title: Numpy mean for big array dataset using For loop Python
body: <p>I have big dataset in array form and its arranged like this:</p>
  
  <p><a href="https://i.stack.imgur.com/tciFJ.jpg" rel="nofollow noreferrer">Rainfal amount arranged in array form</a></p>
  
  <p>Average or mean mean for each latitude and longitude at axis=0 is computed using this method declaration:</p>
  
  <pre><code>Lat=data[:,0]
  
  Lon=data[:,1]
  
  rain1=data[:,2]
  
  rain2=data[:,3]
  
  --
  
  rain44=data[:,44]
  
  
  rainT=[rain1,rain2,rain3,rain4,....rain44]
  
  mean=np.mean(rainT)
  </code></pre>
  
  <p>The result was aweseome but requires time computation and I look forward to use For Loop to ease the calculation. As for the moment the script that I used is like this:</p>
  
  <pre><code>mean=[]
  
  lat=data[:,0]
  
  lon=data[:,1]
  
  for x in range(2,46):
  
      rainT=data[:,x]
  
  mean=np.mean(rainT,axis=0)
  
  print mean
  </code></pre>
  
  <p>But weird result is appeared. Anyone? </p>