深度学习时间序列预测：LSTM算法构建时间序列单变量模型预测空气质量（PM2.5）+代码实战

Posted 2021-09-01 Data+Science+Insight

深度学习时间序列预测：LSTM算法构建时间序列单变量模型预测空气质量（PM2.5）+代码实战

# 导入需要的包和函数；

from __future__ import print_function
import os
import sys
import pandas as pd
import numpy as np
%matplotlib inline
from matplotlib import pyplot as plt
import seaborn as sns
import datetime

# 数据加载

# set current working directory
# os.chdir(\'D:/Practical Time Series\')


#set current working directory
os.chdir(\'E:\\\\time series\\\\Practical-Time-Series-Analysis-code\')

#Read the dataset into a pandas.DataFrame
# df = pd.read_csv(\'datasets/PRSA_data_2010.1.1-2014.12.31.csv\')

#Read the dataset into a pandas.DataFrame
df = pd.read_csv(\'DataFiles\\\\PRSA_data_2010.1.1-2014.12.31.csv\')


print(\'Shape of the dataframe:\', df.shape)

#Let\'s see th