You are reading an old version of the documentation (v2.2.4). For the latest version see https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.scatter.html
Version 2.2.4
matplotlib
Fork me on GitHub

Table of Contents

matplotlib.axes.Axes.scatter

Axes.scatter(x, y, s=None, c=None, marker=None, cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, verts=None, edgecolors=None, *, data=None, **kwargs)[source]

A scatter plot of y vs x with varying marker size and/or color.

Parameters:
x, y : array_like, shape (n, )

The data positions.

s : scalar or array_like, shape (n, ), optional

The marker size in points**2. Default is rcParams['lines.markersize'] ** 2.

c : color, sequence, or sequence of color, optional, default: 'b'

The marker color. Possible values:

  • A single color format string.
  • A sequence of color specifications of length n.
  • A sequence of n numbers to be mapped to colors using cmap and norm.
  • A 2-D array in which the rows are RGB or RGBA.

Note that c should not be a single numeric RGB or RGBA sequence because that is indistinguishable from an array of values to be colormapped. If you want to specify the same RGB or RGBA value for all points, use a 2-D array with a single row.

marker : MarkerStyle, optional, default: 'o'

The marker style. marker can be either an instance of the class or the text shorthand for a particular marker. See markers for more information marker styles.

cmap : Colormap, optional, default: None

A Colormap instance or registered colormap name. cmap is only used if c is an array of floats. If None, defaults to rc image.cmap.

norm : Normalize, optional, default: None

A Normalize instance is used to scale luminance data to 0, 1. norm is only used if c is an array of floats. If None, use the default colors.Normalize.

vmin, vmax : scalar, optional, default: None

vmin and vmax are used in conjunction with norm to normalize luminance data. If None, the respective min and max of the color array is used. vmin and vmax are ignored if you pass a norm instance.

alpha : scalar, optional, default: None

The alpha blending value, between 0 (transparent) and 1 (opaque).

linewidths : scalar or array_like, optional, default: None

The linewidth of the marker edges. Note: The default edgecolors is 'face'. You may want to change this as well. If None, defaults to rcParams lines.linewidth.

verts : sequence of (x, y), optional

If marker is None, these vertices will be used to construct the marker. The center of the marker is located at (0, 0) in normalized units. The overall marker is rescaled by s.

edgecolors : color or sequence of color, optional, default: 'face'

The edge color of the marker. Possible values:

  • 'face': The edge color will always be the same as the face color.
  • 'none': No patch boundary will be drawn.
  • A matplotib color.

For non-filled markers, the edgecolors kwarg is ignored and forced to 'face' internally.

Returns:
paths : PathCollection
Other Parameters:
**kwargs : Collection properties

See also

plot
To plot scatter plots when markers are identical in size and color.

Notes

  • The plot function will be faster for scatterplots where markers don't vary in size or color.
  • Any or all of x, y, s, and c may be masked arrays, in which case all masks will be combined and only unmasked points will be plotted.
  • Fundamentally, scatter works with 1-D arrays; x, y, s, and c may be input as 2-D arrays, but within scatter they will be flattened. The exception is c, which will be flattened only if its size matches the size of x and y.

Note

In addition to the above described arguments, this function can take a data keyword argument. If such a data argument is given, the following arguments are replaced by data[<arg>]:

  • All arguments with the following names: 'c', 'color', 'edgecolors', 'facecolor', 'facecolors', 'linewidths', 's', 'x', 'y'.

Examples using matplotlib.axes.Axes.scatter