matplotlib - Plotly Backend Shim

Version: 3.9.0-offlinai | Type: API compatibility layer (matplotlib -> Plotly) | Modules: 64 | Location: matplotlib/

Drop-in replacement for matplotlib.pyplot that renders interactive charts via Plotly.js. Import matplotlib.pyplot as plt and it just works. Provides comprehensive API coverage across 64 modules matching matplotlib's public interface.

Quick Start

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 2 * np.pi, 200)
plt.plot(x, np.sin(x), label='sin(x)')
plt.plot(x, np.cos(x), label='cos(x)')
plt.title('Trigonometric Functions')
plt.xlabel('x')
plt.ylabel('y')
plt.legend()
plt.grid(True)
plt.show()

Module Reference (64 modules)

`matplotlib.pyplot` -- Primary Plotting Interface

2D Plot Types

Function	Description
`plt.plot(x, y, fmt, **kwargs)`	Line plot. Format strings: `'b-'`, `'ro'`, `'g--'`, etc.
`plt.scatter(x, y, s, c, marker, alpha)`	Scatter plot with optional size/color arrays
`plt.bar(x, height, width, bottom, color)`	Vertical bar chart
`plt.barh(y, width, height, left, color)`	Horizontal bar chart
`plt.hist(data, bins, range, density, cumulative)`	Histogram
`plt.hist2d(x, y, bins, cmap)`	2D histogram / heatmap
`plt.pie(sizes, labels, autopct, explode, shadow)`	Pie chart
`plt.fill_between(x, y1, y2, alpha, color)`	Filled area between curves
`plt.fill_betweenx(y, x1, x2, alpha)`	Horizontal filled area
`plt.stem(x, y, linefmt, markerfmt, basefmt)`	Stem plot
`plt.step(x, y, where, color, linewidth)`	Step plot
`plt.errorbar(x, y, yerr, xerr, fmt, capsize)`	Error bars
`plt.boxplot(data, notch, vert, labels)`	Box-and-whisker plot
`plt.violinplot(data, positions, showmeans)`	Violin plot
`plt.imshow(Z, cmap, aspect, interpolation, extent)`	Image / heatmap display
`plt.matshow(Z, cmap)`	Matrix display (calls imshow)
`plt.pcolormesh(X, Y, Z, cmap, shading)`	Pseudocolor mesh plot
`plt.contour(X, Y, Z, levels, colors, cmap)`	Contour lines
`plt.contourf(X, Y, Z, levels, cmap)`	Filled contours
`plt.polar(theta, r, **kwargs)`	Polar plot
`plt.stackplot(x, *ys, labels, colors)`	Stacked area chart
`plt.hexbin(x, y, gridsize, cmap, mincnt)`	Hexagonal binning plot
`plt.hlines(y, xmin, xmax, colors, linestyles)`	Horizontal line segments
`plt.vlines(x, ymin, ymax, colors, linestyles)`	Vertical line segments
`plt.quiver(X, Y, U, V, C)`	2D vector field (arrows)
`plt.streamplot(X, Y, U, V, density, color)`	2D streamlines
`plt.tricontour(x, y, z, levels)`	Unstructured triangular contour
`plt.tricontourf(x, y, z, levels)`	Filled triangular contour
`plt.tripcolor(x, y, z, cmap)`	Pseudocolor on triangular grid
`plt.spy(Z, precision, marker)`	Sparsity pattern visualization
`plt.eventplot(positions, orientation)`	Event/raster plot
`plt.broken_barh(xranges, yrange)`	Broken horizontal bars (Gantt-style)

3D Plot Types

Function	Description
`plt.plot_surface(X, Y, Z, cmap, alpha)`	3D surface (auto-creates 3D axes)
`plt.plot_wireframe(X, Y, Z, color)`	3D wireframe mesh
`plt.scatter3D(x, y, z, c, s, cmap)`	3D scatter plot
`plt.plot3D(x, y, z, color)`	3D line plot
`plt.bar3d(x, y, z, dx, dy, dz, color)`	3D bar chart
`plt.plot_trisurf(x, y, z, cmap)`	3D triangulated surface
`ax.contour3D(X, Y, Z, levels, cmap)`	3D contour lines
`ax.contourf3D(X, Y, Z, levels, cmap)`	3D filled contours

Figure & Axes Management

Function	Description
`plt.figure(figsize, dpi, facecolor)`	Create new figure
`plt.subplots(nrows, ncols, sharex, sharey, figsize)`	Create figure + axes grid
`plt.subplot(nrows, ncols, index)`	Add subplot to current figure
`plt.subplot2grid(shape, loc, rowspan, colspan)`	Subplot with grid positioning
`plt.axes(rect)`	Add axes at arbitrary position
`plt.gca()`	Get current axes
`plt.gcf()`	Get current figure
`plt.cla()`	Clear current axes
`plt.clf()`	Clear current figure
`plt.close(fig)`	Close a figure
`ax.twinx()`	Create secondary y-axis
`ax.twiny()`	Create secondary x-axis
`fig.add_subplot(nrows, ncols, index, projection)`	Add subplot (`projection='3d'` for 3D)

Annotations & Text

Function	Description
`plt.title(s, fontsize, fontweight)`	Set axes title
`plt.suptitle(s, fontsize)`	Set figure super title
`plt.xlabel(s, fontsize)` / `plt.ylabel(s)`	Axis labels
`plt.text(x, y, s, fontsize, ha, va)`	Place text at data coordinates
`plt.annotate(text, xy, xytext, arrowprops)`	Arrow annotation
`plt.figtext(x, y, s)`	Text in figure coordinates
`ax.set_title(s)`	Axes title (OO interface)
`ax.set_xlabel(s)` / `ax.set_ylabel(s)`	Axis labels (OO)

Axis Configuration

Function	Description
`plt.xlim(left, right)` / `plt.ylim(bottom, top)`	Set axis limits
`plt.xscale('log')` / `plt.yscale('log')`	Set axis scale (`linear`/`log`/`symlog`/`logit`)
`plt.xticks(ticks, labels, rotation)`	Set tick positions and labels
`plt.yticks(ticks, labels)`	Set y-axis ticks
`plt.grid(visible, which, axis, linestyle)`	Toggle grid
`plt.legend(loc, fontsize, frameon, ncol)`	Show legend
`plt.colorbar(mappable, ax, label)`	Add colorbar
`plt.axis('equal'/'off'/'tight'/'scaled')`	Set axis mode
`plt.tight_layout(pad)`	Adjust subplot spacing
`plt.margins(x, y)`	Set axis margins
`plt.axhline(y, color, linestyle)`	Horizontal reference line
`plt.axvline(x, color, linestyle)`	Vertical reference line
`plt.axhspan(ymin, ymax, alpha, color)`	Horizontal span (shaded region)
`plt.axvspan(xmin, xmax, alpha, color)`	Vertical span
`plt.minorticks_on()` / `plt.minorticks_off()`	Toggle minor ticks
`ax.invert_xaxis()` / `ax.invert_yaxis()`	Invert axis direction
`ax.set_aspect('equal'/'auto')`	Set aspect ratio

Output

Function	Description
`plt.show()`	Display chart (renders as interactive HTML in WKWebView)
`plt.savefig('chart.html')`	Save as interactive HTML
`plt.savefig('chart.png', dpi)`	Save as PNG (requires kaleido)
`plt.savefig('chart.svg')`	Save as SVG
`plt.savefig('chart.pdf')`	Save as PDF

`matplotlib.figure` -- Figure Class

Class / Method	Description
`Figure(figsize, dpi, facecolor, edgecolor)`	Figure container
`fig.add_subplot(pos, projection)`	Add Axes to the figure
`fig.add_axes(rect)`	Add Axes at arbitrary position [left, bottom, width, height]
`fig.suptitle(t, fontsize)`	Super title for the figure
`fig.tight_layout()`	Adjust subplot params for tight layout
`fig.subplots_adjust(left, bottom, right, top, wspace, hspace)`	Fine-tune subplot spacing
`fig.savefig(fname, dpi, bbox_inches)`	Save figure
`fig.set_size_inches(w, h)`	Set figure size
`fig.get_axes()`	Return list of axes

`matplotlib.axes` -- Axes Class

The Axes object supports the full OO plotting interface. All plt.xxx() functions delegate to the current axes.

Method	Description
`ax.plot()`, `ax.scatter()`, `ax.bar()`, etc.	All plot types listed above
`ax.set_xlim()`, `ax.set_ylim()`	Axis limits
`ax.set_xscale()`, `ax.set_yscale()`	Axis scales
`ax.set_xticks()`, `ax.set_yticks()`	Tick positions
`ax.set_xticklabels()`, `ax.set_yticklabels()`	Tick labels
`ax.legend()`	Show legend
`ax.grid()`	Toggle grid
`ax.twinx()`, `ax.twiny()`	Secondary axes
`ax.tick_params(axis, which, direction, length)`	Configure tick appearance

`matplotlib.cm` -- Colormaps (50+ mapped)

Colormaps are callable objects that map normalized values [0, 1] to RGBA colors.

from matplotlib import cm

# Callable colormaps
rgba = cm.viridis(0.5)    # Returns (R, G, B, A) tuple
rgba = cm.plasma(0.75)
rgba = cm.jet(0.25)

# Get colormap by name
cmap = cm.get_cmap('coolwarm')
colors = cmap(np.linspace(0, 1, 10))  # Array of 10 RGBA colors

Sequential: viridis, plasma, inferno, magma, cividis, turbo

Perceptual: hot, cool, bone, copper, gray, binary

Seasonal: spring, summer, autumn, winter

Diverging: coolwarm, RdBu, RdYlGn, RdYlBu, Spectral, PiYG, PRGn, BrBG, seismic, bwr

Cyclic: twilight, twilight_shifted, hsv

Qualitative: tab10, tab20, tab20b, tab20c, Set1, Set2, Set3, Paired, Pastel1, Pastel2, Dark2, Accent

Multi-hue sequential: YlGnBu, YlOrRd, PuBu, BuGn, GnBu, PuRd, OrRd, RdPu, BuPu, YlGn

Single-hue sequential: Greens, Blues, Reds, Oranges, Purples, Greys

Other: jet, rainbow, gist_rainbow, nipy_spectral, terrain, ocean, cubehelix

`matplotlib.colors` -- Color Utilities

Function / Class	Description
`to_rgba(c, alpha)`	Convert any color spec to (R, G, B, A). Supports hex (`'#ff0000'`), named (`'red'`), CSS4, RGB tuples, shorthand (`'r'`, `'b'`)
`to_hex(c, keep_alpha)`	Convert color to hex string
`to_rgb(c)`	Convert to (R, G, B) tuple
`Normalize(vmin, vmax)`	Linear normalization to [0, 1]
`LogNorm(vmin, vmax)`	Logarithmic normalization
`SymLogNorm(linthresh, vmin, vmax)`	Symmetric log normalization
`PowerNorm(gamma, vmin, vmax)`	Power-law normalization
`BoundaryNorm(boundaries, ncolors)`	Map to discrete boundaries
`TwoSlopeNorm(vcenter, vmin, vmax)`	Diverging normalization around center
`Colormap(name, N)`	Base colormap class
`ListedColormap(colors, name)`	Colormap from explicit color list
`LinearSegmentedColormap(name, segmentdata)`	Colormap from linear segments
`LinearSegmentedColormap.from_list(name, colors)`	Create from list of colors
`CSS4_COLORS`	Dict of 148 CSS4 named colors
`TABLEAU_COLORS`	Dict of Tableau 10 colors
`BASE_COLORS`	Dict of single-letter colors (r, g, b, c, m, y, k, w)
`XKCD_COLORS`	Dict of 954 XKCD color survey names

`matplotlib.ticker` -- Tick Locators & Formatters

Locators

Class	Description
`AutoLocator()`	Automatic tick placement
`MaxNLocator(nbins)`	At most N bins
`MultipleLocator(base)`	Ticks at multiples of base
`FixedLocator(locs)`	Ticks at specific locations
`IndexLocator(base, offset)`	Ticks at index intervals
`LinearLocator(numticks)`	Evenly spaced ticks
`LogLocator(base, subs)`	Log-scale tick locations
`SymmetricalLogLocator(linthresh)`	Symmetric log ticks
`NullLocator()`	No ticks
`AutoMinorLocator(n)`	Automatic minor ticks

Formatters

Class	Description
`ScalarFormatter(useOffset, useMathText)`	Default scalar formatting
`FuncFormatter(func)`	Custom function-based formatting
`FormatStrFormatter(fmt)`	Printf-style format string
`StrMethodFormatter(fmt)`	str.format()-style formatting
`FixedFormatter(seq)`	Fixed sequence of label strings
`PercentFormatter(xmax, decimals)`	Display as percentage
`LogFormatter(base)`	Log-scale labels
`LogFormatterMathtext(base)`	Log labels with mathtext
`NullFormatter()`	No labels
`EngFormatter(unit, places)`	Engineering notation (k, M, G)

`matplotlib.patches` -- 2D Shapes

Class	Key Parameters	Description
`Rectangle(xy, width, height, angle)`	Rectangle patch
`Circle(xy, radius)`	Circle patch
`Ellipse(xy, width, height, angle)`	Ellipse patch
`FancyBboxPatch(xy, width, height, boxstyle)`	Fancy box with rounded corners etc.
`Polygon(xy, closed)`	Arbitrary polygon
`RegularPolygon(xy, numVertices, radius)`	Regular polygon
`Arc(xy, width, height, angle, theta1, theta2)`	Elliptical arc
`Wedge(center, r, theta1, theta2, width)`	Wedge (pie slice)
`Arrow(x, y, dx, dy, width)`	Arrow patch
`FancyArrow(x, y, dx, dy, width, head_width)`	Fancy arrow
`FancyArrowPatch(posA, posB, arrowstyle)`	Arrow between two points with style
`PathPatch(path, **kwargs)`	Arbitrary path patch
`ConnectionPatch(xyA, xyB, coordsA, coordsB)`	Connect points across axes
`BoxStyle`	Box styles: `round`, `round4`, `roundtooth`, `sawtooth`, `square`
`ArrowStyle`	Arrow styles: `->`, `-[`, `-	>`,` <->`,` <

`matplotlib.lines` -- Line2D

Property	Values
`linestyle` / `ls`	`'-'`, `'--'`, `'-.'`, `':'`, `'None'`
`linewidth` / `lw`	Float (points)
`color` / `c`	Any color spec
`marker`	`'o'`, `'s'`, `'^'`, `'v'`, `'D'`, `'*'`, `'+'`, `'x'`, `'.'`, `','`, `'h'`, `'p'`, `'
`markersize` / `ms`	Float (points)
`markerfacecolor` / `mfc`	Marker fill color
`markeredgecolor` / `mec`	Marker edge color
`alpha`	Float 0-1 transparency
`label`	String for legend
`zorder`	Drawing order (higher = on top)

`matplotlib.animation` -- Animation

Class	Description
`FuncAnimation(fig, func, frames, init_func, interval, blit)`	Animation by repeatedly calling a function
`ArtistAnimation(fig, artists, interval)`	Animation from a list of artist sequences

Note: Animation renders as a sequence of frames. Video export requires ffmpeg (limited on iOS).

`matplotlib.gridspec` -- Grid Layout

Class	Description
`GridSpec(nrows, ncols, figure, width_ratios, height_ratios, wspace, hspace)`	Flexible subplot grid specification
`SubplotSpec`	Specifies location of a subplot in a GridSpec
`GridSpecFromSubplotSpec(nrows, ncols, subplot_spec)`	Nested grid spec

import matplotlib.gridspec as gridspec
fig = plt.figure(figsize=(12, 8))
gs = gridspec.GridSpec(2, 3, width_ratios=[1, 2, 1], height_ratios=[2, 1])
ax1 = fig.add_subplot(gs[0, :])   # Top row, all columns
ax2 = fig.add_subplot(gs[1, 0])   # Bottom-left
ax3 = fig.add_subplot(gs[1, 1:])  # Bottom-right spanning 2 cols

`matplotlib.text` -- Text Rendering

Class / Property	Description
`Text(x, y, text, fontsize, ha, va, rotation, color, fontweight, fontstyle)`	Text artist
`Annotation(text, xy, xytext, arrowprops, fontsize)`	Annotated text with arrow
`fontsize`	Integer or `'xx-small'`, `'x-small'`, `'small'`, `'medium'`, `'large'`, `'x-large'`, `'xx-large'`
`fontweight`	`'normal'`, `'bold'`, `'light'`, `'heavy'`
`fontstyle`	`'normal'`, `'italic'`, `'oblique'`
`ha` (horizontalalignment)	`'left'`, `'center'`, `'right'`
`va` (verticalalignment)	`'top'`, `'center'`, `'bottom'`, `'baseline'`

`matplotlib.image` -- Image Handling

Function	Description
`imread(fname)`	Read image file to numpy array
`imsave(fname, arr, cmap)`	Save numpy array as image
`AxesImage`	Image displayed on axes (returned by `imshow`)

`matplotlib.collections` -- Efficient Drawing

Class	Description
`PathCollection`	Collection of paths (used by `scatter()`)
`LineCollection(segments, colors, linewidths)`	Collection of line segments
`PatchCollection(patches, match_original)`	Collection of patches
`PolyCollection(verts, **kwargs)`	Collection of polygons
`QuadMesh`	Quadrilateral mesh (used by `pcolormesh()`)
`EventCollection(positions, orientation)`	Collection of events

`matplotlib.legend` -- Legend

Parameter	Description
`loc`	`'best'`, `'upper right'`, `'upper left'`, `'lower left'`, `'lower right'`, `'center'`, etc.
`fontsize`	Legend font size
`frameon`	Draw frame around legend
`ncol`	Number of columns
`title`	Legend title
`bbox_to_anchor`	Anchor point for positioning
`borderaxespad`	Padding between legend and axes

`matplotlib.transforms` -- Coordinate Transforms

Class	Description
`Affine2D()`	2D affine transform (rotate, translate, scale)
`Bbox(points)`	Bounding box
`TransformedBbox(bbox, transform)`	Transformed bounding box
`BlendedGenericTransform(x_transform, y_transform)`	Blend separate x and y transforms
`CompositeGenericTransform(a, b)`	Composition of two transforms

`matplotlib.dates` -- Date Handling

Class / Function	Description
`DateFormatter(fmt)`	Format dates on axis (e.g. `'%Y-%m-%d'`)
`AutoDateLocator()`	Automatic date tick placement
`DayLocator(bymonthday)`	Tick every N days
`MonthLocator(bymonth)`	Tick every N months
`YearLocator(base)`	Tick every N years
`HourLocator(byhour)`	Tick every N hours
`MinuteLocator(byminute)`	Tick every N minutes
`date2num(d)`	Convert datetime to matplotlib float
`num2date(n)`	Convert matplotlib float to datetime
`datestr2num(d)`	Convert date string to float

`matplotlib.scale` -- Axis Scales

Scale	Description
`'linear'`	Default linear scale
`'log'`	Logarithmic scale (base 10)
`'symlog'`	Symmetric log (linear near zero, log for large values)
`'logit'`	Logit scale for probabilities
`'function'`	Custom function-based scale

`matplotlib.style` -- Style Sheets

import matplotlib.style as mplstyle
print(mplstyle.available)  # List available styles
mplstyle.use('ggplot')     # Apply a style
mplstyle.use('seaborn-v0_8')
mplstyle.use('dark_background')

Available styles: default, classic, ggplot, seaborn-v0_8, bmh, dark_background, fivethirtyeight, grayscale, Solarize_Light2, tableau-colorblind10

`matplotlib.rcParams` -- Configuration

import matplotlib as mpl
mpl.rcParams['figure.figsize'] = [10, 6]
mpl.rcParams['font.size'] = 14
mpl.rcParams['lines.linewidth'] = 2
mpl.rcParams['axes.grid'] = True

Note: Only basic rcParams are supported. Complex configuration may not propagate to the Plotly backend.

`matplotlib.mathtext` -- Math Text Rendering

Supports TeX-like math expressions in labels and titles:

plt.title(r'$\alpha \cdot \beta = \gamma$')
plt.xlabel(r'$x^2 + y^2 = r^2$')
plt.ylabel(r'$\frac{d}{dx} e^x = e^x$')

Supported: Greek letters, superscripts, subscripts, fractions, square roots, summation, integrals, common math symbols.

`mpl_toolkits.mplot3d` -- 3D Plotting Toolkit

Class / Method	Description
`Axes3D(fig)`	3D axes object
`ax.plot_surface(X, Y, Z, cmap, alpha, rstride, cstride)`	3D surface mesh
`ax.plot_wireframe(X, Y, Z, rstride, cstride)`	3D wireframe mesh
`ax.scatter(x, y, z, c, s, marker)`	3D scatter points
`ax.plot(x, y, z, color)`	3D line
`ax.bar3d(x, y, z, dx, dy, dz, color)`	3D bar chart
`ax.plot_trisurf(x, y, z, cmap)`	3D triangulated surface
`ax.contour(X, Y, Z, levels)`	3D contour
`ax.contourf(X, Y, Z, levels)`	3D filled contour
`ax.set_zlabel(s)`	Z-axis label
`ax.set_zlim(low, high)`	Z-axis limits
`ax.view_init(elev, azim)`	Set camera angle
`ax.dist`	Camera distance

Access via: fig.add_subplot(111, projection='3d') or from mpl_toolkits.mplot3d import Axes3D

`mpl_toolkits.axes_grid1` -- Axes Grid Helpers

Class	Description
`make_axes_locatable(ax)`	Create divider for appending axes (used for colorbars)
`ImageGrid(fig, rect, nrows_ncols, axes_pad)`	Grid of axes for images
`AxesDivider`	Divide axes into sub-axes
`inset_locator.inset_axes(parent_axes, width, height, loc)`	Create inset axes
`inset_locator.mark_inset(parent_axes, inset_axes, loc1, loc2)`	Mark inset region

`mpl_toolkits.axisartist` -- Custom Axis

Class	Description
`Subplot(fig, *args)`	Subplot with axisartist features
`Axes(fig, rect)`	Axes with custom axis drawing
`floating_axes.FloatingSubplot(fig, rect, transform)`	Floating axes (curved coordinate systems)
`grid_helper_curvelinear`	Curvilinear grid helper

Additional Modules

Module	Description
`matplotlib.backend_bases`	Abstract backend interface
`matplotlib.backends`	Backend implementations
`matplotlib.bezier`	Bezier curve utilities
`matplotlib.blocking_input`	Blocking input helpers
`matplotlib.category`	Categorical axis support
`matplotlib.cbook`	Utility functions (deprecated_warning, etc.)
`matplotlib.colorbar`	Colorbar class and helpers
`matplotlib.container`	Artist containers (BarContainer, ErrorbarContainer, StemContainer)
`matplotlib.contour`	Contour computation
`matplotlib.dviread`	DVI file reading
`matplotlib.font_manager`	Font discovery and management
`matplotlib.ft2font`	FreeType font interface
`matplotlib.hatch`	Hatch pattern definitions
`matplotlib.markers`	Marker style definitions
`matplotlib.mlab`	MATLAB-compatible helper functions
`matplotlib.offsetbox`	Offset box for annotations (AnchoredText, TextArea, DrawingArea)
`matplotlib.path`	Path class for arbitrary curves
`matplotlib.patheffects`	Path effects (shadow, stroke, normal)
`matplotlib.projections`	Projection registry (polar, etc.)
`matplotlib.quiver`	Quiver and barbs
`matplotlib.sankey`	Sankey diagram
`matplotlib.spines`	Axes spines (borders)
`matplotlib.stackplot`	Stacked area plot
`matplotlib.streamplot`	Streamline plots
`matplotlib.table`	Table rendering on axes
`matplotlib.texmanager`	TeX rendering manager
`matplotlib.textpath`	Text as Path objects
`matplotlib.tri`	Triangulation and triangular grids
`matplotlib.units`	Unit conversion support
`matplotlib.widgets`	Interactive widgets (Slider, Button, etc.)

Compatibility Notes

All plots render as interactive Plotly.js charts in WKWebView
Plotly provides built-in hover, zoom, pan, and legend toggle
plt.show() generates HTML output (not bitmap)
Most rcParams are accepted but not all propagate to Plotly
The OO interface (fig, ax = plt.subplots()) is fully supported
Format strings ('r--', 'bo', 'g^') are parsed and mapped to Plotly styles

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matplotlib - Plotly Backend Shim

Quick Start

Module Reference (64 modules)

`matplotlib.pyplot` -- Primary Plotting Interface

2D Plot Types

3D Plot Types

Figure & Axes Management

Annotations & Text

Axis Configuration

Output

`matplotlib.figure` -- Figure Class

`matplotlib.axes` -- Axes Class

`matplotlib.cm` -- Colormaps (50+ mapped)

`matplotlib.colors` -- Color Utilities

`matplotlib.ticker` -- Tick Locators & Formatters

Locators

Formatters

`matplotlib.patches` -- 2D Shapes

`matplotlib.lines` -- Line2D

`matplotlib.animation` -- Animation

`matplotlib.gridspec` -- Grid Layout

`matplotlib.text` -- Text Rendering

`matplotlib.image` -- Image Handling

`matplotlib.collections` -- Efficient Drawing

`matplotlib.legend` -- Legend

`matplotlib.transforms` -- Coordinate Transforms

`matplotlib.dates` -- Date Handling

`matplotlib.scale` -- Axis Scales

`matplotlib.style` -- Style Sheets

`matplotlib.rcParams` -- Configuration

`matplotlib.mathtext` -- Math Text Rendering

`mpl_toolkits.mplot3d` -- 3D Plotting Toolkit

`mpl_toolkits.axes_grid1` -- Axes Grid Helpers

`mpl_toolkits.axisartist` -- Custom Axis

Additional Modules

Compatibility Notes

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matplotlib - Plotly Backend Shim

Quick Start

Module Reference (64 modules)

matplotlib.pyplot -- Primary Plotting Interface

2D Plot Types

3D Plot Types

Figure & Axes Management

Annotations & Text

Axis Configuration

Output

matplotlib.figure -- Figure Class

matplotlib.axes -- Axes Class

matplotlib.cm -- Colormaps (50+ mapped)

matplotlib.colors -- Color Utilities

matplotlib.ticker -- Tick Locators & Formatters

Locators

Formatters

matplotlib.patches -- 2D Shapes

matplotlib.lines -- Line2D

matplotlib.animation -- Animation

matplotlib.gridspec -- Grid Layout

matplotlib.text -- Text Rendering

matplotlib.image -- Image Handling

matplotlib.collections -- Efficient Drawing

matplotlib.legend -- Legend

matplotlib.transforms -- Coordinate Transforms

matplotlib.dates -- Date Handling

matplotlib.scale -- Axis Scales

matplotlib.style -- Style Sheets

matplotlib.rcParams -- Configuration

matplotlib.mathtext -- Math Text Rendering

mpl_toolkits.mplot3d -- 3D Plotting Toolkit

mpl_toolkits.axes_grid1 -- Axes Grid Helpers

mpl_toolkits.axisartist -- Custom Axis

Additional Modules

Compatibility Notes

`matplotlib.pyplot` -- Primary Plotting Interface

`matplotlib.figure` -- Figure Class

`matplotlib.axes` -- Axes Class

`matplotlib.cm` -- Colormaps (50+ mapped)

`matplotlib.colors` -- Color Utilities

`matplotlib.ticker` -- Tick Locators & Formatters

`matplotlib.patches` -- 2D Shapes

`matplotlib.lines` -- Line2D

`matplotlib.animation` -- Animation

`matplotlib.gridspec` -- Grid Layout

`matplotlib.text` -- Text Rendering

`matplotlib.image` -- Image Handling

`matplotlib.collections` -- Efficient Drawing

`matplotlib.legend` -- Legend

`matplotlib.transforms` -- Coordinate Transforms

`matplotlib.dates` -- Date Handling

`matplotlib.scale` -- Axis Scales

`matplotlib.style` -- Style Sheets

`matplotlib.rcParams` -- Configuration

`matplotlib.mathtext` -- Math Text Rendering

`mpl_toolkits.mplot3d` -- 3D Plotting Toolkit

`mpl_toolkits.axes_grid1` -- Axes Grid Helpers

`mpl_toolkits.axisartist` -- Custom Axis