*args: Any, Plot y versus x as lines and/or markers.
+
+Call signatures:
+
+```
+plot([x], y, [fmt], *, data=None, **kwargs)
+plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)
+```
+
+The coordinates of the points or line nodes are given by \*x\*, \*y\*.
+
+The optional parameter \*fmt\* is a convenient way for defining basic
+formatting like color, marker and linestyle. It's a shortcut string
+notation described in the \*Notes\* section below.
+
+```
+>>> plot(x, y) # plot x and y using default line style and color
+>>> plot(x, y, 'bo') # plot x and y using blue circle markers
+>>> plot(y) # plot y using x as index array 0..N-1
+>>> plot(y, 'r+') # ditto, but with red plusses
+```
+
+You can use `.Line2D` properties as keyword arguments for more
+control on the appearance. Line properties and \*fmt\* can be mixed.
+The following two calls yield identical results:
+
+```
+>>> plot(x, y, 'go--', linewidth=2, markersize=12)
+>>> plot(x, y, color='green', marker='o', linestyle='dashed',
+... linewidth=2, markersize=12)
+```
+
+When conflicting with \*fmt\*, keyword arguments take precedence.
+
+\*\*Plotting labelled data\*\*
+
+There's a convenient way for plotting objects with labelled data (i.e.
+data that can be accessed by index `obj['y']`). Instead of giving
+the data in \*x\* and \*y\*, you can provide the object in the \*data\*
+parameter and just give the labels for \*x\* and \*y\*:
+
+```
+>>> plot('xlabel', 'ylabel', data=obj)
+```
+
+All indexable objects are supported. This could e.g. be a `dict`, a
+`pandas.DataFrame` or a structured numpy array.
+
+\*\*Plotting multiple sets of data\*\*
+
+There are various ways to plot multiple sets of data.
+
+- The most straight forward way is just to call `plot` multiple times.
+Example:
+
+```
+>>> plot(x1, y1, 'bo')
+>>> plot(x2, y2, 'go')
+```
+
+- If \*x\* and/or \*y\* are 2D arrays a separate data set will be drawn
+for every column. If both \*x\* and \*y\* are 2D, they must have the
+same shape. If only one of them is 2D with shape (N, m) the other
+must have length N and will be used for every data set m.
+
+ Example:
+
+```
+>>> x = [1, 2, 3]
+>>> y = np.array([[1, 2], [3, 4], [5, 6]])
+>>> plot(x, y)
+```
+
+ is equivalent to:
+
+```
+>>> for col in range(y.shape[1]):
+... plot(x, y[:, col])
+```
+
+- The third way is to specify multiple sets of \*\[x\]\*, \*y\*, \*\[fmt\]\*
+groups:
+
+```
+>>> plot(x1, y1, 'g^', x2, y2, 'g-')
+
+In this case, any additional keyword argument applies to all
+datasets. Also, this syntax cannot be combined with the *data*
+parameter.
+```
+
+By default, each line is assigned a different style specified by a
+'style cycle'. The \*fmt\* and line property parameters are only
+necessary if you want explicit deviations from these defaults.
+Alternatively, you can also change the style cycle using
+`axes.prop_cycle`.
+
+Parameters
+----------
+x, y : array-like or scalar
+ The horizontal / vertical coordinates of the data points.
+\*x\* values are optional and default to `range(len(y))`.
+
+ Commonly, these parameters are 1D arrays.
+
+ They can also be scalars, or two-dimensional (in that case, the
+columns represent separate data sets).
+
+ These arguments cannot be passed as keywords.
+
+fmt : str, optional
+ A format string, e.g. 'ro' for red circles. See the \*Notes\*
+section for a full description of the format strings.
+
+ Format strings are just an abbreviation for quickly setting
+basic line properties. All of these and more can also be
+controlled by keyword arguments.
+
+ This argument cannot be passed as keyword.
+
+data : indexable object, optional
+ An object with labelled data. If given, provide the label names to
+plot in \*x\* and \*y\*.
+
+Returns
+-------
+list of `.Line2D`
+ A list of lines representing the plotted data.
+
+Other Parameters
+----------------
+scalex, scaley : bool, default: True
+ These parameters determine if the view limits are adapted to the
+data limits. The values are passed on to
+`~.axes.Axes.autoscale_view`.
+
+\*\*kwargs : `.Line2D` properties, optional
+ \*kwargs\* are used to specify properties like a line label (for
+auto legends), linewidth, antialiasing, marker face color.
+Example:
+
+```
+>>> plot([1, 2, 3], [1, 2, 3], 'go-', label='line 1', linewidth=2)
+>>> plot([1, 2, 3], [1, 4, 9], 'rs', label='line 2')
+
+If you specify multiple lines with one plot call, the kwargs apply
+to all those lines. In case the label object is iterable, each
+element is used as labels for each set of data.
+
+Here is a list of available `.Line2D` 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: scalar or None
+animated: bool
+antialiased or aa: bool
+clip_box: `.Bbox`
+clip_on: bool
+clip_path: Patch or (Path, Transform) or None
+color or c: color
+dash_capstyle: `.CapStyle` or {'butt', 'projecting', 'round'}
+dash_joinstyle: `.JoinStyle` or {'miter', 'round', 'bevel'}
+dashes: sequence of floats (on/off ink in points) or (None, None)
+data: (2, N) array or two 1D arrays
+drawstyle or ds: {'default', 'steps', 'steps-pre', 'steps-mid', 'steps-post'}, default: 'default'
+figure: `.Figure`
+fillstyle: {'full', 'left', 'right', 'bottom', 'top', 'none'}
+gapcolor: color or None
+gid: str
+in_layout: bool
+label: object
+linestyle or ls: {'-', '--', '-.', ':', '', (offset, on-off-seq), ...}
+linewidth or lw: float
+marker: marker style string, `~.path.Path` or `~.markers.MarkerStyle`
+markeredgecolor or mec: color
+markeredgewidth or mew: float
+markerfacecolor or mfc: color
+markerfacecoloralt or mfcalt: color
+markersize or ms: float
+markevery: None or int or (int, int) or slice or list[int] or float or (float, float) or list[bool]
+mouseover: bool
+path_effects: `.AbstractPathEffect`
+picker: float or callable[[Artist, Event], tuple[bool, dict]]
+pickradius: unknown
+rasterized: bool
+sketch_params: (scale: float, length: float, randomness: float)
+snap: bool or None
+solid_capstyle: `.CapStyle` or {'butt', 'projecting', 'round'}
+solid_joinstyle: `.JoinStyle` or {'miter', 'round', 'bevel'}
+transform: unknown
+url: str
+visible: bool
+xdata: 1D array
+ydata: 1D array
+zorder: float
+```
+
+See Also
+--------
+scatter : XY scatter plot with markers of varying size and/or color (
+ sometimes also called bubble chart).
+
+Notes
+-----
+\*\*Format Strings\*\*
+
+A format string consists of a part for color, marker and line:
+
+```
+fmt = '[marker][line][color]'
+```
+
+Each of them is optional. If not provided, the value from the style
+cycle is used. Exception: If `line` is given, but no `marker`,
+the data will be a line without markers.
+
+Other combinations such as `[color][marker][line]` are also
+supported, but note that their parsing may be ambiguous.
+
+\*\*Markers\*\*
+
+|character | | |description |
+|-------------| -------------------------------|
+|``'.'`` | | |point marker|
+|``','`` | | |pixel marker|
+|``'o'`` | | |circle marker|
+|``'v'`` | | |triangle_down marker|
+|``'^'`` | | |triangle_up marker|
+|``'<'`` | | |triangle_left marker|
+|``'>'`` | | |triangle_right marker|
+|``'1'`` | | |tri_down marker|
+|``'2'`` | | |tri_up marker|
+|``'3'`` | | |tri_left marker|
+|``'4'`` | | |tri_right marker|
+|``'8'`` | | |octagon marker|
+|``'s'`` | | |square marker|
+|``'p'`` | | |pentagon marker|
+|``'P'`` | | |plus (filled) marker|
+|``'*'`` | | |star marker|
+|``'h'`` | | |hexagon1 marker|
+|``'H'`` | | |hexagon2 marker|
+|``'+'`` | | |plus marker|
+|``'x'`` | | |x marker|
+|``'X'`` | | |x (filled) marker|
+|``'D'`` | | |diamond marker|
+|``'d'`` | | |thin_diamond marker|
+|``'|'`` | | |vline marker|
+|``'_'`` | | |hline marker|
+
+<br/>
+
+
+\*\*Line Styles\*\*
+
+|character | | | |description |
+|-------------| -------------------------------|
+|``'-'`` | | | |solid line style|
+|``'--'`` | | | |dashed line style|
+|``'-.'`` | | | |dash-dot line style|
+|``':'`` | | | |dotted line style|
+
+<br/>
+
+
+Example format strings:
+
+```
+'b' # blue markers with default shape
+'or' # red circles
+'-g' # green solid line
+'--' # dashed line with default color
+'^k:' # black triangle_up markers connected by a dotted line
+```
+
+\*\*Colors\*\*
+
+The supported color abbreviations are the single letter codes
+
+|character | | | |color |
+|-------------| -------------------------------|
+|``'b'`` | | | |blue|
+|``'g'`` | | | |green|
+|``'r'`` | | | |red|
+|``'c'`` | | | |cyan|
+|``'m'`` | | | |magenta|
+|``'y'`` | | | |yellow|
+|``'k'`` | | | |black|
+|``'w'`` | | | |white|
+
+<br/>
+
+
+and the `'CN'` colors that index into the default property cycle.
+
+If the color is the only part of the format string, you can
+additionally use any `matplotlib.colors` spec, e.g. full names
+(`'green'`) or hex strings (`'#008000'`)., hint
y_pred: Any, Mean squared error regression loss.
+
+Read more in the `User Guide <mean_squared_error>`.
+
+Parameters
+----------
+y\_true : array-like of shape (n\_samples,) or (n\_samples, n\_outputs)
+ Ground truth (correct) target values.
+
+y\_pred : array-like of shape (n\_samples,) or (n\_samples, n\_outputs)
+ Estimated target values.
+
+sample\_weight : array-like of shape (n\_samples,), default=None
+ Sample weights.
+
+multioutput : {'raw\_values', 'uniform\_average'} or array-like of shape (n\_outputs,), default='uniform\_average'
+ Defines aggregating of multiple output values.
+Array-like value defines weights used to average errors.
+
+ 'raw\_values' :
+ Returns a full set of errors in case of multioutput input.
+
+ 'uniform\_average' :
+ Errors of all outputs are averaged with uniform weight.
+
+squared : bool, default=True
+ If True returns MSE value, if False returns RMSE value.
+
+Returns
+-------
+loss : float or ndarray of floats
+ A non-negative floating point value (the best value is 0.0), or an
+array of floating point values, one for each individual target.
+
+Examples
+--------
+```
+>>> from sklearn.metrics import mean_squared_error
+>>> y_true = [3, -0.5, 2, 7]
+>>> y_pred = [2.5, 0.0, 2, 8]
+>>> mean_squared_error(y_true, y_pred)
+0.375
+>>> y_true = [3, -0.5, 2, 7]
+>>> y_pred = [2.5, 0.0, 2, 8]
+>>> mean_squared_error(y_true, y_pred, squared=False)
+0.612...
+>>> y_true = [[0.5, 1],[-1, 1],[7, -6]]
+>>> y_pred = [[0, 2],[-1, 2],[8, -5]]
+>>> mean_squared_error(y_true, y_pred)
+0.708...
+>>> mean_squared_error(y_true, y_pred, squared=False)
+0.822...
+>>> mean_squared_error(y_true, y_pred, multioutput='raw_values')
+array([0.41666667, 1. ])
+>>> mean_squared_error(y_true, y_pred, multioutput=[0.3, 0.7])
+0.825...
+```, hint
