title: Return the index of a row based on value in different dataframe's row
body: <p>I have two Pandas dataframes. They all contain 3 decimal point float values.</p>
  <p>Dataframe A is a one column dataframe with 12 rows. Dataframe B is a one column dataframe with over 40,000 rows, which contain the 12 values in Dataframe A spread out randomly.</p>
  <p>I need to find the indices of the values in Dataframe A within Dataframe B.</p>
  <p>I have tried <code>.query()</code>, <code>.index.value()</code> and <code>.where()</code> but am unable to return the indices.</p>
  <h3>Dataframe A</h3>
  <div class="s-table-container">
  <table class="s-table">
  <thead>
  <tr>
  <th>Row Index</th>
  <th>Time</th>
  </tr>
  </thead>
  <tbody>
  <tr>
  <td>0</td>
  <td>148.521</td>
  </tr>
  <tr>
  <td>1</td>
  <td>112.379</td>
  </tr>
  <tr>
  <td>...</td>
  <td>...</td>
  </tr>
  <tr>
  <td>12</td>
  <td>510.121</td>
  </tr>
  </tbody>
  </table>
  </div><h2>Dataframe B</h2>
  <div class="s-table-container">
  <table class="s-table">
  <thead>
  <tr>
  <th>Row Index</th>
  <th>Time</th>
  </tr>
  </thead>
  <tbody>
  <tr>
  <td>0</td>
  <td>0.000</td>
  </tr>
  <tr>
  <td>1</td>
  <td>0.025</td>
  </tr>
  <tr>
  <td>...</td>
  <td>...</td>
  </tr>
  <tr>
  <td>46871</td>
  <td>1171.675</td>
  </tr>
  </tbody>
  </table>
  </div>