title: Removing dataframe rows using a list of ints
body: <p>I have a dataframe. It contains <code>df['article_id']</code>. I'm using <code>to_sql</code> function with <code>sqlalchemy</code> to insert into my database. However, sometimes I have duplicate records that I want to remove before inserting.</p>
  
  <p>This is my list:</p>
  
  <pre><code>usedIDs = []
  select_st = select([article_table])
  res = conn.execute(select_st)
  for _row in res:
      clean = int(_row[1])
      usedIDs.append(clean)
  
  usedIDs
  </code></pre>
  
  <p>With output: </p>
  
  <pre><code>[1202623831,
   1747352473,
   1748645480,
   1759957596,
   1811054956,
   1812183879,
   1816974229,
   2450784233,
   2579244390,
   2580336884]
  </code></pre>
  
  <p>What i've tried:</p>
  
  <pre><code>df[~df.isin(usedIDs)]
  df.drop(usedIDs, axis=0)
  </code></pre>
  
  <p>And this does not work.
  However when I hardcode it like below, it does work.</p>
  
  <pre><code>df = df[~df.article_id.isin(['1202623831','1747352473'])]
  </code></pre>
  
  <p>Error is either <code>unhashable</code> or <code>KeyError: not found in axis</code>.</p>
  
  <p>How can I drop the rows from my dataframe where <code>df['article_id']</code> is in <code>usedIDs</code> list?</p>