Steve L. Nyemba 4 years ago
parent f65b082fb1
commit 62a665464d

@ -604,7 +604,7 @@ class Predict(GNet):
# df = pd.DataFrame(np.round(f)).astype(np.int32) # df = pd.DataFrame(np.round(f)).astype(np.int32)
# candidates.append (np.round(_matrix).astype(np.int64)) # candidates.append (np.round(_matrix).astype(np.int64))
candidates.append( [np.round(row).astype(int) for row in _matrix]) candidates.append(np.array([np.round(row).astype(int) for row in _matrix]))
# return candidates[0] if len(candidates) == 1 else candidates # return candidates[0] if len(candidates) == 1 else candidates
return candidates return candidates

@ -111,7 +111,7 @@ class Input :
if 'columns' in _args : if 'columns' in _args :
self._columns = _args['columns'] self._columns = _args['columns']
else: # else:
# #
# We will look into the count and make a judgment call # We will look into the count and make a judgment call
_df = pd.DataFrame(self.df.apply(lambda col: col.dropna().unique().size )).T _df = pd.DataFrame(self.df.apply(lambda col: col.dropna().unique().size )).T

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