title: How to put a limit in Pandas to the number of rows read from a 'feather' file?
body: <p>I have a <code>feather</code> datafile that weights approximately 300 MB, name it <code>df.ftr</code>. I can read it with Pandas using the following command:</p>
  <pre class="lang-py prettyprint-override"><code>import pandas as pd
  df = pd.read_feather('df.ftr')
  </code></pre>
  <p>However, this dataset contains over 21 million rows and its size overflows my local computer's memory. What I would like to do is to read only the first 1 million rows.</p>
  <p>If it were an <code>df.h5</code> file, I would read it by using the <code>stop</code> argument of the <code>read_hdf</code> method (documentation available <a href="https://pandas.pydata.org/docs/reference/api/pandas.read_hdf.html" rel="nofollow noreferrer">here</a>):</p>
  <pre class="lang-py prettyprint-override"><code>import pandas as pd
  df = pd.read_hdf('df.h5', 'table', stop=1000000)
  </code></pre>
  <p>However, after checking the <a href="https://pandas.pydata.org/docs/reference/api/pandas.read_feather.html" rel="nofollow noreferrer">read_feather()</a> documentation, there is no argument which seems to be able to produce the same effect.</p>
  <p>How can it be done?</p>