title: Populating a Pandas dataframe where index and column are values of another dataframe
body: <p>I have a dataframe with columns ['ID', 'DATE', 'VALUE']. The way that the data I am sourcing comes in, I have many duplicate IDs, each of which has a duplicate price--so, for instance, the frame will come in with</p>
  
  <pre><code>ID  Date   Value
  a  1/1/17    2
  a  1/2/17    3
  a  1/3/17    4
  b  1/1/17    5
  b  1/2/17    6
  b  1/2/17    7
  </code></pre>
  
  <p>I have made a frame where the date is the index, and unique IDs are the columns, via </p>
  
  <pre><code>ID = list(set(df['ID']))
  DATE = list(set(df['DATE']))
  newdf = pd.DataFrame(columns = ID, index = DATE).sort()
  </code></pre>
  
  <p>I now want to retrieve the Value from df, and place it so that newdf[DATE][ID] matches up with the those indices from df, and I can't figure out how to cast those without some onerous for loops--is there a better way?</p>