为什么我在计算波动率时会得到NaN？

import pandas as pd

# 假设df是你的数据框，'price'是价格列
df = pd.DataFrame({'price': [100, 102, 101, None, 103]})

# 检查是否有缺失值
print(df.isnull().sum())

# 填充缺失值
df['price'].fillna(method='ffill', inplace=True)

import numpy as np

# 计算平均价格
mean_price = df['price'].mean()

# 计算每个价格与平均价格的差的平方
squared_diff = (df['price'] - mean_price) ** 2

# 计算波动率
volatility = np.sqrt(np.sum(squared_diff) / (len(df) - 1))

print(volatility)

print("Mean Price:", mean_price)
print("Squared Differences:", squared_diff)
print("Sum of Squared Differences:", np.sum(squared_diff))