title: How to only extract Close prices from Dataframe Pandas
body: <p>I can't find a method to loop over my data frame (<code>df_yf</code>) and extract all the &quot;Close&quot; prices and create a new <code>df_adj</code>. The df is group_by coin price.</p>
  <p><a href="https://i.stack.imgur.com/sBfb4.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/sBfb4.png" alt="enter image description here" /></a></p>
  <p>Initially, I tried something like but throwing me error.</p>
  <pre><code>for i in range(len(df_yf.columns):
        df_adj.append(df_yf[i][&quot;Close&quot;])
  </code></pre>
  <p>Also tried using <code>.get</code> and <code>.filter</code> but throws me errors</p>
  <blockquote>
  <p>&quot;list indices must be integers or slices, not str; perhaps you missed
  a comma?&quot;</p>
  </blockquote>
  <p>EDIT!!</p>
  <p>Thank you for the answers. It made me realize my mistake :D. I shouldn't group_by tickers so I changed it to group_by prices (Low, Close etc.) and then was able to simply extract the right columns by doing df_adj = df_yf[&quot;Close&quot;] as was mentioned</p>