title: How to normalize data from a csv file within a specific range
body: <p>I have a csv file as follows:</p>
  
  <p>1,1.23,1.53,1.22,0.96,0.24,1.22,1.22,2.12,0.76,0.99<BR>
  2,1.17,1.52,0.67,0.93,0.14,1.60,1.23,2.22,0.55,0.65<BR>
  3,2.21,1.52,0.66,0.33,0.15,1.72,1.18,1.45,0.98,0.33<BR></p>
  
  <p>I want to read all the data in the csv file EXCEPT the first value in each row.</p>
  
  <p>I then want to normalise the data to a specific range.</p>
  
  <p>Thanks to stackoverflow, I have learnt to read the relevant data, and have managed to research enough Python to normalize the data.</p>
  
  <p>This data (if my code is correct) normalizes the data to a range of 0 to 1.</p>
  
  <p>I cannot however work out how to normalise the data to a different range (for example 0.001 to 1).</p>
  
  <pre><code>import numpy
  
  array = numpy.genfromtxt('Anaconda3JamesData/james_test_3.csv', delimiter=',')
  
  # get minimum and maximum values of 
  # all data except the first value in each row
  maximum=array[:, 1:].max()
  minimum=array[:, 1:].min()   
  
  print (minimum)
  print (maximum)
  
  # display the contents of the csv file except the first value in each row
  print (array[:,1:])
  
  # normalise all data in the array except 
  # the first value of each row
  x = (array[:,1:] - minimum)/(maximum - minimum)
  
  print (x)
  </code></pre>
  
  <p>My output is:</p>
  
  <p>0.14<BR>
  2.22<BR><BR>
  [[1.23 1.53 1.22 0.96 0.24 1.22 1.22 2.12 0.76 0.99]<BR>
   [1.17 1.52 0.67 0.93 0.14 1.6  1.23 2.22 0.55 0.65]<BR>
   [2.21 1.52 0.66 0.33 0.15 1.72 1.18 1.45 0.98 0.33]]<BR><BR>
  [[0.52403846 0.66826923 0.51923077 0.39423077 0.04807692 0.51923077<BR>
    0.51923077 0.95192308 0.29807692 0.40865385]<BR>
   [0.49519231 0.66346154 0.25480769 0.37980769 0.         0.70192308<BR>
    0.52403846 1.         0.19711538 0.24519231]<BR>
   [0.99519231 0.66346154 0.25       0.09134615 0.00480769 0.75961538<BR>
    0.5        0.62980769 0.40384615 0.09134615]]<BR></p>
  
  <p>This does indeed look like my normalization code is correct. It's normalizing the required data in-between 0 and 1. But how would I normalize the data in-between 0.001 and 1? Thank you.</p>