Note: this answer was written for an older version of numpy, relevant when the question was written. With modern numpy, makhlaghi's answer provides a more elegant solution.

Since numpy.savetxt can also write to file objects, you can open the file youself and write your header before the data:

import numpy
a = numpy.array([[0.0,1.630000e+01,1.990000e+01,1.840000e+01],
                 [1.0,1.630000e+01,1.990000e+01,1.840000e+01],
                 [2.0,1.630000e+01,1.990000e+01,1.840000e+01]])
fmt = ",".join(["%s"] + ["%10.6e"] * (a.shape[1]-1))

# numpy.savetxt, at least as of numpy 1.6.2, writes bytes
# to file, which doesn't work with a file open in text mode.  To
# work around this deficiency, open the file in binary mode, and
# write out the header as bytes.
with open('final.csv', 'wb') as f:
  f.write(b'SP,1,2,3\n')
  #f.write(bytes("SP,"+lists+"\n","UTF-8"))
  #Used this line for a variable list of numbers
  numpy.savetxt(f, a, fmt=fmt, delimiter=",")

Below is sample code:

output = np.zeros(names.size, dtype=[('name', 'U32'), ('r', float),('m',float)])
np.savetxt("foo.csv", output, delimiter=",", header="name,r,m", fmt="%s,%f,%f", comments='')

As documented here.

it inserts the # because that line is a comment, and the default character for comments is the symbol #,

If you want to get rid of it, pass comments='' as option to savetxt.

numpy.savetxt('reference_vect_tool.00001.txt',riferimento,fmt='%.6f',header="reference", comments="")

 np.savetxt(BASEPATH+ r'keywordsarray2.txt', df1.values,
                          fmt='%4.d', header=str(df1.columns))