title: pandas map makes values NaN
body: <p>I'm trying to map my values that i want to change.
  When i apply 'map' like this >> df[column].map(dictionary), the values that are not in the dictionary convert to NaN. I think the reason is that there are no matched values in the series, right? If so, nothing should be applied instead converting to NaN? How can i solve this problem using df.map() instead of df.replace()?</p>
  
  <pre><code>df1 = pd.Series(['a','b','c','d'])
  df
  0    a
  1    b
  2    c
  3    d
  dtype: object
  
  mapping = {'a' : 0, 'b' : 1, 'c' : 2}
  df1.map(mapping)
  0    0.0
  1    1.0
  2    2.0
  3    NaN
  dtype: float64
  </code></pre>
  
  <p>or</p>
  
  <pre><code>df1 = pd.Series(['a','b','c','d'])
  df
  0    a
  1    b
  2    c
  3    d
  dtype: object
  
  mapping = {'k' : 0, 'e' : 1, 'f' : 2}
  df1.map(mapping)
  
  0   NaN
  1   NaN
  2   NaN
  3   NaN
  dtype: float64
  </code></pre>