title: How to load file.npy into a numpy array?
body: <p>I've got a data like this:</p>
  
  <pre><code>934e,554d,5059,0100,4600,7b27,6465,7363
  7227,3a20,273c,6938,272c,2027,666f,7274
  7261,6e5f,6f72,6465,7227,3a20,4661,6c73
  652c,2027,7368,6170,6527,3a20,2831,3030
  3030,302c,292c,207d,2020,2020,2020,200a
  2e03,0000,0000,0000,6f01,0000,0000,0000
  0f00,0000,0000,0000,6202,0000,0000,0000
  1c00,0000,0000,0000,2402,0000,0000,0000
  7302,0000,0000,0000,3001,0000,0000,0000
  9c00,0000,0000,0000,9002,0000,0000,0000
  1302,0000,0000,0000,9301,0000,0000,0000
  </code></pre>
  
  <p>How can I load it to numpy array? I've tried follow the documentation, but nothing was helpful! I've converted this data to txt file and after each, the write like this:</p>
  
  <pre><code>import numpy as np
  data = np.loadtxt('data.txt', delimiter=",")
  print(data)
  </code></pre>
  
  <p>but it results in an error:</p>
  
  <pre><code>Traceback (most recent call last):
    File "/home/cow13/Documents/Assignment5/datastr.py", line 2, in &lt;module&gt;
      data = np.loadtxt('data.txt', delimiter=",")
    File "/usr/lib/python2.7/dist-packages/numpy/lib/npyio.py", line 1024, in loadtxt
      items = [conv(val) for (conv, val) in zip(converters, vals)]
    File "/usr/lib/python2.7/dist-packages/numpy/lib/npyio.py", line 725, in floatconv
      return float(x)
  ValueError: invalid literal for float(): 934e
  </code></pre>