title: Python Memory Error encountered when replacing NaN values in large Pandas dataframe
body: <p>I have a very large pandas dataframe: ~300,000 columns and ~17,520 rows. The pandas dataframe is called <code>result_full</code>. I am attempting to replace all of the strings <code>"NaN"</code> with <code>numpy.nan</code>:</p>
  
  <pre><code>result_full.replace(["NaN"], np.nan, inplace = True)
  </code></pre>
  
  <p>Here is where I get <code>MemoryError</code> Is there a memory efficient way to drop these strings in my dataframe? I tried <code>result_full.dropna()</code> but it didn't work because they are technically string that are "NaN"</p>