ValueError: Found unknown categories [nan] in column 2 during fit

import pandas as pd
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split,cross_val_score
from sklearn.tree import DecisionTreeClassifier
from sklearn.naive_bayes import GaussianNB, MultinomialNB
from sklearn.metrics import accuracy_score
from sklearn.neighbors import KNeighborsClassifier
from sklearn.neural_network import MLPClassifier
from sklearn.metrics import precision_score, recall_score,auc
from sklearn.metrics import roc_curve,roc_auc_score,plot_roc_curve
from io import StringIO


path = r"C:\Users\thund\Downloads\Boat.csv"
data = pd.read_csv(path)  # pip install xlrd

print(data.shape)
print(data.columns)

print(data.isnull().sum())
print (data.dropna(axis=0))  #dropping rows that have missing values

print (data['Class'].value_counts())
print(data['Class'].value_counts().plot(kind = 'bar'))
#plt.show()

data['safety'].value_counts().plot(kind = 'bar')#plt.show()


import seaborn as snssns.countplot(data['demand'], hue = data['Class'])
#plt.show()

X = data.drop(['Class'], axis = 1)y = data['Class']

from sklearn.preprocessing import OrdinalEncoder
demand_category = ['low', 'med', 'high', 'vhigh']
maint_category = ['low', 'med', 'high', 'vhigh']
seats_category = ['2', '3', '4', '5more']
passenger_category = ['2', '4', 'more']
storage_category = ['Nostorage', 'small', 'med']
safety_category = ['poor', 'good', 'vgood']
all_categories = [demand_category, maint_category,seats_category,passenger_category,storage_category,safety_category]


oe = OrdinalEncoder(categories= all_categories)
X = oe.fit_transform( data[['demand','maint', 'seats', 'passenger', 'storage', 'safety']])

Dataset: https://drive.google.com/file/d/1O0sYZGJep4JkrSgGeJc5e_Nlao2bmegV/view?usp=sharing

I don't know why I keep encountering the 'ValueError: Found unknown categories [nan] in column 2 during fit' since I need it to PreProcess the data. I am quite new to python, would appreciate an in-depth explanation for this, please