debug:TypeError: Feature names are only supported if all input features have string names, but your

一个bug卡了我好几天，写个文档记录一下处理过程，我个人思考的也不是很清楚，仅用做记录，希望日后能更深入的解决

问题产生：

训练随机森林等算法

df.head()

打印结果

track_id	track_name	popularity	duration_ms	explicit	artists	artists_id	release_date	danceability	energy	...	r&b	mandopop	japanese	rap	hong	indie	kong	house	singer	songwriter
0	5KpWHEh32vzxkttIK3KHKI	國際孤獨等級	51	193747	False	['Gareth.T']	6R57JlNKlnNrYaji0vw8xx	2023-03-03	0.692	0.189	...	0	0	0	0	1	0	1	0	0	0
1	1sb71AvysPMJlsx4qYtTpG	緊急聯絡人	58	222668	False	['Gareth.T']	6R57JlNKlnNrYaji0vw8xx	2023-11-30	0.513	0.373	...	0	0	0	0	1	0	1	0	0	0
2	2mMgDVazhRjNoOweYMP1pz	青春告別式	50	256967	False	['Hins Cheung']	2MVfNjocvNrE03cQuxpsWK	2023-12-31	0.433	0.380	...	0	0	0	0	0	0	0	0	0	0
3	6UuJk5rvrxSnOAwv6uSr5b	給你幸福 所以幸福	51	244693	False	['Jay Fung']	4EXI1ieJe2VDbvNsKOaNQL	2023-10-24	0.414	0.456	...	0	0	0	0	0	0	0	0	0	0
4	1mUhvuqX0ScGodDTdnRtuL	永久損毀	49	232002	False	['MC 張天賦', 'Panther Chan']	5tRk0bqMQubKAVowp35XtC	2023-12-19	0.514	0.405	...	0	0	0	0	0	0	0	0	0	0

5 rows × 45 columns

以上是数据内容

x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.4, random_state=0)
print(x_train.columns.tolist())
print(x_train.columns.dtype)
#TODO
x_train= x_train.rename(str,axis="columns") 

# 决策树模型
dt_model = DecisionTreeRegressor(random_state=0)
dt_model.fit(x_train, y_train)
y_pred_dt = dt_model.predict(x_test)

在dt_model.fit(x_train, y_train)报错，

TypeError: Feature names are only supported if all input features have stringAsk Qnames, but your input has ['str', 'str_'] as column name types

解决思路一

对数据类型进行转换，

x.columns = x.columns.astype(str)
print(x.columns.dtype)
print(x.columns.tolist())
for col_name in x.columns:
    assert isinstance(col_name, str)

其实这里核心的是x.columns = x.columns.astype(str)，一句就够了

但是经过上述代码，column的类型已经变成object，即字符串型，但是在上面的dt_model.fit(x_train, y_train)仍然报错相同，这里的失败原因尚不可知

解决思路二

x_train= x_train.rename(str,axis="columns") 

换了一种解决方法在StackOverflow中查到的，没想到一下子就好了，原理和方法一类似，我还没找到为什么这个可以