title: How to add values to new column according to conditions?
body: <p>I am trying to put a new column to my dataset according to condition, however, resulting dataframe is not what I am expecting.</p>
  
  <p>I've tried some approaches and this is closest what I've been.</p>
  
  <pre><code>import pandas as pd
  
  data = {'Date' : ['3-Mar', '20-Mar', '20-Apr', '21-Apr', '29-Apr', '7- 
           May', '30-May', '31-May', '7-Jun', '16-Jun',
          '1-Jul', '2-Jul', '10-Jul'],
          'Value' : [0.5840, 0.8159, 0.7789, 0.7665, 0.8510, 0.7428, 0.7124, 
          0.6820, 0.8714, 0.8902, 0.8596, 0.8289, 0.6877],}
  frame = pd.DataFrame(data)
  
  for counter, value in enumerate(frame['Value']):
      if value &gt;= 0.7:
          frame = frame.append({'result': 'High'}, ignore_index=True)   
      else:
          frame = frame.append({'result': 'Low'}, ignore_index=True)   
  
  print(frame)
  </code></pre>
  
  <p>Result is:</p>
  
  <pre><code>     Date   Value result
  0    3-Mar  0.5840    NaN
  1   20-Mar  0.8159    NaN
  2   20-Apr  0.7789    NaN
  3   21-Apr  0.7665    NaN
  4   29-Apr  0.8510    NaN
  5    7-May  0.7428    NaN
  6   30-May  0.7124    NaN
  7   31-May  0.6820    NaN
  8    7-Jun  0.8714    NaN
  9   16-Jun  0.8902    NaN
  10   1-Jul  0.8596    NaN
  11   2-Jul  0.8289    NaN
  12  10-Jul  0.6877    NaN
  13     NaN     NaN    Low
  14     NaN     NaN   High
  15     NaN     NaN   High
  16     NaN     NaN   High
  17     NaN     NaN   High
  18     NaN     NaN   High
  19     NaN     NaN   High
  20     NaN     NaN    Low
  21     NaN     NaN   High
  22     NaN     NaN   High
  23     NaN     NaN   High
  24     NaN     NaN   High
  25     NaN     NaN    Low
  </code></pre>
  
  <p>However, I am expecting that values will be placed next to the existing ones not new ones.</p>
  
  <p>Thank you!</p>