A scatter plot of y vs. x with varying marker size and/or color.
The data positions.
The marker size in points**2 (typographic points are 1/72 in.). Default is rcParams['lines.markersize'] ** 2.
The linewidth and edgecolor can visually interact with the marker size, and can lead to artifacts if the marker size is smaller than the linewidth.
If the linewidth is greater than 0 and the edgecolor is anything but 'none', then the effective size of the marker will be increased by half the linewidth because the stroke will be centered on the edge of the shape.
To eliminate the marker edge either set linewidth=0 or edgecolor='none'.
The marker colors. Possible values:
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 2D array with a single row. Otherwise, value-matching will have precedence in case of a size matching with x and y.
If you wish to specify a single color for all points prefer the color keyword argument.
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"] (default: cycler('color', ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf'])).
MarkerStyle, default: rcParams["scatter.marker"] (default: 'o')
The marker style. marker can be either an instance of the class or the text shorthand for a particular marker. See matplotlib.markers for more information about marker styles.
Colormap, default: rcParams["image.cmap"] (default: 'viridis')
The Colormap instance or registered colormap name used to map scalar data to colors.
This parameter is ignored if c is RGB(A).
Normalize, optional
The normalization method used to scale scalar data to the [0, 1] range before mapping to colors using cmap. By default, a linear scaling is used, mapping the lowest value to 0 and the highest to 1.
If given, this can be one of the following:
Normalize or one of its subclasses (see Colormap normalization).matplotlib.scale.get_scale_names(). In that case, a suitable Normalize subclass is dynamically generated and instantiated.This parameter is ignored if c is RGB(A).
When using scalar data and no explicit norm, vmin and vmax define the data range that the colormap covers. By default, the colormap covers the complete value range of the supplied data. It is an error to use vmin/vmax when a norm instance is given (but using a str norm name together with vmin/vmax is acceptable).
This parameter is ignored if c is RGB(A).
The alpha blending value, between 0 (transparent) and 1 (opaque).
rcParams["lines.linewidth"] (default: 1.5)
The linewidth of the marker edges. Note: The default edgecolors is 'face'. You may want to change this as well.
rcParams["scatter.edgecolors"] (default: 'face')
The edge color of the marker. Possible values:
For non-filled markers, edgecolors is ignored. Instead, the color is determined like with 'face', i.e. from c, colors, or facecolors.
Whether to plot points with nonfinite c (i.e. inf, -inf or nan). If True the points are drawn with the bad colormap color (see Colormap.set_bad).
If given, the following parameters also accept a string s, which is interpreted as data[s] (unless this raises an exception):
x, y, s, linewidths, edgecolors, c, facecolor, facecolors, color
Collection properties
See also
plotTo plot scatter plots when markers are identical in size and color.
Note
This is the pyplot wrapper for axes.Axes.scatter.
plot function will be faster for scatterplots where markers don't vary in size or color.matplotlib.pyplot.scatter
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