如何在python中填充NaN的值？

import pandas as pd

df = pd.DataFrame({'A': [1, 2, None, 4, 5], 'B': [None, 6, 7, None, 9]})
df.fillna(0, inplace=True)

import pandas as pd

df = pd.DataFrame({'A': [1, 2, None, 4, 5], 'B': [None, 6, 7, None, 9]})
df.replace(to_replace=pd.NaT, value=0, inplace=True)

import numpy as np

arr = np.array([1, 2, np.nan, 4, 5])
arr = np.where(np.isnan(arr), 0, arr)

from sklearn.impute import SimpleImputer

arr = np.array([1, 2, np.nan, 4, 5]).reshape(-1, 1)
imputer = SimpleImputer(strategy='mean')
arr = imputer.fit_transform(arr)