output_description: Print the distance where $p = 1, 2, 3$ and $\infty$ in a line respectively.
  The output should not contain an absolute error greater than 10-5.
input_description: In the first line, an integer $n$ is given. In the second and third line, $x =
  \\{x_1, x_2, ... x_n\\}$ and $y = \\{y_1, y_2, ... y_n\\}$ are given
  respectively. The elements in $x$ and $y$ are given in integers.
attempt: mark_list = [1, 2, 3, "∞"]
  n = int(input())
  element_x = [int(i) for i in input().split()]
  element_y = [int(l) for l in input().split()]
  for p in mark_list:
      if p == 1:
          m_distance = 0
          for o in range(n):
              x = element_x[o]
              y = element_y[o]
              m_distance += abs(x - y)
          print(m_distance)
      if p == 2:
          y_distance = 0
          y_distance2 = 0
          for m in range(n):
              x = element_x[m]
              y = element_y[m]
              y_distance2 += pow(abs(x - y), 2)
          y_distance = pow(y_distance2, 0.5)
          print(y_distance)
      if p == 3:
          third_distance = 0
          third_distance2 = 0
          for q in range(n):
              x = element_x[q]
              y = element_y[q]
              third_distance2 += pow(abs(x - y), 3)
          third_distance = pow(third_distance2, 1 / 3)
          print(third_distance)
      if p == "∞":
          c_distance = 0
          difference = 0
          for r in range(n):
              x = element_x[r]
              y = element_y[r]
              difference = abs(x - y)
              if difference > c_distance:
                  c_distance = difference
          print(c_distance)
  
problem_description: Distance II
  
    
  
  Your task is to calculate the distance between two $n$ dimensional vectors $x
  = \\{x_1, x_2, ..., x_n\\}$ and $y = \\{y_1, y_2, ..., y_n\\}$.
  
  The Minkowski's distance defined below is a metric which is a generalization
  of both the Manhattan distance and the Euclidean distance.  
  \\[ D_{xy} = (\sum_{i=1}^n |x_i - y_i|^p)^{\frac{1}{p}} \\]  
  It can be the Manhattan distance  
  \\[ D_{xy} = |x_1 - y_1| + |x_2 - y_2| + ... + |x_n - y_n| \\]  
  where $p = 1 $.  
    
  It can be the Euclidean distance  
  \\[ D_{xy} = \sqrt{(|x_1 - y_1|)^{2} + (|x_2 - y_2|)^{2} + ... + (|x_n -
  y_n|)^{2}} \\]  
  where $p = 2 $.  
    
  Also, it can be the Chebyshev distance  
    
  \\[ D_{xy} = max_{i=1}^n (|x_i - y_i|) \\]  
    
  where $p = \infty$
  
  Write a program which reads two $n$ dimensional vectors $x$ and $y$, and
  calculates Minkowski's distance where $p = 1, 2, 3, \infty$ respectively.
samples: [{"input": "1 2 3\n    2 0 4", "output": ".000000\n    2.449490\n    2.154435\n    2.000000"}]