def s( d ) :
    ''' Returns the sum of the values in dataset d.
    '''

    # s(d) calculates the sum of all of the elements in the entire dataset
    # Recall d is a dataset, a list of lists.
    # sum( list ) can only be called on a SINGLE list of numbers like sum( [1,2,3] ) = 6

    result = 0 # Accumulator for our sum
    for row in d: # Loop through each list in our dataset (each row in our dataset)
        for number in row:  # Loop through each number in each row
            result = result + number # Add each number from each inner list to our result sum
    return result

    # Alternate Way
    result = 0
    for row in d:
        sum_row = sum( row ) # Call the sum function on each inner list in our dataset
        result = result + sum_row # Add the sum of each row to our result accumulator for the total sum
    return result

    # Anytime we ask you to look at a dataset, if we want you to look at each cell (smaller parts of rows)
    # you want to use a nested loop:
    # for row in dataset:
        # for cell in row:
    # [[1,2,3], [4,5,6]]
    #   ^ Cell value (each value in each row)
    #   row       row

''' DO NOT MODIFY THE BELOW CODE '''
    
if ( __name__ == '__main__' ) :
    import sigma

    d1 = [ [ 0 ],             [ 1, 2 ],             [ 1, 2, 3 ], [ 0 ]       ]
    d2 = [ [ 1, 0, 1, 2, 2 ], [ 3, 0, 1, 1, 1, 0 ], [ 2 ],       [ 0, 0, 1 ] ]
    d3 = [ [ 3, 0, 3],        [ 3, 0, 3, 0, 1],     [ 1, 0, 2 ]              ]
    d4 = [ ]


    s1 = sigma.s( d1 );       print( 's( d1 ) =', s1 )
    s2 = sigma.s( d2 );       print( 's( d2 ) =', s2 )
    s3 = sigma.s( d3 );       print( 's( d3 ) =', s3 )
    s4 = sigma.s( d4 );       print( 's( d4 ) =', s4 )