title: Pandas split column in several columns throug string replacement or regex
body: <p>I have a 'Column' in my dataframe that, in optimal conditions, looks like this:</p>
  
  <pre><code>Client: Stack Overflow   Order Num: 123456  Account From: 3656645654   Account to: 546546578
  
  </code></pre>
  
  <p>I want to split this column in several columns like:</p>
  
  <pre><code>'Client','Order Num', 'Account From','Account to'
  </code></pre>
  
  <p>But in some cases i don't have the client, order num and accounts in the column</p>
  
  <p>I'am doing it in this way:</p>
  
  <pre><code>for x in len(df.columns):
     if 'Client' in df.loc[x,'Columnn']:
        df.loc[x,'Client'] = str(df.loc[x,'Column']).split('Client: ')[1]
        if 'Order Num' in df.loc[x,'Client']:
           df.loc[x,'Client'] = str(df.loc[x,'Client']).split('Order Num: ')[0]
        if 'Account From' in df.loc[x,'Client']:
           df.loc[x,'Client'] = str(df.loc[x,'Client']).split('Account From: ')[0]
        if 'Account to' in df.loc[x,'Client']:
           df.loc[x,'Client'] = str(df.loc[x,'Client']).split('Account to: ')[0]
     else:
        df.loc[x,'Client'] = ''
  
  </code></pre>
  
  <p>And so on for all the columns I want to create.</p>
  
  <p>This part of the script is almost 40 lines and is very slow.</p>
  
  <p>Do you have a more 'pandastic' solution?</p>