python-Sk learn 无法将字符串转换为浮点数

我有一个CSV文件

lemma,trained
iran seizes bitcoin mining machines power spike,-1
... (goes on for 1054 lines)

我的代码如下所示：

import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
from sklearn.metrics import accuracy_score
from sklearn.naive_bayes import GaussianNB
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split

df = pd.read_csv('lemma copy.csv')
X = df.iloc[:, 0].values
y = df.iloc[:, 1].values
print(y)

X_train, X_test, y_train, y_test =train_test_split(X,y,test_size= 0.25, random_state=0)

sc_X = StandardScaler() 

X_train = sc_X.fit_transform(X_train)

我收到错误

Traceback (most recent call last):
  File "/home/arctesian/Scripts/School/EE/Algos/Qual/bayes/sklean.py", line 20, in 
    X_train = sc_X.fit_transform(X_train)
  File "/home/arctesian/.local/lib/python3.10/site-packages/sklearn/base.py", line 867, in fit_transform
    return self.fit(X, **fit_params).transform(X)
  File "/home/arctesian/.local/lib/python3.10/site-packages/sklearn/preprocessing/_data.py", line 809, in fit
    return self.partial_fit(X, y, sample_weight)
  File "/home/arctesian/.local/lib/python3.10/site-packages/sklearn/preprocessing/_data.py", line 844, in partial_fit
    X = self._validate_data(
  File "/home/arctesian/.local/lib/python3.10/site-packages/sklearn/base.py", line 577, in _validate_data
    X = check_array(X, input_name="X", **check_params)
  File "/home/arctesian/.local/lib/python3.10/site-packages/sklearn/utils/validation.py", line 856, in check_array
    array = np.asarray(array, order=order, dtype=dtype)
ValueError: could not convert string to float: 'twitter ios beta lays groundwork bitcoin tips'

打印出来表明数据的随机拆分使该行成为第一行，因此它必须是对数据进行转码的问题。我该如何解决这个问题？