今天，我将使用TSfresh库来管理我的时间序列数据集，并进行时间序列分类。
我使用this tutorial来使代码适应我的数据。现在，我实现了一些步骤，但在分割数据时出现了一个错误：

import os
import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split

# Import the data path (my time series path)
data_path = 'PATH'

#Import the csv containing the label (in my case "Reussite_Sevrage")
target_df = pd.read_csv("PATH.csv",encoding="ISO-8859-1", dtype={'ID': 'str'})

# Delete the useless lines (containing nan values in the end of the dataset)
target_df = target_df.iloc[0:57,:]

# Definition of the labels
labels = target_df['Reussite_sevrage']

# Definition of the df containing the IDs
sequence_ids=target_df['ID']

#Splitting the data 
train_ids, test_ids, train_labels, test_labels = train_test_split(sequence_ids, labels, test_size=0.2)

#Create the X_train and X_test dataframe
X_train = pd.DataFrame()
X_test = pd.DataFrame()

# Now, will loop through the training sequence IDs and the testing sequence IDs. 
# For each of these sequence IDs, we will read the corresponding time series data CSV file and add it to the main dataframe.
# We will also add a column for the sequence number and a step column which contains integers representing the time step in the sequence

for i, sequence in enumerate(train_ids):
    inputfile = 'PATH'/ f"{sequence}.txt"
    if inputfile.exists():
        df = pd.read_csv(os.path.join(data_path, 'PAD/', "%s.txt" % sequence), 
                delimiter='\t',  # columns are separated by spaces
                header=None,  # there's no header information
                #parse_dates=[[0, 1]],  # the first and second columns should be combined and converted to datetime objects
                #infer_datetime_format=True,
                decimal=",")
        df = df.iloc[:,1]
        df = df.to_frame(name ='values')
        df.insert(0, 'sequence', i)
        df['step'] = np.arange(df.shape[0]) # creates a range of integers starting from 0 to the number of the measurements.
        X_train = pd.concat([X_train, df])

我在循环中添加了一个条件，只检查和处理存在的文件。丢失的数据由丢失的文件表示。如果我省略了这个条件，循环将在检测到丢失的文件时停止。

inputfile = PATH / f"{sequence}.txt"
    if inputfile.exists():

但出现以下错误：unsupported operand type(s) for /: 'str' and 'str'
我不知道是否错误是由于数据加载过程中的dtype={'ID': 'str'}，但我需要它，因为ID的格式如下：0001，0002，0003 ...如果不添加此条件，则ID将转换为：1,2,3...
sequence_ids, train_ids, train_labels, test_ids and test_labels为串行格式，sequence为字符串格式。
你能想出解决这个问题的办法吗？
非常感谢