title: Replace pandas column values with dictionary values
body: <p>I have a dictionary like as shown below</p>
  <pre><code>OUTPUT = {'supplier': {0: 'ABCD',
    1: 'DEFG',
    2: 'GHIK',
    3: 'JKL'},
   'region': {0: 'KOREA',
    1: 'AUS/NZ',
    2: 'INDIA',
    3: 'ASEAN',
    4: 'HK / CHINA'}}
  
  ID,supplier,region,subject
  1, 0, 3, TEST
  2, 1, 2, EXAM
  3, 3, 4, VIVA
  
  df = pd.read_clipboard(sep=',')
  </code></pre>
  <p>I would like to replace the values in column <code>supplier</code> and <code>region</code> with their corresponding mapping value from the dictionary</p>
  <p>I tried the below</p>
  <pre><code>df[&quot;supplier&quot;].replace(output) # not works
  df['supplier'].map(output) # not works
  </code></pre>
  <p>But this threw an error as shown below</p>
  <blockquote>
  <p>AttributeError: 'Series' object has no attribute '_replace_columnwise'</p>
  </blockquote>
  <p>I expect my output to be like as shown below</p>
  <pre><code>ID,supplier,region,subject
  1, ABCD, ASEAN, TEST
  2, DEFG, INDIA, EXAM
  3, JKL, HK/CHINA, VIVA
  </code></pre>