range(len(roc_dict))
with enumerate(roc_dict)
1321 if target_type == "classification":
1322 roc_df = pd.DataFrame(conn.CASTable("ROC", caslib="Public").to_frame())
1323 roc_dict = cls.apply_dataframe_to_json(json_dict[1]["data"], i, roc_df)
1324 for j in range(len(roc_dict)):1325 json_dict[1]["data"][j].update(roc_dict[j])
1326 fitstat_data = None
1327 if roc_dict[j]["dataMap"]["_KS_"] == 1:
range(len(lift_dict))
with enumerate(lift_dict)
1342
1343 lift_df = pd.DataFrame(conn.CASTable("Lift", caslib="Public").to_frame())
1344 lift_dict = cls.apply_dataframe_to_json(json_dict[2]["data"], i, lift_df, 1)
1345 for j in range(len(lift_dict)):1346 json_dict[2]["data"][j].update(lift_dict[j])
1347
1348 if json_path:
range(len(metrics))
with enumerate(metrics)
1246 """
1247 else:
1248 self.score_code += f"{'':4}if input_array.shape[0] == 1:\n"
1249 for i in range(len(metrics)):1250 self.score_code += f"{'':8}{metrics[i]} = prediction[0][{i}]\n"
1251 self.score_code += f"\n{'':8}return {', '.join(metrics)}\n"
1252 self.score_code += (
range(len(meta_data))
with enumerate(meta_data)
63 python_score_code = list(zip_path.glob("*.py"))[0].name
64
65 score_resource = []
66 for i in range(len(meta_data)): 67 if meta_data[i]["role"] == "score":
68 meta_data[i].update({"name": python_score_code})
69 if meta_data[i]["role"] == "scoreResource":
Using range(len(...))
is not pythonic. Python does not have not index-based loops. Instead, it uses collection iterators.
Python has a built-in method enumerate
which adds a counter to an iterable.
Using this, you can access the counter and the value from the iterable at the same time.
It is therefore recommended to replace range(len(...))
with enumerate(...)
.
for index in range(len(mylist)):
...
for index, element in enumerate(mylist):
...