问题描述
我正在学习 python,其中的困惑是按年制作, 真心求帮助 我有这样的股票数据 (data1) 来自 yfinance 的数据
data1 = yf.download(ticker,'2000-01-01','2021-01-01')
与(data1)的内容
Index(['Open','High','Low','Close','Adj Close','Volume'],dtype='object')
.
Date Open High Low Close* Adj Close** Volume
04/01/2011 15:00:00 4,330.00 4,390.00 4,300.00 4,390.00 186,370,900
05/01/2011 15:00:00 4,260.00 4,290.00 4,210.00 4,280.00 4,280.00 128,905,400
06/01/2011 15:00:00 4,160.00 4,200.00 4,200.00 116,634,000
07/01/2012 15:00:00 4,240.00 4,270.00 4,270.00 97,239,100
08/01/2012 15:00:00 4,150.00 4,320.00 4,310.00 4,310.00 96,568,200
11/01/2012 15:00:00 4,180.00 3,950.00 4,160.00 170,156,900
12/01/2013 15:00:00 4,120.00 4,130.00 4,130.00 171,484,000
13/01/2013 15:00:00 4,340.00 4,210.00 218,968,900
14/01/2013 15:00:00 4,280.00 207,410,700
15/01/2020 15:00:00 4,360.00 4,330.00 141,727,100
19/01/2020 15:00:00 4,350.00 4,320.00 130,044,800
像这样的年度数据(data2)
data2 = {'eps': ['100','231','200','167']}
df = pd.DataFrame(data2,index = [ '2017','2018','2019','2020'])
带有(data2)的内容
Year EPS
2017 100
2018 231
2019 200
2020 167
最终的结果是这样的,
然后确定了基于 eps 年份的除法计算,这与 data1 上的日期相同,并计算了 P / EPS (P = Adj Close ** / EPS)
Date Open High Low Close* Adj Close** Volume Eps P / EPS
04/01/2017 4,390.01 186,900 100 43,9
05/01/2017 4,280.01 128,400 100 42,8
06/01/2017 4,200.01 116,000 100 42,0
07/01/2018 4,270.01 97,100 231 18,5
08/01/2018 4,310.01 96,200 231 18,7
11/01/2019 4,160.01 170,900 200 20,8
12/01/2019 4,130.01 171,000 200 20,7
13/01/2019 4,210.01 218,900 200 21,1
14/01/2020 4,280.01 207,700 167 25,6
15/01/2020 4,330.01 141,100 167 25,9
19/01/2020 4,320.01 130,800 167 25,9
我应该在python中输入什么代码
非常感谢在我学习过程中帮助我的朋友们,谢谢
解决方法
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