if is_pandas_like(c):
c = c.values // convert pandas into numpy
if label is not None:
label = listify(label)
n_cols = 1 if len(c.shape) == 1 else c.shape[1]
labels = []
for i in range(0, n_cols):
After Change
result = feat._compute(*tuple(data1 + data2))
features.append((result, feat.label))
features = self.union(features, pairs)
// log timing
total_time = time.time() - start_time