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: n = int(input())
  x = input().strip().split()
  y = input().strip().split()
  x = [float(s) for s in x]
  y = [float(s) for s in y]
  
  m_d = 0
  y_d = 0
  u_d = 0
  
  mmm = [0] * n
  md = 0
  for i in range(n):
  
      md = abs(x[i] - y[i])
      m_d += md
      y_d += md**2
      u_d += md**3
      mmm[i] = md
  
  
  print(m_d)
  print(y_d**0.5)
  print(u_d ** (1 / 3))
  print(max(mmm))
  
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"}]