neulab/docprompting-conala huggingface dataset:
matplotlib.axes.Axes.set_axes_locator   Axes.set_axes_locator(locator)[source]
 
Set the Axes locator.  Parameters 
 
locatorCallable[[Axes, Renderer], Bbox]

   
  Examples using matplotlib.axes.Axes.set_axes_locator
 
   HBoxDivider demo
matplotlib.axes.Axes.set_axis_off   Axes.set_axis_off()[source]
 
Turn the x- and y-axis off. This affects the axis lines, ticks, ticklabels, grid and axis labels. 
  Examples using matplotlib.axes.Axes.set_axis_off
 
   Marker reference   

   Barcode   

   Blend transparency with color in 2D images   

   Nested pie charts   

   Annotation arrow style reference   

   Precise text layout   

   Drawing fancy boxes   

   Choosing Colormaps in Matplotlib   

   Text properties and layout
matplotlib.axes.Axes.set_axis_on   Axes.set_axis_on()[source]
 
Turn the x- and y-axis on. This affects the axis lines, ticks, ticklabels, grid and axis labels.
matplotlib.axes.Axes.set_axisbelow   Axes.set_axisbelow(b)[source]
 
Set whether axis ticks and gridlines are above or below most artists. This controls the zorder of the ticks and gridlines. For more information on the zorder see Zorder Demo.  Parameters 
 
bbool or 'line'


Possible values:  
True (zorder = 0.5): Ticks and gridlines are below all Artists. 'line' (zorder = 1.5): Ticks and gridlines are above patches (e.g. rectangles, with default zorder = 1) but still below lines and markers (with their default zorder = 2). 
False (zorder = 2.5): Ticks and gridlines are above patches and lines / markers.       See also  get_axisbelow
matplotlib.axes.Axes.set_box_aspect   Axes.set_box_aspect(aspect=None)[source]
 
Set the Axes box aspect, i.e. the ratio of height to width. This defines the aspect of the Axes in figure space and is not to be confused with the data aspect (see set_aspect).  Parameters 
 
aspectfloat or None


Changes the physical dimensions of the Axes, such that the ratio of the Axes height to the Axes width in physical units is equal to aspect. Defining a box aspect will change the adjustable property to 'datalim' (see set_adjustable). None will disable a fixed box aspect so that height and width of the Axes are chosen independently.      See also  matplotlib.axes.Axes.set_aspect

for a description of aspect handling.    
  Examples using matplotlib.axes.Axes.set_box_aspect
 
   Axes box aspect
matplotlib.axes.Axes.set_facecolor   Axes.set_facecolor(color)[source]
 
Set the facecolor of the Axes.  Parameters 
 
colorcolor

   
  Examples using matplotlib.axes.Axes.set_facecolor
 
   Color Demo
matplotlib.axes.Axes.set_frame_on   Axes.set_frame_on(b)[source]
 
Set whether the Axes rectangle patch is drawn.  Parameters 
 
bbool
matplotlib.axes.Axes.set_navigate   Axes.set_navigate(b)[source]
 
Set whether the Axes responds to navigation toolbar commands.  Parameters 
 
bbool
matplotlib.axes.Axes.set_navigate_mode   Axes.set_navigate_mode(b)[source]
 
Set the navigation toolbar button status.  Warning this is not a user-API function.
matplotlib.axes.Axes.set_position   Axes.set_position(pos, which='both')[source]
 
Set the Axes position. Axes have two position attributes. The 'original' position is the position allocated for the Axes. The 'active' position is the position the Axes is actually drawn at. These positions are usually the same unless a fixed aspect is set to the Axes. See Axes.set_aspect for details.  Parameters 
 
pos[left, bottom, width, height] or Bbox


The new position of the in Figure coordinates.  
which{'both', 'active', 'original'}, default: 'both'


Determines which position variables to change.      See also  matplotlib.transforms.Bbox.from_bounds
matplotlib.transforms.Bbox.from_extents
  
  Examples using matplotlib.axes.Axes.set_position
 
   Contour Demo
matplotlib.axes.Axes.set_prop_cycle   Axes.set_prop_cycle(*args, **kwargs)[source]
 
Set the property cycle of the Axes. The property cycle controls the style properties such as color, marker and linestyle of future plot commands. The style properties of data already added to the Axes are not modified. Call signatures: set_prop_cycle(cycler)
set_prop_cycle(label=values[, label2=values2[, ...]])
set_prop_cycle(label, values)
 Form 1 sets given Cycler object. Form 2 creates a Cycler which cycles over one or more properties simultaneously and set it as the property cycle of the Axes. If multiple properties are given, their value lists must have the same length. This is just a shortcut for explicitly creating a cycler and passing it to the function, i.e. it's short for set_prop_cycle(cycler(label=values label2=values2, ...)). Form 3 creates a Cycler for a single property and set it as the property cycle of the Axes. This form exists for compatibility with the original cycler.cycler interface. Its use is discouraged in favor of the kwarg form, i.e. set_prop_cycle(label=values).  Parameters 
 
cyclerCycler


Set the given Cycler. None resets to the cycle defined by the current style.  
labelstr


The property key. Must be a valid Artist property. For example, 'color' or 'linestyle'. Aliases are allowed, such as 'c' for 'color' and 'lw' for 'linewidth'.  
valuesiterable


Finite-length iterable of the property values. These values are validated and will raise a ValueError if invalid.      See also  matplotlib.rcsetup.cycler

Convenience function for creating validated cyclers for properties.  cycler.cycler

The original function for creating unvalidated cyclers.    Examples Setting the property cycle for a single property: >>> ax.set_prop_cycle(color=['red', 'green', 'blue'])
 Setting the property cycle for simultaneously cycling over multiple properties (e.g. red circle, green plus, blue cross): >>> ax.set_prop_cycle(color=['red', 'green', 'blue'],
...                   marker=['o', '+', 'x'])
 
  Examples using matplotlib.axes.Axes.set_prop_cycle
 
   Bachelor's degrees by gender   

   Styling with cycler
matplotlib.axes.Axes.set_rasterization_zorder   Axes.set_rasterization_zorder(z)[source]
 
Set the zorder threshold for rasterization for vector graphics output. All artists with a zorder below the given value will be rasterized if they support rasterization. This setting is ignored for pixel-based output. See also Rasterization for vector graphics.  Parameters 
 
zfloat or None


The zorder below which artists are rasterized. If None rasterization based on zorder is deactivated.     
  Examples using matplotlib.axes.Axes.set_rasterization_zorder
 
   Rasterization for vector graphics
matplotlib.axes.Axes.set_xbound   Axes.set_xbound(lower=None, upper=None)[source]
 
Set the lower and upper numerical bounds of the x-axis. This method will honor axis inversion regardless of parameter order. It will not change the autoscaling setting (get_autoscalex_on()).  Parameters 
 
lower, upperfloat or None


The lower and upper bounds. If None, the respective axis bound is not modified.      See also  get_xbound

get_xlim, set_xlim


invert_xaxis, xaxis_inverted
matplotlib.axes.Axes.set_xlabel   Axes.set_xlabel(xlabel, fontdict=None, labelpad=None, *, loc=None, **kwargs)[source]
 
Set the label for the x-axis.  Parameters 
 
xlabelstr


The label text.  
labelpadfloat, default: rcParams["axes.labelpad"] (default: 4.0)


Spacing in points from the Axes bounding box including ticks and tick labels. If None, the previous value is left as is.  
loc{'left', 'center', 'right'}, default: rcParams["xaxis.labellocation"] (default: 'center')


The label position. This is a high-level alternative for passing parameters x and horizontalalignment.    Other Parameters 
 
**kwargsText properties


Text properties control the appearance of the label.      See also  text

Documents the properties supported by Text.    
  Examples using matplotlib.axes.Axes.set_xlabel
 
   Bar Label Demo   

   Horizontal bar chart   

   Broken Barh   

   CSD Demo   

   Fill Between and Alpha   

   Filling the area between lines   

   Fill Betweenx Demo   

   Hatch-filled histograms   

   Hat graph   

   Psd Demo   

   Scatter Demo2   

   Stackplots and streamgraphs   

   hlines and vlines   

   Contourf Demo   

   Tricontour Demo   

   Tripcolor Demo   

   Triplot Demo   

   Aligning Labels   

   Axes Demo   

   Axis Label Position   

   Resizing axes with constrained layout   

   Resizing axes with tight layout   

   Figure labels: suptitle, supxlabel, supylabel   

   Invert Axes   

   Secondary Axis   

   Figure subfigures   

   Multiple subplots   

   Plots with different scales   

   Box plots with custom fill colors   

   Boxplots   

   Box plot vs. violin plot comparison   

   Violin plot customization   

   Using histograms to plot a cumulative distribution   

   Some features of the histogram (hist) function   

   Producing multiple histograms side by side   

   Using accented text in matplotlib   

   Labeling ticks using engineering notation   

   Using a ttf font file in Matplotlib   

   Legend Demo   

   Mathtext   

   Multiline   

   Rendering math equations using TeX   

   Title positioning   

   Simple axes labels   

   Text Commands   

   Color Demo   

   Line, Poly and RegularPoly Collection with autoscaling   

   Ellipse Collection   

   Dark background style sheet   

   Make Room For Ylabel Using Axesgrid   

   Parasite Simple   

   Parasite Axes demo   

   Parasite axis demo   

   Ticklabel alignment   

   Simple Axis Direction03   

   Simple Axisline   

   Anatomy of a figure   

   XKCD   

   Keypress event   

   Pythonic Matplotlib   

   Plot 2D data on 3D plot   

   Create 2D bar graphs in different planes   

   3D errorbars   

   Lorenz Attractor   

   Automatic Text Offsetting   

   3D scatterplot   

   3D surface with polar coordinates   

   Text annotations in 3D   

   Log Bar   

   MRI With EEG   

   Multiple Yaxis With Spines   

   Centering labels between ticks   

   Pgf Fonts   

   Pgf Texsystem   

   Slider   

   Basic Usage   

   Artist tutorial   

   Constrained Layout Guide   

   Tight Layout guide   

   Arranging multiple Axes in a Figure   

   Choosing Colormaps in Matplotlib   

   Text in Matplotlib Plots
matplotlib.axes.Axes.set_xmargin   Axes.set_xmargin(m)[source]
 
Set padding of X data limits prior to autoscaling. m times the data interval will be added to each end of that interval before it is used in autoscaling. For example, if your data is in the range [0, 2], a factor of m = 0.1 will result in a range [-0.2, 2.2]. Negative values -0.5 < m < 0 will result in clipping of the data range. I.e. for a data range [0, 2], a factor of m = -0.1 will result in a range [0.2, 1.8].  Parameters 
 
mfloat greater than -0.5

   
  Examples using matplotlib.axes.Axes.set_xmargin
 
   Automatically setting tick positions
matplotlib.axes.Axes.set_xscale   Axes.set_xscale(value, **kwargs)[source]
 
Set the x-axis scale.  Parameters 
 
value{"linear", "log", "symlog", "logit", ...} or ScaleBase


The axis scale type to apply.  **kwargs

Different keyword arguments are accepted, depending on the scale. See the respective class keyword arguments:  matplotlib.scale.LinearScale matplotlib.scale.LogScale matplotlib.scale.SymmetricalLogScale matplotlib.scale.LogitScale matplotlib.scale.FuncScale      Notes By default, Matplotlib supports the above mentioned scales. Additionally, custom scales may be registered using matplotlib.scale.register_scale. These scales can then also be used here. 
  Examples using matplotlib.axes.Axes.set_xscale
 
   Markevery Demo   

   Labeling ticks using engineering notation   

   Inset Locator Demo   

   Loglog Aspect   

   Log Demo   

   Symlog Demo   

   Transformations Tutorial
matplotlib.axes.Axes.set_xticklabels   Axes.set_xticklabels(labels, *, fontdict=None, minor=False, **kwargs)[source]
 
Set the xaxis' labels with list of string labels.  Warning This method should only be used after fixing the tick positions using Axes.set_xticks. Otherwise, the labels may end up in unexpected positions.   Parameters 
 
labelslist of str


The label texts.  
fontdictdict, optional


A dictionary controlling the appearance of the ticklabels. The default fontdict is: {'fontsize': rcParams['axes.titlesize'],
 'fontweight': rcParams['axes.titleweight'],
 'verticalalignment': 'baseline',
 'horizontalalignment': loc}
  
minorbool, default: False


Whether to set the minor ticklabels rather than the major ones.    Returns 
 list of Text


The labels.    Other Parameters 
 
**kwargsText properties.

   
  Examples using matplotlib.axes.Axes.set_xticklabels
 
   Managing multiple figures in pyplot   

   Zoom region inset axes   

   Boxplots   

   Rendering math equations using TeX   

   XKCD   

   Colorbar Tick Labelling   

   Constrained Layout Guide
matplotlib.axes.Axes.set_xticks   Axes.set_xticks(ticks, labels=None, *, minor=False, **kwargs)[source]
 
Set the xaxis' tick locations and optionally labels. If necessary, the view limits of the Axis are expanded so that all given ticks are visible.  Parameters 
 
tickslist of floats


List of tick locations.  
labelslist of str, optional


List of tick labels. If not set, the labels show the data value.  
minorbool, default: False


If False, set the major ticks; if True, the minor ticks.  **kwargs

Text properties for the labels. These take effect only if you pass labels. In other cases, please use tick_params.     Notes The mandatory expansion of the view limits is an intentional design choice to prevent the surprise of a non-visible tick. If you need other limits, you should set the limits explicitly after setting the ticks. 
  Examples using matplotlib.axes.Axes.set_xticks
 
   Bar Label Demo   

   Grouped bar chart with labels   

   Hat graph   

   Psd Demo   

   Creating annotated heatmaps   

   Box plot vs. violin plot comparison   

   Violin plot customization   

   Producing multiple histograms side by side   

   Multiline   

   Rendering math equations using TeX   

   ggplot style sheet   

   Scatter Histogram (Locatable Axes)   

   Simple Axisline4   

   Ticklabel alignment   

   Ticklabel direction   

   Bachelor's degrees by gender   

   Integral as the area under a curve   

   Shaded & power normalized rendering   

   XKCD   

   Rain simulation   

   MATPLOTLIB UNCHAINED   

   Frontpage 3D example   

   Frontpage contour example   

   Frontpage histogram example   

   Frontpage plot example   

   Log Bar   

   MRI With EEG   

   Custom spine bounds   

   Group barchart with units   

   The Lifecycle of a Plot
matplotlib.axes.Axes.set_ybound   Axes.set_ybound(lower=None, upper=None)[source]
 
Set the lower and upper numerical bounds of the y-axis. This method will honor axis inversion regardless of parameter order. It will not change the autoscaling setting (get_autoscaley_on()).  Parameters 
 
lower, upperfloat or None


The lower and upper bounds. If None, the respective axis bound is not modified.      See also  get_ybound

get_ylim, set_ylim


invert_yaxis, yaxis_inverted
matplotlib.axes.Axes.set_ylabel   Axes.set_ylabel(ylabel, fontdict=None, labelpad=None, *, loc=None, **kwargs)[source]
 
Set the label for the y-axis.  Parameters 
 
ylabelstr


The label text.  
labelpadfloat, default: rcParams["axes.labelpad"] (default: 4.0)


Spacing in points from the Axes bounding box including ticks and tick labels. If None, the previous value is left as is.  
loc{'bottom', 'center', 'top'}, default: rcParams["yaxis.labellocation"] (default: 'center')


The label position. This is a high-level alternative for passing parameters y and horizontalalignment.    Other Parameters 
 
**kwargsText properties


Text properties control the appearance of the label.      See also  text

Documents the properties supported by Text.    
  Examples using matplotlib.axes.Axes.set_ylabel
 
   Bar Label Demo   

   Stacked bar chart   

   Grouped bar chart with labels   

   CSD Demo   

   Fill Between and Alpha   

   Hatch-filled histograms   

   Hat graph   

   Psd Demo   

   Scatter Demo2   

   Stackplots and streamgraphs   

   Contourf Demo   

   Creating annotated heatmaps   

   Tricontour Demo   

   Tripcolor Demo   

   Triplot Demo   

   Aligning Labels   

   Axes Demo   

   Axis Label Position   

   Resizing axes with constrained layout   

   Resizing axes with tight layout   

   Figure labels: suptitle, supxlabel, supylabel   

   Invert Axes   

   Secondary Axis   

   Figure subfigures   

   Multiple subplots   

   Plots with different scales   

   Box plots with custom fill colors   

   Boxplots   

   Box plot vs. violin plot comparison   

   Violin plot customization   

   Using histograms to plot a cumulative distribution   

   Some features of the histogram (hist) function   

   Producing multiple histograms side by side   

   Using accented text in matplotlib   

   Date tick labels   

   Legend Demo   

   Mathtext   

   Multiline   

   Rendering math equations using TeX   

   Simple axes labels   

   Text Commands   

   Color Demo   

   Line, Poly and RegularPoly Collection with autoscaling   

   Ellipse Collection   

   Dark background style sheet   

   Make Room For Ylabel Using Axesgrid   

   Parasite Simple   

   Parasite Axes demo   

   Parasite axis demo   

   Ticklabel alignment   

   Simple Axis Direction03   

   Simple Axisline   

   Anatomy of a figure   

   XKCD   

   Pythonic Matplotlib   

   Plot 2D data on 3D plot   

   Create 2D bar graphs in different planes   

   3D errorbars   

   Lorenz Attractor   

   2D and 3D Axes in same Figure   

   Automatic Text Offsetting   

   3D scatterplot   

   3D surface with polar coordinates   

   Text annotations in 3D   

   Log Bar   

   Symlog Demo   

   MRI With EEG   

   Topographic hillshading   

   Multiple Yaxis With Spines   

   Basic Usage   

   Artist tutorial   

   Constrained Layout Guide   

   Tight Layout guide   

   Arranging multiple Axes in a Figure   

   Choosing Colormaps in Matplotlib   

   Text in Matplotlib Plots
matplotlib.axes.Axes.set_ymargin   Axes.set_ymargin(m)[source]
 
Set padding of Y data limits prior to autoscaling. m times the data interval will be added to each end of that interval before it is used in autoscaling. For example, if your data is in the range [0, 2], a factor of m = 0.1 will result in a range [-0.2, 2.2]. Negative values -0.5 < m < 0 will result in clipping of the data range. I.e. for a data range [0, 2], a factor of m = -0.1 will result in a range [0.2, 1.8].  Parameters 
 
mfloat greater than -0.5
matplotlib.axes.Axes.set_yscale   Axes.set_yscale(value, **kwargs)[source]
 
Set the y-axis scale.  Parameters 
 
value{"linear", "log", "symlog", "logit", ...} or ScaleBase


The axis scale type to apply.  **kwargs

Different keyword arguments are accepted, depending on the scale. See the respective class keyword arguments:  matplotlib.scale.LinearScale matplotlib.scale.LogScale matplotlib.scale.SymmetricalLogScale matplotlib.scale.LogitScale matplotlib.scale.FuncScale      Notes By default, Matplotlib supports the above mentioned scales. Additionally, custom scales may be registered using matplotlib.scale.register_scale. These scales can then also be used here. 
  Examples using matplotlib.axes.Axes.set_yscale
 
   Markevery Demo   

   Artist customization in box plots   

   Boxplot drawer function   

   Different ways of specifying error bars   

   Loglog Aspect   

   Log Bar   

   Log Demo   

   Scales   

   Symlog Demo
matplotlib.axes.Axes.set_yticklabels   Axes.set_yticklabels(labels, *, fontdict=None, minor=False, **kwargs)[source]
 
Set the yaxis' labels with list of string labels.  Warning This method should only be used after fixing the tick positions using Axes.set_yticks. Otherwise, the labels may end up in unexpected positions.   Parameters 
 
labelslist of str


The label texts.  
fontdictdict, optional


A dictionary controlling the appearance of the ticklabels. The default fontdict is: {'fontsize': rcParams['axes.titlesize'],
 'fontweight': rcParams['axes.titleweight'],
 'verticalalignment': 'baseline',
 'horizontalalignment': loc}
  
minorbool, default: False


Whether to set the minor ticklabels rather than the major ones.    Returns 
 list of Text


The labels.    Other Parameters 
 
**kwargsText properties.

   
  Examples using matplotlib.axes.Axes.set_yticklabels
 
   Zoom region inset axes   

   Artist customization in box plots   

   Boxplot drawer function   

   Violin plot basics   

   Rendering math equations using TeX   

   Colorbar Tick Labelling   

   Constrained Layout Guide
matplotlib.axes.Axes.set_yticks   Axes.set_yticks(ticks, labels=None, *, minor=False, **kwargs)[source]
 
Set the yaxis' tick locations and optionally labels. If necessary, the view limits of the Axis are expanded so that all given ticks are visible.  Parameters 
 
tickslist of floats


List of tick locations.  
labelslist of str, optional


List of tick labels. If not set, the labels show the data value.  
minorbool, default: False


If False, set the major ticks; if True, the minor ticks.  **kwargs

Text properties for the labels. These take effect only if you pass labels. In other cases, please use tick_params.     Notes The mandatory expansion of the view limits is an intentional design choice to prevent the surprise of a non-visible tick. If you need other limits, you should set the limits explicitly after setting the ticks. 
  Examples using matplotlib.axes.Axes.set_yticks
 
   Bar Label Demo   

   Horizontal bar chart   

   Broken Barh   

   Psd Demo   

   Creating annotated heatmaps   

   Rendering math equations using TeX   

   Programmatically controlling subplot adjustment   

   Make Room For Ylabel Using Axesgrid   

   Scatter Histogram (Locatable Axes)   

   Ticklabel alignment   

   Ticklabel direction   

   Bachelor's degrees by gender   

   Integral as the area under a curve   

   Shaded & power normalized rendering   

   XKCD   

   Rain simulation   

   MATPLOTLIB UNCHAINED   

   Frontpage 3D example   

   Frontpage contour example   

   Frontpage histogram example   

   Frontpage plot example   

   Create 2D bar graphs in different planes   

   MRI With EEG   

   SkewT-logP diagram: using transforms and custom projections   

   Custom spine bounds
matplotlib.axes.Axes.sharex   Axes.sharex(other)[source]
 
Share the x-axis with other. This is equivalent to passing sharex=other when constructing the axes, and cannot be used if the x-axis is already being shared with another Axes.
matplotlib.axes.Axes.sharey   Axes.sharey(other)[source]
 
Share the y-axis with other. This is equivalent to passing sharey=other when constructing the axes, and cannot be used if the y-axis is already being shared with another Axes.