title: Extract values from array type of column in pandas
body: <p>I am trying to extract the location codes / product codes from a sql table using pandas. The field is an array type, i.e. it has multiple values as a list within each row. I have to extract values from string for product/location codes.</p>
  <p><strong>Here is a sample of the table</strong></p>
  <pre><code>df.head()
  Target_Type Constraints
  45          ti_8188,to_8188,r_8188,trad_8188_1,to_9258,ti_9258,r_9258,trad_9258_1   
  45          ti_8188,to_8188,r_8188,trad_8188_1,trad_22420_1   
  45          ti_8894,trad_8894_0.2
  </code></pre>
  <p>Now I want to extract the numeric values of the codes. I also want to ignore the end float values after 2nd underscore in the entries, i.e. ignore the _1, _0.2 etc.</p>
  <p>Here is a sample output I want to achieve. It should be unique list/df column of all the extracted values -</p>
  <pre><code> Target_Type_45_df.head()
   Constraints
   8188
   9258
   22420
   8894
  </code></pre>
  <p>I have never worked with nested/array type of column before. Any help would be appreciated.</p>