True. If True, a small default linewidth is used to cover up the white lines. If float, this linewidth is used.
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'].
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 (sequence of float or sequence 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 inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to fill_betweenx.

heatmap(*args, aspect=None, **kwargs)[source]¶

Plot grid boxes with formatting suitable for heatmaps. Ensures square grid boxes, adds major ticks to the center of each grid box, disables minor ticks and gridlines, and sets rc['cmap.discrete'] to False by default.

Parameters

*args (z or x, y, z) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only z coordinates are passed, try to infer the x and y coordinates from the DataFrame indices and columns or the DataArray coordinates. Otherwise, the y coordinates are np.arange(0, y.shape[0]) and the x coordinates are np.arange(0, y.shape[1]).
- For pcolor and pcolormesh, calculate coordinate edges using edges or edges2d if centers were provided. For all other methods, calculate coordinate centers if edges were provided.
- If the x or y coordinates are pint.Quantity, auto-add the pint unit registry to matplotlib’s unit registry using setup_matplotlib. If the z coordinates are pint.Quantity, pass the magnitude to the plotting command. A pint.Quantity embedded in an xarray.DataArray is also supported.
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.
transpose (bool, optional) – Whether to transpose the input data. This should be used when passing datasets with column-major dimension order (x, y). Otherwise row-major dimension order (y, x) is expected.
order ({{'C', 'F'}}, optional) – Alternative to transpose. 'C' corresponds to the default C-cyle row-major ordering (equivalent to transpose=False). 'F' corresponds to Fortran-style column-major ordering (equivalent to transpose=True).
globe (bool, optional) – For proplot.axes.GeoAxes only. Whether to enforce global coverage. Default is False. When set to True this does the following:
1. Interpolates input data to the North and South poles by setting the data values at the poles to the mean from latitudes nearest each pole.
2. Makes meridional coverage “circular”, i.e. the last longitude coordinate equals the first longitude coordinate plus 360°.
3. When basemap is the backend, cycles 1D longitude vectors to fit within the map edges. For example, if the central longitude is 90°, the data is shifted so that it spans -90° to 270°.
aspect ({'equal', 'auto'} or float, optional) – Modify the axes aspect ratio. The aspect ratio is of particular relevance for heatmaps since it may lead to non-square grid boxes. This parameter is a shortcut for calling set_aspect. Default is rc['image.aspect'] = 'equal'. The options are as follows:
- Number: The data aspect ratio.
- 'equal': A data aspect ratio of 1.
- 'auto': Allows the data aspect ratio to change depending on the layout. In general this results in non-square grid boxes.

Other Parameters

cmap (colormap-spec, optional) – The colormap specifer, passed to the Colormap constructor function.
cmap_kw (dict-like, optional) – Passed to Colormap.
c, color, colors (color-spec or sequence of color-spec, optional) – The color(s) used to create a DiscreteColormap. If not passed, cmap is used.
norm (norm-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, 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 diverging option also applies DivergingNorm as the default continuous normalizer.
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 sequence of float, 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 that decreasing levels will only work with pcolor plots, not contour plots). Default is rc['cmap.levels'] = 11.
values (int or sequence of float, 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 using edges. This will override any levels input.
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.
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.
lw, linewidth, linewidths (float, optional) – The width of lines between grid boxes.
ls, linestyle, linestyles (str, optional) – The style of lines between grid boxes.
ec, edgecolor, edgecolors (color-spec, optional) – The color for lines between grid boxes.
a, alpha, alphas (float, optional) – The opacity of the grid boxes.
edgefix (bool or float, optional) – Whether to fix the common issue where white lines appear between adjacent patches in saved vector graphics. This can slow down figure rendering. Default is rc.edgefix = True. If True, a small default linewidth is used to cover up the white lines. If float, this linewidth is used.
labels (bool, optional) – Whether to apply labels to contours and grid boxes. The text will be white when the luminance of the underlying filled contour or grid box is less than 50 and black otherwise.
labels_kw (dict-like, optional) – Ignored if labels is False. Extra keyword args for the labels. For contour plots, this is passed to clabel. Otherwise, this is passed to text.
fmt (format-spec, optional) – Passed to the Norm constructor, used to format number labels. You can also use the precision keyword arg.
precision (int, optional) – Maximum number of decimal places for the number labels. Number labels are generated with the SimpleFormatter formatter, which permits limiting the precision.
label (str, optional) – The legend label to be used for this object. In the case of contours, this is paired with the the central artist in the artist list returned by matplotlib.contour.ContourSet.legend_elements.
colorbar (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to matplotlib.axes.Axes.pcolormesh.

hexbin(x, y, weights, **kwargs)[source]¶

Plot a 2D hexagonally binned histogram. standard 2D histogram.

Parameters

*args (y or x, y) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only y coordinates are passed, try to infer the x coordinates from the Series or DataFrame indices or the DataArray coordinates. Otherwise, the x coordinates are np.arange(0, y.shape[0]).
- If the y 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.
weights (array-like, optional) – The weights associated with each point. If string this can be retrieved from data (see below).
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

cmap (colormap-spec, optional) – The colormap specifer, passed to the Colormap constructor function.
cmap_kw (dict-like, optional) – Passed to Colormap.
c, color, colors (color-spec or sequence of color-spec, optional) – The color(s) used to create a DiscreteColormap. If not passed, cmap is used.
norm (norm-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, 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 diverging option also applies DivergingNorm as the default continuous normalizer.
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 sequence of float, 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 that decreasing levels will only work with pcolor plots, not contour plots). Default is rc['cmap.levels'] = 11.
values (int or sequence of float, 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 using edges. This will override any levels input.
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.
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.
labels (bool, optional) – Whether to apply labels to contours and grid boxes. The text will be white when the luminance of the underlying filled contour or grid box is less than 50 and black otherwise.
labels_kw (dict-like, optional) – Ignored if labels is False. Extra keyword args for the labels. For contour plots, this is passed to clabel. Otherwise, this is passed to text.
fmt (format-spec, optional) – Passed to the Norm constructor, used to format number labels. You can also use the precision keyword arg.
precision (int, optional) – Maximum number of decimal places for the number labels. Number labels are generated with the SimpleFormatter formatter, which permits limiting the precision.
label (str, optional) – The legend label to be used for this object. In the case of contours, this is paired with the the central artist in the artist list returned by matplotlib.contour.ContourSet.legend_elements.
colorbar (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to hexbin.

hist(*args, **kwargs)[source]¶

Plot vertical histograms.

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.
bins (int or sequence of float, optional) – The bin count or exact bin edges.
weights (array-like, optional) – The weights associated with each point. If string this can be retrieved from data (see below).
histtype ({'bar', 'barstacked', 'step', 'stepfilled'}, optional) – The histogram type. See matplotlib.axes.Axes.hist for details.
width, rwidth (float, optional) – The bar width(s) for bar-type histograms relative to the bin size. Default is 0.8 for multiple columns of unstacked data and 1 otherwise.
stack, stacked (bool, optional) – Whether to “stack” successive columns of x data for bar-type histograms or show side-by-side in groups. Setting this to False is equivalent to histtype='bar' and to True is equivalent to histtype='barstacked'.
fill, filled (bool, optional) – Whether to “fill” step-type histograms or just plot the edges. Setting this to False is equivalent to histtype='step' and to True is equivalent to histtype='stepfilled'.
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

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.
lw, linewidth, linewidths (float, optional) – The edge width for the patches.
ls, linestyle, linestyles (str, optional) – The edge style for the patches.
ec, edgecolor, edgecolors (color-spec, optional) – The edge color for the patches.
fc, facecolor, facecolors, fillcolor, fillcolors (color-spec, optional) – The face color for the patches.
a, alpha, alphas (float, optional) – The face opacity for the patches.
edgefix (bool or float, optional) – Whether to fix the common issue where white lines appear between adjacent patches in saved vector graphics. This can slow down figure rendering. Default is rc.edgefix = True. If True, a small default linewidth is used to cover up the white lines. If float, this linewidth is used.
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 (sequence of float or sequence 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 inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to hist.

hist2d(x, y, bins, **kwargs)[source]¶

Plot a standard 2D histogram. standard 2D histogram.

Parameters

*args (y or x, y) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only y coordinates are passed, try to infer the x coordinates from the Series or DataFrame indices or the DataArray coordinates. Otherwise, the x coordinates are np.arange(0, y.shape[0]).
- If the y 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.
bins (int or 2-tuple of int, or array-like or 2-tuple of array-like, optional) – The bin count or exact bin edges for each dimension or both dimensions.
weights (array-like, optional) – The weights associated with each point. If string this can be retrieved from data (see below).
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

cmap (colormap-spec, optional) – The colormap specifer, passed to the Colormap constructor function.
cmap_kw (dict-like, optional) – Passed to Colormap.
c, color, colors (color-spec or sequence of color-spec, optional) – The color(s) used to create a DiscreteColormap. If not passed, cmap is used.
norm (norm-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, 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 diverging option also applies DivergingNorm as the default continuous normalizer.
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 sequence of float, 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 that decreasing levels will only work with pcolor plots, not contour plots). Default is rc['cmap.levels'] = 11.
values (int or sequence of float, 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 using edges. This will override any levels input.
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.
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.
labels (bool, optional) – Whether to apply labels to contours and grid boxes. The text will be white when the luminance of the underlying filled contour or grid box is less than 50 and black otherwise.
labels_kw (dict-like, optional) – Ignored if labels is False. Extra keyword args for the labels. For contour plots, this is passed to clabel. Otherwise, this is passed to text.
fmt (format-spec, optional) – Passed to the Norm constructor, used to format number labels. You can also use the precision keyword arg.
precision (int, optional) – Maximum number of decimal places for the number labels. Number labels are generated with the SimpleFormatter formatter, which permits limiting the precision.
label (str, optional) – The legend label to be used for this object. In the case of contours, this is paired with the the central artist in the artist list returned by matplotlib.contour.ContourSet.legend_elements.
colorbar (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to hist2d.

histh(*args, **kwargs)[source]¶

Plot horizontal histograms.

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.
bins (int or sequence of float, optional) – The bin count or exact bin edges.
weights (array-like, optional) – The weights associated with each point. If string this can be retrieved from data (see below).
histtype ({'bar', 'barstacked', 'step', 'stepfilled'}, optional) – The histogram type. See matplotlib.axes.Axes.hist for details.
width, rwidth (float, optional) – The bar width(s) for bar-type histograms relative to the bin size. Default is 0.8 for multiple columns of unstacked data and 1 otherwise.
stack, stacked (bool, optional) – Whether to “stack” successive columns of x data for bar-type histograms or show side-by-side in groups. Setting this to False is equivalent to histtype='bar' and to True is equivalent to histtype='barstacked'.
fill, filled (bool, optional) – Whether to “fill” step-type histograms or just plot the edges. Setting this to False is equivalent to histtype='step' and to True is equivalent to histtype='stepfilled'.
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

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.
lw, linewidth, linewidths (float, optional) – The edge width for the patches.
ls, linestyle, linestyles (str, optional) – The edge style for the patches.
ec, edgecolor, edgecolors (color-spec, optional) – The edge color for the patches.
fc, facecolor, facecolors, fillcolor, fillcolors (color-spec, optional) – The face color for the patches.
a, alpha, alphas (float, optional) – The face opacity for the patches.
edgefix (bool or float, optional) – Whether to fix the common issue where white lines appear between adjacent patches in saved vector graphics. This can slow down figure rendering. Default is rc.edgefix = True. If True, a small default linewidth is used to cover up the white lines. If float, this linewidth is used.
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 (sequence of float or sequence 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 inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to hist.

hlines(*args, **kwargs)[source]¶

Plot horizontal lines.

Parameters

*args (x2 or y, x2, or y, x1, x2) – 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, x2.shape[0]).
- If only y and x2 coordinates are passed, set the x1 coordinates to zero. This draws elements originating from the zero line.
- If both x1 and x2 are provided, draw elements between these points. If either are 2D, draw elements by iterating over each column.
- 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.
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

stack, stacked (bool, optional) – Whether to “stack” lines from successive columns of x data or plot lines on top of each other. Default is False.
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.
lw, linewidth, linewidths (float, optional) – The line width.
ls, linestyle, linestyles (str, optional) – The line style.
c, color, colors (color-spec, optional) – The line color.
a, alpha, alphas (float, optional) – The opacity.
negpos (bool, optional) – Whether to shade lines where ymax >= ymin with poscolor and where ymax < ymin with negcolor. Default is False. If True this function will return a 2-tuple of values.
negcolor, poscolor (color-spec, optional) – Colors to use for the negative and positive lines. Ignored if negpos is False. Defaults are rc.negcolor = 'blue7' and rc.poscolor = 'red7'.
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'].
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 (sequence of float or sequence 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 inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to hlines.

imshow(z, **kwargs)[source]¶

Plot an image.

Parameters

z (array-like) – The data passed as a positional argument or keyword argument.
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

cmap (colormap-spec, optional) – The colormap specifer, passed to the Colormap constructor function.
cmap_kw (dict-like, optional) – Passed to Colormap.
c, color, colors (color-spec or sequence of color-spec, optional) – The color(s) used to create a DiscreteColormap. If not passed, cmap is used.
norm (norm-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, 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 diverging option also applies DivergingNorm as the default continuous normalizer.
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 sequence of float, 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 that decreasing levels will only work with pcolor plots, not contour plots). Default is rc['cmap.levels'] = 11.
values (int or sequence of float, 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 using edges. This will override any levels input.
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.
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.
colorbar (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to matplotlib.axes.Axes.imshow.

line(*args, **kwargs)[source]¶

Plot standard lines.

Parameters

*args (y or x, y) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only y coordinates are passed, try to infer the x coordinates from the Series or DataFrame indices or the DataArray coordinates. Otherwise, the x coordinates are np.arange(0, y.shape[0]).
- If the y 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.
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

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.
lw, linewidth, linewidths (float, optional) – The line width.
ls, linestyle, linestyles (str, optional) – The line style.
c, color, colors (color-spec, optional) – The line color.
a, alpha, alphas (float, optional) – The opacity.
mean, means (bool, optional) – Whether to plot the means of each column for 2D y 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 y 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 (array-like, 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 boxstds 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'].
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 (sequence of float or sequence 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 inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to plot.

linex(*args, **kwargs)[source]¶

Plot standard lines.

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.
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

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.
lw, linewidth, linewidths (float, optional) – The line width.
ls, linestyle, linestyles (str, optional) – The line style.
c, color, colors (color-spec, optional) – The line color.
a, alpha, alphas (float, optional) – The opacity.
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 (array-like, 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 boxstds 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'].
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 (sequence of float or sequence 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 inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to plot.

matshow(z, **kwargs)[source]¶

Plot a matrix.

Parameters

z (array-like) – The data passed as a positional argument or keyword argument.
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

cmap (colormap-spec, optional) – The colormap specifer, passed to the Colormap constructor function.
cmap_kw (dict-like, optional) – Passed to Colormap.
c, color, colors (color-spec or sequence of color-spec, optional) – The color(s) used to create a DiscreteColormap. If not passed, cmap is used.
norm (norm-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, 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 diverging option also applies DivergingNorm as the default continuous normalizer.
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 sequence of float, 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 that decreasing levels will only work with pcolor plots, not contour plots). Default is rc['cmap.levels'] = 11.
values (int or sequence of float, 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 using edges. This will override any levels input.
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.
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.
colorbar (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to matplotlib.axes.Axes.matshow.

parametric(x, y, c, *, interp=0, scalex=True, scaley=True, **kwargs)[source]¶

Plot a parametric line.

Parameters

*args (y or x, y) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only y coordinates are passed, try to infer the x coordinates from the Series or DataFrame indices or the DataArray coordinates. Otherwise, the x coordinates are np.arange(0, y.shape[0]).
- If the y 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.
c, color, colors, values (array-like, optional) – The parametric coordinate. These can be passed as a third positional argument or as a keyword argument. They can also be string labels instead of numbers and the resulting colorbar ticks will be labeled accordingly.
interp (int, optional) – Interpolate to this many additional points between the parametric coordinates. Default is 0. This can be increased to make the color gradations between a small number of coordinates appear “smooth”.
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

cmap (colormap-spec, optional) – The colormap specifer, passed to the Colormap constructor function.
cmap_kw (dict-like, optional) – Passed to Colormap.
c, color, colors (color-spec or sequence of color-spec, optional) – The color(s) used to create a DiscreteColormap. If not passed, cmap is used.
norm (norm-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, 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 diverging option also applies DivergingNorm as the default continuous normalizer.
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.
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.
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'].
scalex, scaley (bool, optional) – Whether the view limits are adapted to the data limits. The values are passed on to autoscale_view.
colorbar (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Valid LineCollection properties.

Returns

LineCollection – The parametric line. See this matplotlib example.

pcolor(x, y, z, **kwargs)[source]¶

Plot irregular grid boxes.

Parameters

*args (z or x, y, z) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only z coordinates are passed, try to infer the x and y coordinates from the DataFrame indices and columns or the DataArray coordinates. Otherwise, the y coordinates are np.arange(0, y.shape[0]) and the x coordinates are np.arange(0, y.shape[1]).
- For pcolor and pcolormesh, calculate coordinate edges using edges or edges2d if centers were provided. For all other methods, calculate coordinate centers if edges were provided.
- If the x or y coordinates are pint.Quantity, auto-add the pint unit registry to matplotlib’s unit registry using setup_matplotlib. If the z coordinates are pint.Quantity, pass the magnitude to the plotting command. A pint.Quantity embedded in an xarray.DataArray is also supported.
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.
transpose (bool, optional) – Whether to transpose the input data. This should be used when passing datasets with column-major dimension order (x, y). Otherwise row-major dimension order (y, x) is expected.
order ({{'C', 'F'}}, optional) – Alternative to transpose. 'C' corresponds to the default C-cyle row-major ordering (equivalent to transpose=False). 'F' corresponds to Fortran-style column-major ordering (equivalent to transpose=True).
globe (bool, optional) – For proplot.axes.GeoAxes only. Whether to enforce global coverage. Default is False. When set to True this does the following:
1. Interpolates input data to the North and South poles by setting the data values at the poles to the mean from latitudes nearest each pole.
2. Makes meridional coverage “circular”, i.e. the last longitude coordinate equals the first longitude coordinate plus 360°.
3. When basemap is the backend, cycles 1D longitude vectors to fit within the map edges. For example, if the central longitude is 90°, the data is shifted so that it spans -90° to 270°.

Other Parameters

cmap (colormap-spec, optional) – The colormap specifer, passed to the Colormap constructor function.
cmap_kw (dict-like, optional) – Passed to Colormap.
c, color, colors (color-spec or sequence of color-spec, optional) – The color(s) used to create a DiscreteColormap. If not passed, cmap is used.
norm (norm-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, 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 diverging option also applies DivergingNorm as the default continuous normalizer.
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 sequence of float, 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 that decreasing levels will only work with pcolor plots, not contour plots). Default is rc['cmap.levels'] = 11.
values (int or sequence of float, 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 using edges. This will override any levels input.
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.
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.
lw, linewidth, linewidths (float, optional) – The width of lines between grid boxes.
ls, linestyle, linestyles (str, optional) – The style of lines between grid boxes.
ec, edgecolor, edgecolors (color-spec, optional) – The color for lines between grid boxes.
a, alpha, alphas (float, optional) – The opacity of the grid boxes.
edgefix (bool or float, optional) – Whether to fix the common issue where white lines appear between adjacent patches in saved vector graphics. This can slow down figure rendering. Default is rc.edgefix = True. If True, a small default linewidth is used to cover up the white lines. If float, this linewidth is used.
labels (bool, optional) – Whether to apply labels to contours and grid boxes. The text will be white when the luminance of the underlying filled contour or grid box is less than 50 and black otherwise.
labels_kw (dict-like, optional) – Ignored if labels is False. Extra keyword args for the labels. For contour plots, this is passed to clabel. Otherwise, this is passed to text.
fmt (format-spec, optional) – Passed to the Norm constructor, used to format number labels. You can also use the precision keyword arg.
precision (int, optional) – Maximum number of decimal places for the number labels. Number labels are generated with the SimpleFormatter formatter, which permits limiting the precision.
label (str, optional) – The legend label to be used for this object. In the case of contours, this is paired with the the central artist in the artist list returned by matplotlib.contour.ContourSet.legend_elements.
colorbar (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to matplotlib.axes.Axes.pcolor.

pcolorfast(x, y, z, **kwargs)[source]¶

Plot grid boxes quickly.

Parameters

*args (z or x, y, z) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only z coordinates are passed, try to infer the x and y coordinates from the DataFrame indices and columns or the DataArray coordinates. Otherwise, the y coordinates are np.arange(0, y.shape[0]) and the x coordinates are np.arange(0, y.shape[1]).
- For pcolor and pcolormesh, calculate coordinate edges using edges or edges2d if centers were provided. For all other methods, calculate coordinate centers if edges were provided.
- If the x or y coordinates are pint.Quantity, auto-add the pint unit registry to matplotlib’s unit registry using setup_matplotlib. If the z coordinates are pint.Quantity, pass the magnitude to the plotting command. A pint.Quantity embedded in an xarray.DataArray is also supported.
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.
transpose (bool, optional) – Whether to transpose the input data. This should be used when passing datasets with column-major dimension order (x, y). Otherwise row-major dimension order (y, x) is expected.
order ({{'C', 'F'}}, optional) – Alternative to transpose. 'C' corresponds to the default C-cyle row-major ordering (equivalent to transpose=False). 'F' corresponds to Fortran-style column-major ordering (equivalent to transpose=True).
globe (bool, optional) – For proplot.axes.GeoAxes only. Whether to enforce global coverage. Default is False. When set to True this does the following:
1. Interpolates input data to the North and South poles by setting the data values at the poles to the mean from latitudes nearest each pole.
2. Makes meridional coverage “circular”, i.e. the last longitude coordinate equals the first longitude coordinate plus 360°.
3. When basemap is the backend, cycles 1D longitude vectors to fit within the map edges. For example, if the central longitude is 90°, the data is shifted so that it spans -90° to 270°.

Other Parameters

cmap (colormap-spec, optional) – The colormap specifer, passed to the Colormap constructor function.
cmap_kw (dict-like, optional) – Passed to Colormap.
c, color, colors (color-spec or sequence of color-spec, optional) – The color(s) used to create a DiscreteColormap. If not passed, cmap is used.
norm (norm-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, 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 diverging option also applies DivergingNorm as the default continuous normalizer.
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 sequence of float, 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 that decreasing levels will only work with pcolor plots, not contour plots). Default is rc['cmap.levels'] = 11.
values (int or sequence of float, 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 using edges. This will override any levels input.
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.
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.
lw, linewidth, linewidths (float, optional) – The width of lines between grid boxes.
ls, linestyle, linestyles (str, optional) – The style of lines between grid boxes.
ec, edgecolor, edgecolors (color-spec, optional) – The color for lines between grid boxes.
a, alpha, alphas (float, optional) – The opacity of the grid boxes.
edgefix (bool or float, optional) – Whether to fix the common issue where white lines appear between adjacent patches in saved vector graphics. This can slow down figure rendering. Default is rc.edgefix = True. If True, a small default linewidth is used to cover up the white lines. If float, this linewidth is used.
labels (bool, optional) – Whether to apply labels to contours and grid boxes. The text will be white when the luminance of the underlying filled contour or grid box is less than 50 and black otherwise.
labels_kw (dict-like, optional) – Ignored if labels is False. Extra keyword args for the labels. For contour plots, this is passed to clabel. Otherwise, this is passed to text.
fmt (format-spec, optional) – Passed to the Norm constructor, used to format number labels. You can also use the precision keyword arg.
precision (int, optional) – Maximum number of decimal places for the number labels. Number labels are generated with the SimpleFormatter formatter, which permits limiting the precision.
label (str, optional) – The legend label to be used for this object. In the case of contours, this is paired with the the central artist in the artist list returned by matplotlib.contour.ContourSet.legend_elements.
colorbar (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to matplotlib.axes.Axes.pcolorfast.

pcolormesh(x, y, z, **kwargs)[source]¶

Plot regular grid boxes.

Parameters

*args (z or x, y, z) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only z coordinates are passed, try to infer the x and y coordinates from the DataFrame indices and columns or the DataArray coordinates. Otherwise, the y coordinates are np.arange(0, y.shape[0]) and the x coordinates are np.arange(0, y.shape[1]).
- For pcolor and pcolormesh, calculate coordinate edges using edges or edges2d if centers were provided. For all other methods, calculate coordinate centers if edges were provided.
- If the x or y coordinates are pint.Quantity, auto-add the pint unit registry to matplotlib’s unit registry using setup_matplotlib. If the z coordinates are pint.Quantity, pass the magnitude to the plotting command. A pint.Quantity embedded in an xarray.DataArray is also supported.
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.
transpose (bool, optional) – Whether to transpose the input data. This should be used when passing datasets with column-major dimension order (x, y). Otherwise row-major dimension order (y, x) is expected.
order ({{'C', 'F'}}, optional) – Alternative to transpose. 'C' corresponds to the default C-cyle row-major ordering (equivalent to transpose=False). 'F' corresponds to Fortran-style column-major ordering (equivalent to transpose=True).
globe (bool, optional) – For proplot.axes.GeoAxes only. Whether to enforce global coverage. Default is False. When set to True this does the following:
1. Interpolates input data to the North and South poles by setting the data values at the poles to the mean from latitudes nearest each pole.
2. Makes meridional coverage “circular”, i.e. the last longitude coordinate equals the first longitude coordinate plus 360°.
3. When basemap is the backend, cycles 1D longitude vectors to fit within the map edges. For example, if the central longitude is 90°, the data is shifted so that it spans -90° to 270°.

Other Parameters

cmap (colormap-spec, optional) – The colormap specifer, passed to the Colormap constructor function.
cmap_kw (dict-like, optional) – Passed to Colormap.
c, color, colors (color-spec or sequence of color-spec, optional) – The color(s) used to create a DiscreteColormap. If not passed, cmap is used.
norm (norm-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, 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 diverging option also applies DivergingNorm as the default continuous normalizer.
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 sequence of float, 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 that decreasing levels will only work with pcolor plots, not contour plots). Default is rc['cmap.levels'] = 11.
values (int or sequence of float, 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 using edges. This will override any levels input.
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.
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.
lw, linewidth, linewidths (float, optional) – The width of lines between grid boxes.
ls, linestyle, linestyles (str, optional) – The style of lines between grid boxes.
ec, edgecolor, edgecolors (color-spec, optional) – The color for lines between grid boxes.
a, alpha, alphas (float, optional) – The opacity of the grid boxes.
edgefix (bool or float, optional) – Whether to fix the common issue where white lines appear between adjacent patches in saved vector graphics. This can slow down figure rendering. Default is rc.edgefix = True. If True, a small default linewidth is used to cover up the white lines. If float, this linewidth is used.
labels (bool, optional) – Whether to apply labels to contours and grid boxes. The text will be white when the luminance of the underlying filled contour or grid box is less than 50 and black otherwise.
labels_kw (dict-like, optional) – Ignored if labels is False. Extra keyword args for the labels. For contour plots, this is passed to clabel. Otherwise, this is passed to text.
fmt (format-spec, optional) – Passed to the Norm constructor, used to format number labels. You can also use the precision keyword arg.
precision (int, optional) – Maximum number of decimal places for the number labels. Number labels are generated with the SimpleFormatter formatter, which permits limiting the precision.
label (str, optional) – The legend label to be used for this object. In the case of contours, this is paired with the the central artist in the artist list returned by matplotlib.contour.ContourSet.legend_elements.
colorbar (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to matplotlib.axes.Axes.pcolormesh.

pie(x, explode, *, labelpad=None, labeldistance=None, **kwargs)[source]¶

Plot a pie chart.

Parameters

*args (y or x, y) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only y coordinates are passed, try to infer the x coordinates from the Series or DataFrame indices or the DataArray coordinates. Otherwise, the x coordinates are np.arange(0, y.shape[0]).
- If the y 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.
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

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.
lw, linewidth, linewidths (float, optional) – The edge width for the patches.
ls, linestyle, linestyles (str, optional) – The edge style for the patches.
ec, edgecolor, edgecolors (color-spec, optional) – The edge color for the patches.
fc, facecolor, facecolors, fillcolor, fillcolors (color-spec, optional) – The face color for the patches.
a, alpha, alphas (float, optional) – The face opacity for the patches.
edgefix (bool or float, optional) – Whether to fix the common issue where white lines appear between adjacent patches in saved vector graphics. This can slow down figure rendering. Default is rc.edgefix = True. If True, a small default linewidth is used to cover up the white lines. If float, this linewidth is used.
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 (sequence of float or sequence 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.
labelpad, labeldistance (float, optional) – The distance at which labels are drawn in radial coordinates.

See also

matplotlib.axes.Axes.pie

plot(*args, **kwargs)[source]¶

Plot standard lines.

Parameters

*args (y or x, y) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only y coordinates are passed, try to infer the x coordinates from the Series or DataFrame indices or the DataArray coordinates. Otherwise, the x coordinates are np.arange(0, y.shape[0]).
- If the y 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.
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

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.
lw, linewidth, linewidths (float, optional) – The line width.
ls, linestyle, linestyles (str, optional) – The line style.
c, color, colors (color-spec, optional) – The line color.
a, alpha, alphas (float, optional) – The opacity.
mean, means (bool, optional) – Whether to plot the means of each column for 2D y 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 y 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 (array-like, 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 boxstds 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'].
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 (sequence of float or sequence 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 inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to plot.

plotx(*args, **kwargs)[source]¶

Plot standard lines.

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.
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

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.
lw, linewidth, linewidths (float, optional) – The line width.
ls, linestyle, linestyles (str, optional) – The line style.
c, color, colors (color-spec, optional) – The line color.
a, alpha, alphas (float, optional) – The opacity.
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 (array-like, 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 boxstds 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'].
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 (sequence of float or sequence 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 inner or outer colorbar from the resulting object(s). If True, the default rc['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 in colorbar.
colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.
legend (bool, int, or str, optional) – Location specifying where to draw an inner or outer legend from the resulting object(s). If True, the default rc['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 in legend.
legend_kw (dict-like, optional) – Extra keyword args for the call to legend.
**kwargs – Passed to plot.

quiver(x, y, u, v, c, **kwargs)[source]¶

Plot quiver arrows.

Parameters

*args (u, v or x, y, u, v) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only u and v coordinates are passed, try to infer the x and y coordinates from the DataFrame indices and columns or the DataArray coordinates. Otherwise, the y coordinates are np.arange(0, y.shape[0]) and the x coordinates are np.arange(0, y.shape[1]).
- For pcolor and pcolormesh, calculate coordinate edges using edges or edges2d if centers were provided. For all other methods, calculate coordinate centers if edges were provided.
- If the x or y coordinates are pint.Quantity, auto-add the pint unit registry to matplotlib’s unit registry using setup_matplotlib. If the u and v coordinates are pint.Quantity, pass the magnitude to the plotting command. A pint.Quantity embedded in an xarray.DataArray is also supported.
c, color, colors (array-like or color-spec, optional) – The colors of the quiver arrows passed as either a keyword argument or a fifth positional argument. This can be a single color or a color array to be scaled by cmap and norm.
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.
transpose (bool, optional) – Whether to transpose the input data. This should be used when passing datasets with column-major dimension order (x, y). Otherwise row-major dimension order (y, x) is expected.
order ({{'C', 'F'}}, optional) – Alternative to transpose. 'C' corresponds to the default C-cyle row-major ordering (equivalent to transpose=False). 'F' corresponds to Fortran-style column-major ordering (equivalent to transpose=True).
globe (bool, optional) – For proplot.axes.GeoAxes only. Whether to enforce global coverage. Default is False. When set to True this does the following:
1. Interpolates input data to the North and South poles by setting the data values at the poles to the mean from latitudes nearest each pole.
2. Makes meridional coverage “circular”, i.e. the last longitude coordinate equals the first longitude coordinate plus 360°.
3. When basemap is the backend, cycles 1D longitude vectors to fit within the map edges. For example, if the central longitude is 90°, the data is shifted so that it spans -90° to 270°.

Other Parameters

cmap (colormap-spec, optional) – The colormap specifer, passed to the Colormap constructor function.
cmap_kw (dict-like, optional) – Passed to Colormap.
c, color, colors (color-spec or sequence of color-spec, optional) – The color(s) used to create a DiscreteColormap. If not passed, cmap is used.
norm (norm-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, 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 diverging option also applies DivergingNorm as the default continuous normalizer.
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 sequence of float, 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 that decreasing levels will only work with pcolor plots, not contour plots). Default is rc['cmap.levels'] = 11.
values (int or sequence of float, 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 using edges. This will override any levels input.
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.
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.
**kwargs – Passed to matplotlib.axes.Axes.quiver

scatter(*args, **kwargs)[source]¶

Plot markers with flexible keyword arguments.

Parameters

*args (y or x, y) – The data passed as positional or keyword arguments. Interpreted as follows:
- If only y coordinates are passed, try to infer the x coordinates from the Series or DataFrame indices or the DataArray coordinates. Otherwise, the x coordinates are np.arange(0, y.shape[0]).
- If the y 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 sequence 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, fc, facecolor, facecolors (array-like or color-spec, optional) – The marker 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

cmap (colormap-spec, optional) – The colormap specifer, passed to the Colormap constructor function.
cmap_kw (dict-like, optional) – Passed to Colormap.
c, color, colors (color-spec or sequence of color-spec, optional) – The color(s) used to create a DiscreteColormap. If not passed, cmap is used.
norm (norm-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, 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 diverging option also applies DivergingNorm as the default continuous normalizer.
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 sequence of float, 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 that decreasing levels will only work with pcolor plots, not contour plots). Default is rc['cmap.levels'] = 11.
values (int or sequence of float, 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 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.
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 2D y 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 y 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,