title: Pandas: Change df column values based on condition with iloc
body: <p>Take a dataframe, say<br></p>
  
  <pre><code>df = pd.DataFrame([[1,2],[3,4],[5,6]],columns=['A','B'])
  
     A  B
  0  1  2
  1  3  4
  2  5  6
  </code></pre>
  
  <p>Now I want to change cells in the first column.<br>
  I can do it this way:<br></p>
  
  <pre><code>df.loc[df['A'] &gt; 1,'A'] = 10
  
      A  B
  0   1  2
  1  10  4
  2  10  6
  </code></pre>
  
  <p>But what if i don't have any column names?
  <br>
  <code>df.iloc[:,0] &gt; 1</code> gives me the same mask as <code>df['A'] &gt; 1</code>
  <br>
  And while</p>
  
  <pre><code>df.loc[df.iloc[:,0] &gt; 1,'A'] = 10
  </code></pre>
  
  <p>works perfectly fine,</p>
  
  <p>using<br></p>
  
  <pre><code>df.iloc[df.iloc[:,0] &gt; 1,1] = 10
  </code></pre>
  
  <p>on the initial df somehow return this error:
  <br></p>
  
  <blockquote>
    <p>NotImplementedError: iLocation based boolean indexing on an integer type is not available</p>
  </blockquote>
  
  <p>Is there a way to change specific cells using only integer indexing?</p>