title: How to use startswith in loc for a dataframe ? Or merger dataframe columns ignoring None?
body: <p>is there a way to use startswith in a loc function to assign a column value to an other column based on the first column value ?</p>
  <p>I've tried :</p>
  <pre><code>inventory_at_date.loc[inventory_at_date[&quot;asset_class&quot;].str.contains('Cash'), &quot;security_class&quot;] = inventory_at_date[&quot;asset_class&quot;]
  </code></pre>
  <p>but I get</p>
  <pre><code>ValueError: Cannot mask with non-boolean array containing NA / NaN values
  </code></pre>
  <p>Ex :
  Column &quot;asset class&quot; contains</p>
  <pre><code>0    Cash EUR
  1        None
  2        None
  3        None
  4        None
  5        None
  </code></pre>
  <p>Column &quot;security class&quot; contains</p>
  <pre><code>0        None
  1        Equity
  2        Equity
  3        Equity
  4        Equity
  5        Equity
  </code></pre>
  <p>Result wanted in &quot;security class&quot; column:</p>
  <pre><code>0        Cash EUR
  1        Equity
  2        Equity
  3        Equity
  4        Equity
  5        Equity
  </code></pre>
  <p>Is there better way to do it ?</p>
  <p>Thanks</p>