title: Pandas: df.groupby() is too slow for big data set. Any alternatives methods?
body: <p>I have a pandas.DataFrame with 3.8 Million rows and one column, and I'm trying to group them by index.</p>
  <p>The index is the customer ID. I want to group the <code>qty_liter</code> by the index:</p>
  <p><code>df = df.groupby(df.index).sum()</code></p>
  <p>But it takes forever to finish the computation. Are there any alternative ways to deal with a very large data set?</p>
  <p>Here is the <code>df.info()</code>:</p>
  <pre><code>&lt;class 'pandas.core.frame.DataFrame'&gt;
  Index: 3842595 entries, -2147153165 to \N
  Data columns (total 1 columns):
  qty_liter    object
  dtypes: object(1)
  memory usage: 58.6+ MB
  </code></pre>
  <p>The data looks like this:</p>
  <p><a href="https://i.stack.imgur.com/2rqA7.png" rel="noreferrer"><img src="https://i.stack.imgur.com/2rqA7.png" alt="enter image description here" /></a></p>