Desired error not necessarily achieved due to precision loss. -novice

I am trying to do mle for school assignment, why could I be getting this error:

#1) Find best fitting distribution parametersbest_fit(macamil2data) #     {'loglaplace': {'c': 1.0603278885766216,#                     'loc': -0.04671203840594998,#                     'scale': 10.230045114772532}}#2) Calculate pdf using said parametersdef loglaplace_loglikelihood(params, data):    c, loc, scale = params    return stats.loglaplace.logpdf(data, c=c, loc=loc, scale=scale).sum()#3) Minimize using said parametersinitial_params = [1.0603278885766216, -0.04671203840594998, 10.230045114772532]results = minimize(loglaplace_loglikelihood, initial_params, args=(macamil2data))print(results) message: Desired error not necessarily achieved due to precision loss.  success: False   status: 2      fun: nan        x: [ 5.127e+03 -1.765e+05 -1.945e+03]      nit: 2      jac: [       nan        nan        nan] hess_inv: [[ 6.876e-01 -1.388e+01  5.195e-02]            [-1.388e+01  5.437e+02  5.473e+00]            [ 5.195e-02  5.473e+00  1.000e+00]]     nfev: 464     njev: 116

Tried lowering gtol, but it appears to me that I am making a systematic error my first time working with data in py. Sorry if it;s silly.

macamil2data=0.91666613.33.383333.683334.166674.26.083336.616677.033337.57.858.159.083339.3510.083310.183310.433311.283314.216.533320.033323.833330.3530.516732.466737.140.816745.65270.066770.533385.2333130.967