`skcriteria.plot` package¶

Plotting utilities

class skcriteria.plot.DataPlotMethods(data)[source]¶

Bases: object

Data plotting accessor and method

Examples

>>> data.plot()
>>> data.plot.hist()
>>> data.plot.scatter('x', 'y')
>>> data.plot.radar()

These plotting methods can also be accessed by calling the accessor as a method with the kind argument: data.plot(kind='violin') is equivalent to data.plot.violin()

Methods

`__call__`([kind])	Make plots of Data using matplotlib.
`plot`(func[, mnorm, wnorm, anames, cnames, …])	Preprocess the data and send to the plot function func.
`preprocess`(data, mnorm, wnorm, anames, …)	Preprocess the data to be plotted.
`radar`(**kwargs)	Creates a radar chart, also known as a spider or star chart (http://en.wikipedia.org/wiki/Radar_chart).

bars
box
hist
scatter
to_str
violin

plot(func, mnorm='none', wnorm='none', anames=None, cnames=None, cmap=None, weighted=True, show_criteria=True, min2max=False, push_negatives=False, addepsto0=False, **kwargs)[source]¶

Preprocess the data and send to the plot function func.

Parameters:

func : callable: The function that make the plot. The return value of func are the return value of this method.
mnorm: string, callable, optional (default=”none”): Normalization method for the alternative matrix.
wnorm : string, callable, optional (default=”none”): Normalization method for the weights array.
anames : list of str or None, optional (default=None): The list of alternative names to be render in the plot. If is None then the alternative names of data are used.
cnames : list of str or None, optional (default=None): The list of criteria names to be render in the plot. If is None then the criteria names of data are used.
cmap : string or None, optional (default=None): Name of the color map to be used (https://matplotlib.org/users/colormaps.html)
weighted : bool, optional (default=True): If the data must be weighted before redering.
show_criteria : bool, optional (default=True): I the sense of optimality must be rendered in the plot.
min2max : bool, optional (default=False): If true all the data of the minimization criteria are inverted before render.
push_negatives : bool, optional (default=False): If True all the criterias with some value < 0 are incremented to be at least 0 in the minimun value.
addepsto0 : bool, optional (default=False): If true add an small value to all the zeros inside the data.
kwargs :: Arguments to send to func

Returns:

The return value of func.

Notes

All the plot methods of Scikit-Criteria returns a matplotlib axis.

preprocess(data, mnorm, wnorm, anames, cnames, cmap, weighted, show_criteria, min2max, push_negatives, addepsto0)[source]¶

Preprocess the data to be plotted.

Parameters:

data : skcritria.core.Data: The data to be preprocessed.
mnorm: string, callable: Normalization method for the alternative matrix.
wnorm : string, callable: Normalization method for the weights array.
anames : list of str or None: The list of alternative names to be render in the plot. If is None then the alternative names of data are used.
cnames : list of str or None: The list of criteria names to be render in the plot. If is None then the criteria names of data are used.
cmap : string or None: Name of the color map to be used (https://matplotlib.org/users/colormaps.html)
weighted : bool: If the data must be weighted before redering.
show_criteria : bool: I the sense of optimality must be rendered in the plot.
min2max : bool: If true all the data of the minimization criteria are inverted before render.
push_negatives : bool: If True all the criterias with some value < 0 are incremented to be at least 0 in the minimun value.
addepsto0 : bool: If true add an small value to all the zeros inside the data.

Returns:

preprocessed_data : dict: All the data ready to be sended to a plot function

radar(**kwargs)[source]¶

Creates a radar chart, also known as a spider or star chart (http://en.wikipedia.org/wiki/Radar_chart).

A radar chart is a graphical method of displaying multivariate data in the form of a two-dimensional chart of three or more quantitative variables represented on axes starting from the same point. The relative position and angle of the axes is typically uninformative.

Parameters:

frame : {“polygon”, “circle”}: Shape of frame surrounding axes.
ax : None or PolarAxes, optional (default=None): Axis where the radar must be redered. Is is None a new axis are created.
legendcol : int, optional (default=5): How many columns must has the legend.
subplots_kwargs : dict or None, optional (default=None): Argument to send to matplotlib.pyplot.subplots if axis is None. If axis is not None, subplots_kwargs are ignored.

Returns:

ax : matplotlib.projections.polar.PolarAxes: Axis where the radar are rendered

skcriteria.plot package¶

`skcriteria.plot` package¶