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Programmation Python
Les fondamentaux
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Module « matplotlib.pyplot »
Signature de la fonction scatter
def scatter(x: 'float | ArrayLike', y: 'float | ArrayLike', s: 'float | ArrayLike | None' = None, c: 'ArrayLike | Sequence[ColorType] | ColorType | None' = None, *, marker: 'MarkerType | None' = None, cmap: 'str | Colormap | None' = None, norm: 'str | Normalize | None' = None, vmin: 'float | None' = None, vmax: 'float | None' = None, alpha: 'float | None' = None, linewidths: 'float | Sequence[float] | None' = None, edgecolors: "Literal['face', 'none'] | ColorType | Sequence[ColorType] | None" = None, colorizer: 'Colorizer | None' = None, plotnonfinite: 'bool' = False, data=None, **kwargs) -> 'PathCollection'
Description
help(matplotlib.pyplot.scatter)
A scatter plot of *y* vs. *x* with varying marker size and/or color.
Parameters
----------
x, y : float or array-like, shape (n, )
The data positions.
s : float 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'*.
c : array-like or list of :mpltype:`color` or :mpltype:`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 :rc:`axes.prop_cycle`.
marker : `~.markers.MarkerStyle`, default: :rc:`scatter.marker`
The marker style. *marker* can be either an instance of the class
or the text shorthand for a particular marker.
See :mod:`matplotlib.markers` for more information about marker
styles.
cmap : str or `~matplotlib.colors.Colormap`, default: :rc:`image.cmap`
The Colormap instance or registered colormap name used to map scalar data
to colors.
This parameter is ignored if *c* is RGB(A).
norm : str or `~matplotlib.colors.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 :ref:`colormapnorms`).
- 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, vmax : float, 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).
alpha : float, default: None
The alpha blending value, between 0 (transparent) and 1 (opaque).
linewidths : float or array-like, default: :rc:`lines.linewidth`
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 :mpltype:`color` or list of :mpltype:`color`, default: :rc:`scatter.edgecolors`
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*.
colorizer : `~matplotlib.colorizer.Colorizer` 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).
plotnonfinite : bool, default: False
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`).
Returns
-------
`~matplotlib.collections.PathCollection`
Other Parameters
----------------
data : indexable 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*
**kwargs : `~matplotlib.collections.PathCollection` properties
Properties:
agg_filter: a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array and two offsets from the bottom left corner of the image
alpha: array-like or scalar or None
animated: bool
antialiased or aa or antialiaseds: bool or list of bools
array: array-like or None
capstyle: `.CapStyle` or {'butt', 'projecting', 'round'}
clim: (vmin: float, vmax: float)
clip_box: `~matplotlib.transforms.BboxBase` or None
clip_on: bool
clip_path: Patch or (Path, Transform) or None
cmap: `.Colormap` or str or None
color: :mpltype:`color` or list of RGBA tuples
edgecolor or ec or edgecolors: :mpltype:`color` or list of :mpltype:`color` or 'face'
facecolor or facecolors or fc: :mpltype:`color` or list of :mpltype:`color`
figure: `~matplotlib.figure.Figure` or `~matplotlib.figure.SubFigure`
gid: str
hatch: {'/', '\\', '|', '-', '+', 'x', 'o', 'O', '.', '*'}
hatch_linewidth: unknown
in_layout: bool
joinstyle: `.JoinStyle` or {'miter', 'round', 'bevel'}
label: object
linestyle or dashes or linestyles or ls: str or tuple or list thereof
linewidth or linewidths or lw: float or list of floats
mouseover: bool
norm: `.Normalize` or str or None
offset_transform or transOffset: `.Transform`
offsets: (N, 2) or (2,) array-like
path_effects: list of `.AbstractPathEffect`
paths: unknown
picker: None or bool or float or callable
pickradius: float
rasterized: bool
sizes: `numpy.ndarray` or None
sketch_params: (scale: float, length: float, randomness: float)
snap: bool or None
transform: `~matplotlib.transforms.Transform`
url: str
urls: list of str or None
visible: bool
zorder: float
See Also
--------
plot : To plot scatter plots when markers are identical in size and
color.
Notes
-----
.. note::
This is the :ref:`pyplot wrapper <pyplot_interface>` for `.axes.Axes.scatter`.
* 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*.
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