数据挖掘 沪深股市预测

导入基本模块库

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from statsmodels.tsa.arima_model import ARMA
import warnings
from itertools import product
from datetime import datetime
warnings.filterwarnings('ignore')

加载数据

# 数据加载
df = pd.read_csv('./shanghai_1990-12-19_to_2019-2-28.csv')

将时间作为df的索引

df.Timestamp = pd.to_datetime(df.Timestamp)
df.index = df.Timestamp

效果如图

数据探索

print(df.head())

按照月，季度，年来统计

df_month = df.resample('M').mean()
df_Q = df.resample('Q-DEC').mean()
df_year = df.resample('A-DEC').mean()

按照天，月，季度，年来显示比特币的走势

fig = plt.figure(figsize=[15, 7])
plt.rcPa