title: Whey saving an numpy array of float arrays to .npy file using numpy.save/numpy.load, is there any reason why the order of the arrays would change?
body: <p>I currently have data where each row has a text passage and a numpy float array. </p>
  
  <p>As far as I know, the it's not efficient to save these two datatypes into one data format (correct me if I am wrong). So I am going to save them separately, with another column of ints that will be used to map the two datasets together when I want to join them again. </p>
  
  <p>I have having trouble figuring out how to append a column of ints next to the float arrays (if anyone has a solution to that I would love to hear it) and then save the numpy array.  </p>
  
  <p>But then I realized I can just save the float arrays as is with numpy.save without the extra int column if I can get a confirmation that numpy.save and numpy.load will never change the order of the arrays.</p>
  
  <p>That way I can just append the loaded numpy float arrays to the pandas dataframe as is. </p>
  
  <p>Logically, I don't see any reason why the order of the rows would change, but perhaps there's some optimization compression that I am unaware of. </p>
  
  <p>Would numpy.save or numpy.load ever change the order of a numpy array of float arrays? </p>