获取的数据标准化问题

Question

获取的数据标准化问题

ValueError: could not convert string to float: '600309.SH'

import tushare as ts
from sklearn.tree import DecisionTreeRegressor
ts.set_token('f7c3adf6d7eb6eb7d922d2d2122c648414fa1cf06be6257764a0cb69')
pro = ts.pro_api('')
data = pro.daily(ts_code='600309.SH', start_date='20220101', end_date='20221209')
#数据按日期正序排序，并设置日期为索引
data.to_csv('600309_2022.csv')

#%%
import pandas as pd
df=pd.read_csv('600309_2022.csv',index_col='trade_date',parse_dates=True)
df.sort_index(axis=0,inplace=True)
pre_days = 10
df['label'] = df['close'].shift(-pre_days)
print(df)
#%%
from sklearn.preprocessing import StandardScaler
scaler = StandardScaler()
sca_X = scaler.fit_transform(df.iloc[:,:-1])
print(sca_X)

查询csv是否空格或者转行

我想要达到的结果，如果你需要快速回答，请尝试 “付费悬赏”