The quantile operator returns the quantiles of the specified array.

Synopsis

quantile( srcArray, q_num [ , attribute [ , dimension_n ... ] ] )

Summary

A q_quantile is a point taken at a specified interval on a sorted data set that divides the data set into q subsets. The quantiles are the data values marking the boundaries between consecutive subsets.

You specify the source array (srcArray) and the number of quantiles (q_num). Optionally, you can specify an attribute and a dimension for grouping. To group by one or more dimensions, you must specify the attribute.

Inputs

The quantile operator takes the following arguments:

Examples

Calculate the 2-Quantile for a 1-Dimensional Array

To calculate the 2-quantile for a 1-dimensional array, do the following:

1. Create a 1-dimensional array called quantile_array:

   AFL% create array quantile_array <val:int64>[i=0:10];

   
   The output is:

   Query was executed successfully. 

2. Put eleven numerical values between 0 and 11 into quantile_array:

   AFL% store(build(quantile_array, '[10,3,0,3,4,5,9,11,7,3,3]', true), quantile_array);

   
   The output is:
   

   {i} val
   {0} 10
   {1} 3
   {2} 0
   {3} 3
   {4} 4
   {5} 5
   {6} 9
   {7} 11
   {8} 7
   {9} 3
   {10} 3

    

3. Find the 2-quantile of quantile_array
   

   AFL% quantile(quantile_array,2);  

   
   The output is:
   

   {quantile} percentage,val_quantile
   {0} 0,0
   {1} 0.5,4
   {2} 1,11

   
   

4. Remove the quantile_array
   

   AFL% remove(quantile_array);  

   
   The output is:
   

   Query was executed successfully

The Group-by-Dimension Parameter

To see/use the group-by-dimension parameter, do the following:

1. Start with a 5x5 array, with a single, integer attribute:
   
   

   AFL% create array m5x5<val:int32>[i=0:4; j=0:4];

   
   The output is:

   Query was executed successfully. 

2. Initialize the data in the array

   AFL% store(build(m5x5, '[[16,13,22,7,13],[11,19,23,21,24],[16,21,15,7,16],[10,19,0,23,23],[12,7,18,7,8]]', true), m5x5);

   
   The output is:

   {i,j} val
   {0,0} 16
   {0,1} 13
   {0,2} 22
   {0,3} 7
   {0,4} 13
   {1,0} 11
   {1,1} 19
   {1,2} 23
   {1,3} 21
   {1,4} 24
   {2,0} 16
   {2,1} 21
   {2,2} 15
   {2,3} 7
   {2,4} 16
   {3,0} 10
   {3,1} 19
   {3,2} 0
   {3,3} 23
   {3,4} 23
   {4,0} 12
   {4,1} 7
   {4,2} 18
   {4,3} 7
   {4,4} 8

3. Find the 2-quantile of the array, and then by the first dimension, and then by the second dimension.
   

   AFL% quantile(m5x5,2);  

   
   The output is:
   

   {quantile} percentage,val_quantile
   {0} 0,0
   {1} 0.5,16
   {2} 1,24 

   
   

   AFL% quantile(m5x5,2,val,i); 

   
   The output is:
   

   {i,quantile} percentage,val_quantile
   {0,0} 0,7
   {0,1} 0.5,13
   {0,2} 1,22
   {1,0} 0,11
   {1,1} 0.5,21
   {1,2} 1,24
   {2,0} 0,7
   {2,1} 0.5,16
   {2,2} 1,21
   {3,0} 0,0
   {3,1} 0.5,19
   {3,2} 1,23
   {4,0} 0,7
   {4,1} 0.5,8
   {4,2} 1,18

   
   

   AFL% quantile(m5x5,2,val,j);

   
   The output is:

   {j,quantile} percentage,val_quantile
   {0,0} 0,10
   {0,1} 0.5,12
   {0,2} 1,16
   {1,0} 0,7
   {1,1} 0.5,19
   {1,2} 1,21
   {2,0} 0,0
   {2,1} 0.5,18
   {2,2} 1,23
   {3,0} 0,7
   {3,1} 0.5,7
   {3,2} 1,23
   {4,0} 0,8
   {4,1} 0.5,16
   {4,2} 1,24

4. Remove the array 
   

   AFL% remove(m5x5);  

   
   The output is:
   

   Query was executed successfully