title: Pandas Dataframe, easier syntax to drop rows by condition on values
body: <p>Consider a Pandas Dataframe like:</p>
  
  <pre><code>df = pd.DataFrame([[0,2],[1,0],[7,99]],index=[3,4,8], columns = ["R1","R2"])
  </code></pre>
  
  <p>Giving:</p>
  
  <pre><code>   R1  R2
  3   0   2
  4   1   0
  8   7  99
  </code></pre>
  
  <p>When I want to remove a row via a condition on a value I either use</p>
  
  <pre><code>df = df.drop(df[df["R1"] == 1].index)
  </code></pre>
  
  <p>Or </p>
  
  <pre><code>df = df.drop(df.index[np.where(df["R1"] == 1)[0]])
  </code></pre>
  
  <p>Or</p>
  
  <pre><code>df = df.drop(df.loc[df['R1'] == 1].index)
  </code></pre>
  
  <p>Both is super cumbersome. Do you know a easier syntax to achieve this?</p>
  
  <p>For example, if there was something like a idrop function, the second option would be more readably:</p>
  
  <pre><code>df = df.idrop(np.where(df["R1"] == 1)[0])
  </code></pre>
  
  <p>EDIT:</p>
  
  <p>I had assumed that <code>df = df[df['R1'] != 1]</code> is less performant then just dropping a row. (Huge Database...)</p>