def dictionary_of_metrics(items):

    """This function receives a list of values as and input then calculated the mean, median, variance,
     standard deviation, min, and the maximum value in the list 
     this fuction then returs a dictionary.

     Example
     --------

        Input: dictionary_of_metrics([39660.0, 36024.0, 32127.0, 39488.0,
                                        18422.0, 23532.0, 8842.0, 37416.0, 16156.0, 18730.0, 19261.0, 25275.0])

        Output: dictionary_of_metrics(gauteng) == {'mean': 26244.42, 'median': 24403.5, 'var': 108160153.17, 'std': 10400.01, 
                                                   'min': 8842.0 , 'max': 39660.0}


    """
    #Importing the module
    import numpy as np
    
    #Assigning required data to metric_dict
    items = np.array(items)
    metric_dict = {'mean': round(np.mean(items),2),'median': round(np.median(items),2), 
                    'var': round(np.var(items, ddof = 1),2),'std': round(np.std(items, ddof = 1),2), 
                    'min': round(np.min(items),2), 'max': round(np.max(items),2)}

    return metric_dict