title: Map column of dataframe with different dictionaries
body: <p>I have a dataframe df with two columns.</p>
  <p>The 'data' column has some values, such as:</p>
  <pre><code>df['data'] = [0, 1, 0, 1]
  </code></pre>
  <p>The 'Dict' column has multiple dictionary, such as:</p>
  <pre><code>df['Dict'] = [{0: ['IPM_0'], 1: ['IPM_1']},
                {0: ['SPM_0'], 1: ['SPM_1']},
                {0: ['NPM_0'], 1: ['NPM_1']},
                {0: ['DPM_0'], 1: ['DPM_1']}]
  </code></pre>
  <p>Now I want to map each 'data'with the relative dictionary in 'Dict', such as that the result looks like:</p>
  <pre><code>df['result'] = [IPM_0, SPM_1, NPM_0, DPM_1]
  </code></pre>
  <p>I tried to use <code>df['result'] = df.data.map(df.Dict)</code> but I get a column with the same values as in df.Dict.</p>
  <p>I tried also <code>df['result'] = df.data.apply(lambda rows: rows.map(rows.Dict))</code> but I get an error  <code>'int' object has no attribute 'map'</code></p>
  <p>How can I achieve the result?</p>
  <p>starting point:</p>
  <pre><code>   data                          Dict
  0     0  {0: ['IPM_0'], 1: ['IPM_1']}
  1     1  {0: ['SPM_0'], 1: ['SPM_1']}
  2     0  {0: ['NPM_0'], 1: ['NPM_1']}
  3     1  {0: ['DPM_0'], 1: ['DPM_1']}
  </code></pre>
  <p>ending point:</p>
  <pre><code>   data                          Dict result
  0     0  {0: ['IPM_0'], 1: ['IPM_1']}  IPM_0
  1     1  {0: ['SPM_0'], 1: ['SPM_1']}  SPM_1
  2     0  {0: ['NPM_0'], 1: ['NPM_1']}  NPM_0
  3     1  {0: ['DPM_0'], 1: ['DPM_1']}  DPM_1
  </code></pre>