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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def plot_data(self, which_data_rows='all', which_data_ycols='all', visible_dims=None, projection='2d', label=None, **plot_kwargs):
 """ Plot the training data - For higher dimensions than two, use fixed_inputs to plot the data points with some of the inputs fixed. Can plot only part of the data using which_data_rows and which_data_ycols. :param which_data_rows: which of the training data to plot (default all) :type which_data_rows: 'all' or a slice object to slice self.X, self.Y :param which_data_ycols: when the data has several columns (independant outputs), only plot these :type which_data_ycols: 'all' or a list of integers :param visible_dims: an array specifying the input dimensions to plot (maximum two) :type visible_dims: a numpy array :param {'2d','3d'} projection: whether to plot in 2d or 3d. This only applies when plotting two dimensional inputs! :param str label: the label for the plot :param kwargs plot_kwargs: kwargs for the data plot for the plotting library you are using :returns list: of plots created. """

    canvas, plot_kwargs = pl().new_canvas(projection=projection, **plot_kwargs)
    plots = _plot_data(self, canvas, which_data_rows, which_data_ycols, visible_dims, projection, label, **plot_kwargs)
    return pl().add_to_canvas(canvas, plots)