参考：

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import numpy as np

import pandas as pd

from pandas import Series,DataFrame

from numpy import nan as NaN

import tensorflow as tf

import matplotlib.pyplot as plt

import scipy.io as sio

import os

from sklearn import preprocessing

读取mat数据

load_path="08_1.mat"

load_data = sio.loadmat(load_path)

a = load_data['D']

print(a)

data = DataFrame(a)

print(data)

data.fillna(0)

print(data.fillna(0))

b=data.fillna(0).values

print(b)

数据归一化

a2 = preprocessing.scale(b)

print('数据归一化：')

print(a2)

数据清洗方法2 删除NAN所在的列

load_path2="08_1.mat"

load_data2 = sio.loadmat(load_path2)

a2 = load_data2['D']

print(a2)

data2 = DataFrame(a2)

data2.dropna(axis=0, how='any')

print(data2.dropna(axis=0, how='any'))`

处理前：

处理后：