PR to handle columns of a dataframe that are not of type float

lime/lime_tabular.py

@@ -316,9 +316,19 @@ def explain_instance(self,
         feature_names = copy.deepcopy(self.feature_names)
         if feature_names is None:
             feature_names = [str(x) for x in range(data_row.shape[0])]
-
-        values = self.convert_and_round(data_row)
-
+        # get column names if numpy.ndarray or pandas df:
+        try:
+            col_names = list(data_row.columns)
+        except AttributeError:
+            if data_row.dtype.names is not None:
+                col_names = list(data_row.dtype.names)
+            else:
+                col_names = []
+        if len(col_names) != 0:
+            if np.sum([1 if str(k).isdigit() else 0 for k in col_names]) != len(col_names):
+                values = self.convert_and_round(data_row.values[0])
+        else:
+            values = self.convert_and_round(data_row)
         for i in self.categorical_features:
             if self.discretizer is not None and i in self.discretizer.lambdas:
                 continue