matplotlib.pyplot.scatter — Matplotlib 3.10.1 documentation (original) (raw)
matplotlib.pyplot.scatter(x, y, s=None, c=None, *, marker=None, cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, edgecolors=None, colorizer=None, plotnonfinite=False, data=None, **kwargs)[source]#
A scatter plot of y vs. x with varying marker size and/or color.
Parameters:
x, yfloat or array-like, shape (n, )
The data positions.
sfloat or array-like, shape (n, ), optional
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'_.
carray-like or list of color or color, optional
The marker colors. Possible values:
- A scalar or sequence of n numbers to be mapped to colors using_cmap_ and norm.
- A 2D array in which the rows are RGB or RGBA.
- A sequence of colors of length n.
- A single color format string.
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"]](../../users/explain/customizing.html?highlight=axes.prop%5Fcycle#matplotlibrc-sample) (default: cycler('color', ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf'])).
markerMarkerStyle, default: [rcParams["scatter.marker"]](../../users/explain/customizing.html?highlight=scatter.marker#matplotlibrc-sample) (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.
cmapstr or Colormap, default: [rcParams["image.cmap"]](../../users/explain/customizing.html?highlight=image.cmap#matplotlibrc-sample) (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).
normstr or 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:
- An instance of Normalize or one of its subclasses (see Colormap normalization).
- A scale name, i.e. one of "linear", "log", "symlog", "logit", etc. For a list of available scales, call 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).
vmin, vmaxfloat, optional
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).
alphafloat, default: None
The alpha blending value, between 0 (transparent) and 1 (opaque).
linewidthsfloat or array-like, default: [rcParams["lines.linewidth"]](../../users/explain/customizing.html?highlight=lines.linewidth#matplotlibrc-sample) (default: 1.5)
The linewidth of the marker edges. Note: The default _edgecolors_is 'face'. You may want to change this as well.
edgecolors{'face', 'none', None} or color or list of color, default: [rcParams["scatter.edgecolors"]](../../users/explain/customizing.html?highlight=scatter.edgecolors#matplotlibrc-sample) (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 color or sequence of colors.
For non-filled markers, edgecolors is ignored. Instead, the color is determined like with 'face', i.e. from c, colors, or_facecolors_.
colorizerColorizer or None, default: None
The Colorizer object used to map color to data. If None, a Colorizer object is created from a norm and cmap.
This parameter is ignored if c is RGB(A).
plotnonfinitebool, default: False
Whether to plot points with nonfinite c (i.e. inf, -infor nan). If True the points are drawn with the _bad_colormap color (see Colormap.set_bad).
Returns:
Other Parameters:
dataindexable object, optional
If given, the following parameters also accept a string s, which is interpreted as data[s] if s is a key in data:
x, y, s, linewidths, edgecolors, c, facecolor, facecolors, color
**kwargsPathCollection properties
See also
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 1D arrays; x, y, s, and _c_may be input as N-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.