title: Pandas - Reverse effect of dropna()?
body: <p>I have a DataFrame with DateTime values as the index which should have daily entries. But in my case, a lot of days are missing from the index (not NaN - they don't exist), I'm assuming due to using dropna somewhere before. I want to add those rows back with NaN values for columns.
  I thought about creating a list that runs from the first date to the last date then looping, indexing, and adding non-existing rows manually. Is there a better way to do it?</p>
  <p>tl;dr: I'm trying to reverse the result of dropna().</p>
  <p>Thanks!</p>