'Draw lines that represent standard deviation or quartiles'

def draw_statistics(self):

    return
    if (self.show_statistics and (self.data is not None)):
        data = []
        domain = self.data.domain
        for attr_idx in self.attribute_indices:
            if (not self.domain[attr_idx].is_continuous):
                data.append([()])
                continue
            if ((not domain.class_var) or domain.has_continuous_class):
                if (self.show_statistics == MEANS):
                    m = self.domain_data_stat[attr_idx].mean
                    dev = self.domain_data_stat[attr_idx].var
                    data.append([((m - dev), m, (m + dev))])
                elif (self.show_statistics == MEDIAN):
                    data.append([(0, 0, 0)])
                    continue
                    sorted_array = np.sort(attr_values)
                    if (len(sorted_array) > 0):
                        data.append([(sorted_array[int((len(sorted_array) / 4.0))], sorted_array[int((len(sorted_array) / 2.0))], sorted_array[int((len(sorted_array) * 0.75))])])
                    else:
                        data.append([(0, 0, 0)])
            else:
                curr = []
                class_values = get_variable_values_sorted(self.domain.class_var)
                class_index = self.domain.index(self.domain.class_var)
                for c in range(len(class_values)):
                    attr_values = self.data[(attr_idx, (self.data[class_index] == c))]
                    attr_values = attr_values[(~ np.isnan(attr_values))]
                    if (len(attr_values) == 0):
                        curr.append((0, 0, 0))
                        continue
                    if (self.show_statistics == MEANS):
                        m = attr_values.mean()
                        dev = attr_values.std()
                        curr.append(((m - dev), m, (m + dev)))
                    elif (self.show_statistics == MEDIAN):
                        sorted_array = np.sort(attr_values)
                        curr.append((sorted_array[int((len(attr_values) / 4.0))], sorted_array[int((len(attr_values) / 2.0))], sorted_array[int((len(attr_values) * 0.75))]))
                data.append(curr)
        for i in range(len(data)):
            for c in range(len(data[i])):
                if (data[i][c] == ()):
                    continue
                x = ((i - ((0.03 * (len(data[i]) - 1)) / 2.0)) + (c * 0.03))
                col = QColor(self.discrete_palette[c])
                col.setAlpha(self.alpha_value_2)
                self.add_curve('', col, col, 3, OWCurve.Lines, OWPoint.NoSymbol, xData=[x, x, x], yData=[data[i][c][0], data[i][c][1], data[i][c][2]], lineWidth=4)
                self.add_curve('', col, col, 1, OWCurve.Lines, OWPoint.NoSymbol, xData=[(x - 0.03), (x + 0.03)], yData=[data[i][c][0], data[i][c][0]], lineWidth=4)
                self.add_curve('', col, col, 1, OWCurve.Lines, OWPoint.NoSymbol, xData=[(x - 0.03), (x + 0.03)], yData=[data[i][c][1], data[i][c][1]], lineWidth=4)
                self.add_curve('', col, col, 1, OWCurve.Lines, OWPoint.NoSymbol, xData=[(x - 0.03), (x + 0.03)], yData=[data[i][c][2], data[i][c][2]], lineWidth=4)
        if ((not domain.class_var) or domain.has_continuous_class):
            class_count = 1
        else:
            class_count = len(self.domain.class_var.values)
        for c in range(class_count):
            diff = ((((-0.03) * (class_count - 1)) / 2.0) + (c * 0.03))
            ys = []
            xs = []
            for i in range(len(data)):
                if (data[i] != [()]):
                    ys.append(data[i][c][1])
                    xs.append((i + diff))
                else:
                    if (len(xs) > 1):
                        col = QColor(self.discrete_palette[c])
                        col.setAlpha(self.alpha_value_2)
                        self.add_curve('', col, col, 1, OWCurve.Lines, OWPoint.NoSymbol, xData=xs, yData=ys, lineWidth=4)
                    xs = []
                    ys = []
            col = QColor(self.discrete_palette[c])
            col.setAlpha(self.alpha_value_2)
            self.add_curve('', col, col, 1, OWCurve.Lines, OWPoint.NoSymbol, xData=xs, yData=ys, lineWidth=4)
