data visualization

import chart_studio.plotly as py
import plotly.graph_objs as go
from plotly.offline import init_notebook_mode, iplot
init_notebook_mode(connected=True)
import plotly
def predreport(y_pred, Y_Test):
    diff = y_pred.flatten() - Y_Test.flatten()
    perc = (abs(diff)/y_pred.flatten())*100
    priority = []
    for i in perc:
        if i > 0.4:
            priority.append(3)
        elif i> 0.1:
            priority.append(2)
        else:
            priority.append(1)
    print("Error Importance 1 reported in ", priority.count(1),
          "cases\n")
    print("Error Importance 2 reported in", priority.count(2), 
          "cases\n")                                 
    print("Error Importance 3 reported in ", priority.count(3),    
          "cases\n")
    colors = ['rgb(102, 153, 255)','rgb(0, 255, 0)', 
              'rgb(255, 153, 51)', 'rgb(255, 51, 0)']
    fig = go.Figure(data=[go.Table(header=
                    dict(
                        values=['Actual Values', 'Predictions', 
                        '% Difference', "Error Importance"],
                        line_color=[np.array(colors)[0]],
                        fill_color=[np.array(colors)[0]],
                                    align='left'),
                    cells=dict(
                       values=[y_pred.flatten(),Y_Test.flatten(),
                               perc, priority], 
                       line_color=[np.array(colors)[priority]],
                       fill_color=[np.array(colors)[priority]],  
                                    align='left'))])
    init_notebook_mode(connected=False)
    py.plot(fig, filename = 'Predictions_Table', auto_open=True)
    fig.show()