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import requests as rq import pandas as pd import csv import matplotlib.pyplot as plt import numpy as np url="http://research.fsc.gov.tw/fsd/fncl_od.asp?opendata=FSF024" r=rq.get(url).content.decode('utf-8') data=list(csv.reader(r.split('\n'),delimiter=',')) df=pd.DataFrame(data[1:len(data)-1],columns=data[0]) #pd.DataFrame(data) # 過濾掉前面只有月份的data df2=df[df.iloc[:,0].astype(int)>105] df2.astype(float) df2.index-=18 df2.head()
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columns=len(df2.columns) for i in np.arange(1,columns): plt.figure(i) plt.title(df2.columns[i]) plt.plot(df2.iloc[:,i].astype(float)) plt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签 plt.xticks(np.arange(0,df2.shape[0],30),df2.iloc[0::30,0]) # if i%3==0: # break plt.show()
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台股市值占GDP比率過去十年約在150%-180%,在150%以下的時間相當短暫, 因此可用此數值判斷台股高估或低估,若接近180則為高估,若接近150則為便宜價,接近便宜價時可以買進0050, 或0056