I am using fitter to try to fit a distribution to a set of data. My problem is that when I try to do it, the results seem to show that fitter is not normalizing the data, so no distribution will ever fit. How could I fix this? Is there any parameter I should pass like normalize=True or something like that? My code is

f = Fitter(deg, distributions=get_common_distributions())
f.fit()
f.summary()

where deg is a Numpy array with thousands of positive integers which represent the degree distribution of a network. And the output:

          sumsquare_error          aic           bic  kl_div
exponpow         5.031107  1405.772702 -34016.407373     inf
chi2             5.047918  1323.657269 -33999.925057     inf
gamma            5.062847  1338.383959 -33985.334011     inf
expon            5.423209  1184.884871 -33654.102234     inf
lognorm          5.512355   994.097326 -33565.037948     inf