title: Extract integers after double space with regex
body: <p>I have a dataframe where I want to extract stuff after double space. For all rows in column <code>NAME</code> there is a double white space after the company names before the integers.</p>
  
  <pre><code>                                    NAME  INVESTMENT  PERCENT
  0     APPLE COMPANY A  57 638 232 stocks     OIL LTD  0.12322
  1  BANANA 1 COMPANY B  12 946 201 stocks    GOLD LTD  0.02768
  2     ORANGE COMPANY C  8 354 229 stocks     GAS LTD  0.01786
  
  df = pd.DataFrame({
      'NAME': ['APPLE COMPANY A  57 638 232 stocks', 'BANANA 1 COMPANY B  12 946 201 stocks', 'ORANGE COMPANY C  8 354 229 stocks'],
      'PERCENT': [0.12322, 0.02768 , 0.01786]
      })
  </code></pre>
  
  <p>I have this earlier, but it also includes integers in the company name:</p>
  
  <pre><code>df['STOCKS']=df['NAME'].str.findall(r'\b\d+\b').apply(lambda x: ''.join(x))
  </code></pre>
  
  <p>Instead I tried to extract after double spaces</p>
  
  <pre><code>df['NAME'].str.split('(\s{2})')
  </code></pre>
  
  <p>which gives output:</p>
  
  <pre><code>0       [APPLE COMPANY A,   , 57 638 232 stocks]
  1    [BANANA 1 COMPANY B,   , 12 946 201 stocks]
  2       [ORANGE COMPANY C,   , 8 354 229 stocks]
  </code></pre>
  
  <p>However, I want the integers that occur after double spaces to be joined/merged and put into a new column. </p>
  
  <pre><code>                 NAME  PERCENT  STOCKS
  0     APPLE COMPANY A  0.12322  57638232
  1  BANANA 1 COMPANY B  0.02768  12946201
  2    ORANGE COMPANY C  0.01786  12946201
  </code></pre>
  
  <p>How can I modify my second function to do what I want?</p>