问“输入包含NaN，无穷大或dtype太大的值(‘float32’)”，当我训练DecisionTreeClassifier时

EN

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import sklearn

data = pd.read_csv('exoplanet.eu_catalog_2021.12.15.csv')
data_new = data.select_dtypes(include=['float64'])#Select only dtype float64 data
data_new[~data_new.isin([np.nan, np.inf, -np.inf]).any(1)]
data_new_2 = data_new.loc[:,('mass', 'mass_error_min')]
data_new_2.dropna(subset =["mass_error_min"], inplace = True)
data_new_2.info()
print(data_new_2)

<class 'pandas.core.frame.DataFrame'>
Int64Index: 1425 entries, 1 to 4892
Data columns (total 2 columns):
 #   Column          Non-Null Count  Dtype  
---  ------          --------------  -----  
 0   mass            1425 non-null   float64
 1   mass_error_min  1425 non-null   float64
dtypes: float64(2)
memory usage: 33.4 KB

data_new_2['mass'] = data_new_2['mass'].astype(float)
data_new_2['mass_error_min'] = data_new_2['mass_error_min'].astype(float)

from sklearn.model_selection import train_test_split
X = data_new_2.drop(["mass"], axis = 1)
y = data_new_2["mass"]
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = .30, random_state = 42)

from sklearn.tree import DecisionTreeClassifier
classifier = DecisionTreeClassifier()
classifier.fit(X_train, y_train_2)

ValueError                                Traceback (most recent call last)
<ipython-input-327-7b81afce3234> in <module>
      1 from sklearn.tree import DecisionTreeClassifier
      2 classifier = DecisionTreeClassifier()
----> 3 classifier.fit(X_train, y_train_2)
.
.
.
~/.local/lib/python3.6/site-packages/sklearn/utils/validation.py in _assert_all_finite(X, allow_nan, msg_dtype)
    104                     msg_err.format
    105                     (type_err,
--> 106                      msg_dtype if msg_dtype is not None else X.dtype)
    107             )
    108     # for object dtype data, we only check for NaNs (GH-13254)

ValueError: Input contains NaN, infinity or a value too large for dtype('float32').