title: Pandas & seaborn: how to classify survey answers based on predefined criteria
body: <p>I have a survey. with 119 question, each question imported in a df as a column.
  each answer for the survey is a row in the df.</p>
  <p>Most variables are categorical variables, some of them allow multiple answers.</p>
  <p>What I want to do is trying to approach this as the following.</p>
  <div class="s-table-container">
  <table class="s-table">
  <thead>
  <tr>
  <th>Company ID</th>
  <th>Bank Account?</th>
  <th>Accounting Practice</th>
  <th>Accountant?</th>
  <th>External Auditor</th>
  <th>Online Banking?</th>
  </tr>
  </thead>
  <tbody>
  <tr>
  <td>1</td>
  <td>yes</td>
  <td>Accounting system</td>
  <td>Yes</td>
  <td>No</td>
  <td>No</td>
  </tr>
  <tr>
  <td>2</td>
  <td>No</td>
  <td>Book keeping</td>
  <td>Yes</td>
  <td>Yes</td>
  <td>Yes</td>
  </tr>
  <tr>
  <td>3</td>
  <td>Yes</td>
  <td>Accounting system</td>
  <td>Yes</td>
  <td>Yes</td>
  <td>Yes</td>
  </tr>
  </tbody>
  </table>
  </div>
  <p>I want to classify each company (row) as Organized, Semi Organized and Not organized.</p>
  <p>based on their answers to a subset of questions.</p>
  <p>For example, if a company has a bank account, Accounting practice, Accountant, Registered trade name and Tax number</p>
  <p>this company will be labeled as organized.</p>
  <p>I have other criteria for semi organized and other for not organized</p>
  <p>Is this obtainable and how?</p>
  <p>Noting that the end result is trying to cluster it all based on employees segment.
  Since most variables are categorical, it seems I can't cluster them because they are not numerical
  I am a still a beginner in this.
  please help</p>