import time
import pandas as pd
import matplotlib.pyplot as plt
import tushare as ts
import statsmodels.api as sm

if __name__ == '__main__':
? ?data = ts.get_k_data('600900', start='20180101', end='20221231')
? ?print(data)
? ?data.to_csv('600900.csv', index=False)
? ?data = pd.read_csv('600900.csv', index_col=0, parse_dates=[0])
? ?print(data)
? ?week = data['close'].resample('W').mean()
? ?print(week)
? ?stock = week['2018':'2023'].dropna()
? ?stock.plot(figsize=(12, 8))
? ?model = sm.tsa.arima.ARIMA(stock, order=(2, 0, 2))
? ?result = model.fit()
? ?x = result.summary()
? ?print(x)
? ?pred = result.predict(210, 300, dynamic=True)
? ?print(pred)
? ?plt.figure(figsize=(6, 6))
? ?plt.plot(pred)
? ?plt.plot(stock.values)
? ?plt.show()
? ?while True:
? ? ? ?time.sleep(60000)