title: remove row in pandas column based on "if string in cell" condition
body: <p>I have a dataframe with some columns, one of this is <code>Text</code> that contains some text (obv).</p>
  
  <p>Several cells of this columns have "no text" in there, but I have noticed ( I don't know why) that there are some spaces: for example in some rows I have <code>"no text"</code> in others <code>" no text"</code> , <code>"  no text  "</code> and <code>"  no text  "</code> and so on.</p>
  
  <p>I thought to use a condition like this to remove the rows whose column <code>Text</code> misses it:</p>
  
  <pre><code>data = data.drop(data['no text' in data['Text']].index)
  </code></pre>
  
  <p>but gives me some errors (<code>KeyError: '[False] not found in axis'</code>)
  I know that for stuff like this, one have to pass a boolean condition, <code>df = df.drop(df[boolean_cond])</code>  so what am I doing wrong?</p>