ValueError: could not convert string to float

أعمل على مجموعة بيانات "داتاسيت" هي تغريدات تويتر، لذا  قمت مبدأياً ببناء نموذج LogisticRegrission  لكن لاأعلم سبب الخطأ التالي:

<class 'pandas.core.series.Series'>

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-9-20b55637dec5> in <module>
     10 print(type(X_train))
     11 clf = LogisticRegression()
---> 12 clf.fit(X_train, y_train)

~\anaconda3\lib\site-packages\sklearn\linear_model\_logistic.py in fit(self, X, y, sample_weight)
   1525 
   1526         X, y = check_X_y(X, y, accept_sparse='csr', dtype=_dtype, order="C",
-> 1527                          accept_large_sparse=solver != 'liblinear')
   1528         check_classification_targets(y)
   1529         self.classes_ = np.unique(y)

~\anaconda3\lib\site-packages\sklearn\utils\validation.py in check_X_y(X, y, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, warn_on_dtype, estimator)
    753                     ensure_min_features=ensure_min_features,
    754                     warn_on_dtype=warn_on_dtype,
--> 755                     estimator=estimator)
    756     if multi_output:
    757         y = check_array(y, 'csr', force_all_finite=True, ensure_2d=False,

~\anaconda3\lib\site-packages\sklearn\utils\validation.py in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)
    529                     array = array.astype(dtype, casting="unsafe", copy=False)
    530                 else:
--> 531                     array = np.asarray(array, order=order, dtype=dtype)
    532             except ComplexWarning:
    533                 raise ValueError("Complex data not supported\n"

~\anaconda3\lib\site-packages\numpy\core\_asarray.py in asarray(a, dtype, order)
     81 
     82     """
---> 83     return array(a, dtype, copy=False, order=order)
     84 
     85 

~\anaconda3\lib\site-packages\pandas\core\series.py in __array__(self, dtype)
    752               dtype='datetime64[ns]')
    753         """
--> 754         return np.asarray(self.array, dtype)
    755 
    756     # ----------------------------------------------------------------------

~\anaconda3\lib\site-packages\numpy\core\_asarray.py in asarray(a, dtype, order)
     81 
     82     """
---> 83     return array(a, dtype, copy=False, order=order)
     84 
     85 

~\anaconda3\lib\site-packages\pandas\core\arrays\numpy_.py in __array__(self, dtype)
    182 
    183     def __array__(self, dtype=None) -> np.ndarray:
--> 184         return np.asarray(self._ndarray, dtype=dtype)
    185 
    186     _HANDLED_TYPES = (np.ndarray, numbers.Number)

~\anaconda3\lib\site-packages\numpy\core\_asarray.py in asarray(a, dtype, order)
     81 
     82     """
---> 83     return array(a, dtype, copy=False, order=order)
     84 
     85 

ValueError: could not convert string to float: 'قزم العهد'

الكود:

from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
import pandas as pd
Data = pd.read_csv('D:/train.csv')
Data['Tweet'] =Data['Tweet'].astype(str)  
data["Class"].replace({"abusive":0,"hate":0,"normal":1},inplace=True) 
data = Data['Tweet']
label = Data["Class"]
X_train, X_test, y_train, y_test = train_test_split(data, label, test_size = 0.2, random_state = 2021)
clf = LogisticRegression()
clf.fit(X_train, y_train)