title: Memory Error in Python 3 and Windows 64
body: <p>I know Memory Error related questions have been asked before, for example <a href="https://stackoverflow.com/q/18282867/4701426">here</a>, <a href="https://stackoverflow.com/q/44508254/4701426">here</a>, <a href="http://grokbase.com/t/python/python-list/102db8s7pb/memoryerror-can-i-use-more" rel="nofollow noreferrer">here</a>, <a href="https://stackoverflow.com/q/23870828/4701426">here</a>, or <a href="https://stackoverflow.com/q/48832479/4701426">here</a>. And the suggested solutions always are to switch to Python 3 and/or to Window 64bit, or in case of faulty code, to fix the code. However, I am already on Python 3 and Win 64. I also can see from windows task manager that I have several GB of my 64GB of RAM still available when Python throw the Memory Error.</p>
  
  <p>I have about 15 date-indexed, pandas data frames each with 14000 rows and on average 5000 columns of float data, and about 40-50% NaN values, that I read in from the hard drive. I can not simply drop NaNs because different columns have NaNs at different dates. Memory Error happens when I try to concatenate them with <code>pd.concat()</code>. So it's not a matter of some faulty code or while loop. If I leave some of the data frames out of concatenation, Memory Error does not happen in concatenation, but then when I try to do a Scikit learn decision tree analysis on the concatenated data, it happens.</p>
  
  <p><strong>My question</strong> is how can I get Python to use all the available memory and not throw Memory Error?</p>
  
  <p><strong>Edit</strong>: screenshots added
  IPython interpreter screenshot (I don't have Python 2 even installed):
  <a href="https://i.stack.imgur.com/BBdUh.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/BBdUh.png" alt="enter image description here"></a></p>
  
  <p>System information screenshot:
  <a href="https://i.stack.imgur.com/Pwu6Q.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/Pwu6Q.png" alt="enter image description here"></a></p>