Error output

gistfile1.txt

import pandas as pd
import statsmodels.api as sm

dta = sm.datasets.macrodata.load_pandas().data
dta.index = pd.PeriodIndex(start='1959Q1', end='2009Q3', freq='Q')

mod = sm.tsa.SARIMAX(dta['infl'], order=(0, 0, 0))
res = mod.fit()
print(res.summary())

/usr/local/lib/python3.6/site-packages/statsmodels/compat/pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.
  from pandas.core import datetools
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-1-c42339ff65f8> in <module>()
      5 dta.index = pd.PeriodIndex(start='1959Q1', end='2009Q3', freq='Q')
      6 
----> 7 mod = sm.tsa.SARIMAX(dta['infl'], order=(0, 0, 0))
      8 res = mod.fit()
      9 print(res.summary())

/usr/local/lib/python3.6/site-packages/statsmodels/tsa/statespace/sarimax.py in __init__(self, endog, exog, order, seasonal_order, trend, measurement_error, time_varying_regression, mle_regression, simple_differencing, enforce_stationarity, enforce_invertibility, hamilton_representation, **kwargs)
    508         # Initialize the statespace
    509         super(SARIMAX, self).__init__(
--> 510             endog, exog=exog, k_states=k_states, k_posdef=k_posdef, **kwargs
    511         )
    512 

/usr/local/lib/python3.6/site-packages/statsmodels/tsa/statespace/mlemodel.py in __init__(self, endog, k_states, exog, dates, freq, **kwargs)
     95 
     96         # Initialize the state-space representation
---> 97         self.initialize_statespace(**kwargs)
     98 
     99     def prepare_data(self):

/usr/local/lib/python3.6/site-packages/statsmodels/tsa/statespace/mlemodel.py in initialize_statespace(self, **kwargs)
    128 
    129         # Instantiate the state space object
--> 130         self.ssm = KalmanSmoother(endog.shape[0], self.k_states, **kwargs)
    131         # Bind the data to the model
    132         self.ssm.bind(endog)

/usr/local/lib/python3.6/site-packages/statsmodels/tsa/statespace/kalman_smoother.py in __init__(self, k_endog, k_states, k_posdef, results_class, **kwargs)
    341 
    342         super(KalmanSmoother, self).__init__(
--> 343             k_endog, k_states, k_posdef, results_class=results_class, **kwargs
    344         )
    345 

/usr/local/lib/python3.6/site-packages/statsmodels/tsa/statespace/kalman_filter.py in __init__(self, k_endog, k_states, k_posdef, loglikelihood_burn, tolerance, results_class, **kwargs)
    211                  **kwargs):
    212         super(KalmanFilter, self).__init__(
--> 213             k_endog, k_states, k_posdef, **kwargs
    214         )
    215 

/usr/local/lib/python3.6/site-packages/statsmodels/tsa/statespace/representation.py in __init__(self, k_endog, k_states, k_posdef, initial_variance, nobs, dtype, design, obs_intercept, obs_cov, transition, state_intercept, selection, state_cov, **kwargs)
    276         # Get dimensions from transition equation
    277         if k_states < 1:
--> 278             raise ValueError('Number of states in statespace model must be a'
    279                              ' positive number.')
    280         self.k_states = k_states

ValueError: Number of states in statespace model must be a positive number.