title: Delete rows in Dataframe based on condition
body: <p>Let us say I have a dataframe : </p>
  
  <pre><code>first_df = pd.DataFrame({"company" : ['abc','def','xyz','lmn','def','xyz'], 
                                  "art_type": ['300x240','100x600','400x600','300x240','100x600','400x600'],
                                  "metrics" : ['imp','rev','cpm','imp','rev','cpm'],
                                  "value": [1234,23,0.5,1234,23,0.5]})
  first_df = first_df.append(first_df)
  </code></pre>
  
  <p>I want to remove all the rows which have a value for company in the list ['lmn','xyz'] and store that in another dataframe. </p>
  
  <pre><code>company_list = ['lmn', 'xyz']
  </code></pre>
  
  <p>I tried this : </p>
  
  <pre><code>deleted_data = first_df[first_df['company'] in company_list] 
  </code></pre>
  
  <p>this obviously did not work because it is list in list. Is for loop the way to do this or is there any better way to do it?</p>
  
  <p>for loop code : </p>
  
  <pre><code>deleted_data = pd.DataFrame()
  for x in company_list:
      deleted_data = deleted_data.append(first_df[first_df['company']==x])
  </code></pre>