title: Pandas add row at index 0 with dummy values
body: <p>To this dataframe <code>df</code>:</p>
  <pre><code>        Player   Team  Points  Mean   Price   Value
  Gameweek                                                                 
  1       Jim  Leeds     4.4   4.40  10.44         0.44
  2       Jim  Leeds     8.9   6.65  12.97         2.53
  3       Jim  Leeds    -1.8   3.83  10.70        -2.27
  </code></pre>
  <p>I need to add a new row at index 0, and fill it with some dummy values, plus an open price. For that I'm trying:</p>
  <pre><code>df.loc[-1] = [df['Player'].item(), 
                df['Team'].item(),
                0.0, 
                0.0, 
               (df['Price'].item() - df['Value'].item()),
                0.0]  
  df.index = df.index +1  # shifting index
  df = df.sort_index()  # sorting by index then resseting
  </code></pre>
  <p>In order to end up with:</p>
  <pre><code>        Player   Team  Points  Mean   Price   Value
  Gameweek  
  0       Jim  Leeds     0.0   0.0   10.00         0.00                                           
  1       Jim  Leeds     4.4   4.40  10.44         0.44
  2       Jim  Leeds     8.9   6.65  12.97         2.53
  3       Jim  Leeds    -1.8   3.83  10.70        -2.27
  </code></pre>
  <p>But I'm getting:</p>
  <pre><code>df.loc[-1] = [df['Player'].item(), 
  return self.values.item()
  ValueError: can only convert an array of size 1 to a Python scalar
  </code></pre>
  <hr />
  <p>What am I missing?</p>