matplotlib.pyplot.scatter

matplotlib.pyplot.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, *, plotnonfinite=False, 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 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. Otherwise, value- matching will have precedence in case of a size matching with x and y. Defaults to None. In that case the marker color is determined by the value of color, facecolor or facecolors. In case those are not specified or None, the marker color is determined by the next color of the Axes' current "shape and fill" color cycle. This cycle defaults to rcParams["axes.prop_cycle"]. marker : MarkerStyle, optional The marker style. marker can be either an instance of the class or the text shorthand for a particular marker. Defaults to None, in which case it takes the value of rcParams["scatter.marker"] = 'o'. See markers for more information about 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. edgecolors : {'face', 'none', None} or color or sequence of color, optional. 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 Matplotlib color or sequence of color. Defaults to None, in which case it takes the value of rcParams["scatter.edgecolors"] = 'face'. For non-filled markers, the edgecolors kwarg is ignored and forced to 'face' internally. plotnonfinite : boolean, optional, default: False Set to plot points with nonfinite c, in conjunction with set_bad.
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'.

Objects passed as data must support item access (data[<arg>]) and membership test (<arg> in data).

Examples using matplotlib.pyplot.scatter