我在读取.csv文件的列时遇到问题。我有这个密码：

# Importing the libraries

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import confusion_matrix
from sklearn.metrics import classification_report
from sklearn.ensemble import RandomForestClassifier
from sklearn.svm import SVC
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import StandardScaler

# Importing the dataset

dataset = pd.read_csv('D:/CTU/ateroskleroza/development/results_output6.csv')
print(dataset.head())

X = dataset.iloc[:, 2:16].values
y = dataset.iloc[:, 0].values

# Splitting the dataset into the Training set and Test set

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

classifier = make_pipeline(StandardScaler(), SVC(gamma='auto'))
classifier.fit(X_train, y_train)

y_pred = classifier.predict(X_test)

# Making the Confusion Matrix

cm = confusion_matrix(y_test, y_pred)
print(cm)

# Generating accuracy, precision, recall and f1-score

target_names = ['Progressive','Stable']
print(classification_report(y_test, y_pred, target_names=target_names))

.csv如下所示：


根据图片的名称，他们有一些列，其他一些与楠。问题是，当我尝试执行此代码时，出现以下错误：

ValueError: Input contains NaN, infinity or a value too large for dtype('float64').

那么我怎么能忽略nan而只使用数字呢(我不想删除空列，只是在执行时忽略nan）。