[Python] error using statsmodels OLS: returning nan values

I have a data set like:

Growth NHSPSTY% Index USURTOT Index GLPFTOCI Index CPTICHNG Index NAPMPMI Index RSTAXYOY Index SAARTOTL Index USASHVTK Index CONCCONF Index LEI TOTL Index SPX Index TOT_DEBT_TO_TOT_EQY BDIY Index cry index CO1 Comdty
Date
1998-03-31 4.1 7.5 4.7 0.121000 83.5325 52.9 2.9 -0.032258 0.404 133.80 88.9 0.455185 197.26 966 169.04 14.26
1998-06-30 3.8 9.8 4.5 0.125556 82.2970 48.9 4.5 0.154930 0.393 138.23 88.6 0.280973 204.65 856 152.58 13.38


I wanted to run a OLS regression but all the parameters returned all nan values. And it warned:

/Users/jake/anaconda3/lib/python3.6/site-packages/scipy/stats/_distn_infrastructure.py:879: RuntimeWarning: invalid value encountered in greater
return (self.a < x) & (x < self.b)
/Users/jake/anaconda3/lib/python3.6/site-packages/scipy/stats/_distn_infrastructure.py:879: RuntimeWarning: invalid value encountered in less
return (self.a < x) & (x < self.b)
/Users/jake/anaconda3/lib/python3.6/site-packages/scipy/stats/_distn_infrastructure.py:1821: RuntimeWarning: invalid value encountered in less_equal
cond2 = cond0 & (x <= self.a)


coef std err t P>|t| [0.025 0.975]
const nan nan nan nan nan nan
NHSPSTY% Index nan nan nan nan nan nan
USURTOT Index nan nan nan nan nan nan
GLPFTOCI Index nan nan nan nan nan nan
CPTICHNG Index nan nan nan nan nan nan


My command:

import statsmodels.api as sm
model = sm.OLS(data.Growth,sm.add_constant(data.iloc[:,1:])).fit()
model.summary()

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