imp = mice.MICEData(dfLocal)
fml = 'LOC1 ~ LOC2 + LOC3 + LOC4 + LOC5'
mice = mice.MICE(fml, sm.OLS, imp)
results = mice.fit(10, 10)
print(results.summary())

dfLocal.dropna(axis=0, how='all', inplace=True)
imp.data = imp.data.set_index(dfLocal.index)

# In this case I only want to fill one specific set of missing data
# hence gap_start and gap_end
dfLocal.loc[gapStart:gapEnd, 'LOC1'] = imp.data[fillSite]