title: Generating unique random value in Numpy
body: <p>I tried to generate large numbers of unique random values using np.random.randint but it returned few duplicates values.</p>
  
  <p>I have following dataset</p>
  
  <pre><code>District    Prefix  Quota       
  A           98426   783
  A           98427   223
  A           98446   127
  A           98626   51
  B           98049   167
  B           98079   153
  B           98140   120
  B           98159   139
  B           98169   182
  B           98249   86
  B           98426   588
  B           98446   96
  C           98049   104
  C           98060   68
  C           98149   65
  C           98150   68
  C           98159   86
  C           98160   80
  C           98169   113
  
  </code></pre>
  
  <p>Code to reproduce: </p>
  
  <pre><code>import pandas as pd
  df = pd.DataFrame([
      ['A', 98426, 783],
      ['A', 98427, 223],
      ['A', 98446, 127],
      ['A', 98626, 51],
      ['B', 98049, 167],
      ['B', 98079, 153],
      ['B', 98140, 120],
      ['B', 98159, 139],
      ['B', 98169, 182],
      ['B', 98249, 86],
      ['B', 98426, 588],
      ['B', 98446, 96],
      ['C', 98049, 104],
      ['C', 98060, 68],
      ['C', 98149, 65],
      ['C', 98150, 68],
      ['C', 98159, 86],
      ['C', 98160, 80],
      ['C', 98169, 113]
  ], 
      columns=['District', 'Prefix', 'Quota'])
  </code></pre>
  
  <p>I had to create a unique random number and add it to the prefix. the number of random values is given in Quota</p>
  
  <pre><code>np.random.seed(1)  # for repeatability 
  random=df.Prefix.repeat(df.Quota)*100000 + np.random.randint(0, 99999, df.Quota.sum())
  </code></pre>
  
  <p>I thought np.random.randint gave unique numbers but while generating around 18000 numbers, it gave around 200 duplicate number.
  eventually I tried random.sample and problem was fixed. but I want to generate unique numbers using np.random.randit because I can change seed in np.random.seed(n) and can create another set of unique numbers different from first set by changing seed.</p>