title: appending nan rows according to difference of two row value
body: <p>Hello i have a dataframe like:</p>
  <pre><code>df1
       A   B
  0  0.7   7
  1  1.0  10
  2  1.2  12
  3  1.4  14
  4  1.8  18
  5  14   7
  6  17   10
  </code></pre>
  <p>I am trying to append nan rows according to difference between column B rows. I mean, for example, column B row 0 and row 1, has difference value 3. So i need to append 2 nan rows to have continuous integer values between them. And then I am going to do interpolation between them. Because i have large scale data and i need to do it fast, i thought it is better to do it with pandas, so please tell me pandas solution. Should i iterate them? what do you think? Final dataframe will look like this:</p>
  <pre><code>       0    1
  0   0.07    7
  1   0.08    8
  2   0.09    9
  3   0.10    10
  4   0.11    11
  5   0.12    12
  6   0.13    13
  7   0.14    14
  8   0.15    15
  9   0.16    16
  10  0.17    17
  11  0.18    18
  12  14.00   7
  13  16.00   8
  14  18.00   9
  15  17.00   10
  </code></pre>
  <p>That's why i am trying to get this:</p>
  <pre><code>    0          1
  0   0.07     7.0
  1   NaN      NaN
  2   NaN      NaN
  3   0.10    10.0
  4   0.11    11.0
  5   0.12    12.0
  6   NaN      NaN
  7   0.14    14.0
  8   0.15    15.0
  9   NaN      NaN
  10  NaN      NaN
  11  0.18    18.0
  12  14.00    7.0
  13  NaN      NaN
  14  NaN      NaN
  15  17.00   10.0
  </code></pre>
  <p>I am searching the most pythonic way, the best way for data science? Thanks.</p>