use imputer.knnimpute.KNN(k=int)

parameters:

k: integer. The number of neighbors to look for

return: complete data

Example:

In [20]: from ycimpute.imputer import knnimput
In [21]: knnimput.KNN(k=4).complete(boston_mis)
Out[21]:
array([[  6.32000000e-03,   1.80000000e+01,   2.31000000e+00, ...,
          1.53000000e+01,   3.96900000e+02,   4.98000000e+00],
       [  2.73100000e-02,   0.00000000e+00,   4.72418064e+00, ...,
          1.78000000e+01,   3.96900000e+02,   9.14000000e+00],
       [  2.72900000e-02,   2.46828581e+01,   7.07000000e+00, ...,
          1.80569058e+01,   3.92830000e+02,   8.74745130e+00],
       ...,
       [  6.07600000e-02,   0.00000000e+00,   1.19300000e+01, ...,
          2.10000000e+01,   3.96900000e+02,   5.64000000e+00],
       [  1.09590000e-01,   0.00000000e+00,   1.19300000e+01, ...,
          2.10000000e+01,   3.93450000e+02,   6.48000000e+00],
       [  4.74100000e-02,   0.00000000e+00,   1.19300000e+01, ...,
          2.10000000e+01,   3.96900000e+02,   7.88000000e+00]])

In [22]: