title: np.where multiple return values
body: <p>Using pandas and numpy I am trying to process a column in a dataframe, and want to create a new column with values relating to it. So if in column x the value 1 is present, in the new column it would be a, for value 2 it would be b etc</p>
  
  <p>I can do this for single conditions, i.e </p>
  
  <pre><code>df['new_col'] = np.where(df['col_1'] == 1, a, n/a)
  </code></pre>
  
  <p>And I can find example of multiple conditions i.e if x = 3 or x = 4 the value should a, but not to do something like if x = 3 the value should be a and if x = 4 the value be c.</p>
  
  <p>I tried simply running two lines of code such as :</p>
  
  <pre><code>df['new_col'] = np.where(df['col_1'] == 1, a, n/a)
  df['new_col'] = np.where(df['col_1'] == 2, b, n/a)
  </code></pre>
  
  <p>But obviously the second line overwrites. Am I missing something crucial?</p>