title: Splitting String numerical values into new columns-Pandas Dataframe
body: <p>I have a dataframe column having values like this:</p>
  
  <pre><code>Salary Offered
  ----------------------
  £18,323 per annum 
  £18,000 - £22,000 per annum 
  Salary not specified 
  £15,000 - £17,000 per annum, pro-rata 
  £37,000 - £45,000 per annum 
  £9,100 - £9,152 per annum, OTE 
  £9.25 - £10.15 per hour 
  £35,000 - £40,000 per annum 
  £23,000 - £26,600 per annum 
  £18,000 - £25,000 per annum, inc benefits 
  </code></pre>
  
  <p>So I ran the following command, which did a good job by replacing the pure string values (like: "Salary not specified") with None, which I can replace with random values, but I have to again split them by £:</p>
  
  <pre><code>In[13]: df = pd.DataFrame(df.salary_offered.str.split('£',1).tolist(),
                                     columns = ['flips','row'])
  In[14]: df['row']
  Out[14]: 
  0                                     18,323 per annum 
  1                           18,000 - £22,000 per annum 
  2                                                  None
  3                 15,000 - £17,000 per annum, pro-rata 
  4                           37,000 - £45,000 per annum 
  5                        9,100 - £9,152 per annum, OTE 
  6                               9.25 - £10.15 per hour 
  7                           35,000 - £40,000 per annum 
  8                           23,000 - £26,600 per annum 
  9             18,000 - £25,000 per annum, inc benefits 
  </code></pre>
  
  <p>Also there are few rows having salaries given in per hour, so will need to replace them as well, which can be done, intuitively. But I want to separate into different columns having the mean values, something like this:</p>
  
  <pre><code>Salary (£)
  ---------------
  18323
  20000
  18000
  16000
  41000
  ...
  </code></pre>