如何使它看起来不那么丑陋和线条更少? 能够将大量库存导出到一个csv文件中,并且也许能够在每个库存信息之后添加一个新行,所以我不必将其放在自己的位置。 P.s.还有一种获取市值并可能随之浮动的方法。请
This is what I'm trying to achieve
import datetime as dt
import matplotlib.pyplot as plt
from matplotlib import style
import pandas as pd
import pandas_datareader.data as web
style.use('ggplot')
start = dt.datetime(2019,12,20)
end = dt.datetime(2019,12,31)
df = web.DataReader('SDRL', 'yahoo', start, end)
df2 = web.DataReader('SLNO', 'yahoo', start, end)
df3 = web.DataReader('PTI', 'yahoo', start, end)
df4 = web.DataReader('LCTX', 'yahoo', start, end)
df5 = web.DataReader('CLPS', 'yahoo', start, end)
df6 = web.DataReader('AGTC', 'yahoo', start, end)
df7 = web.DataReader('NLNK', 'yahoo', start, end)
df8 = web.DataReader('SAVA', 'yahoo', start, end)
df9 = web.DataReader('MBOT', 'yahoo', start, end)
df10 = web.DataReader('HSDT', 'yahoo', start, end)
df11 = web.DataReader('CTXR', 'yahoo', start, end)
df12 = web.DataReader('ISCNF', 'yahoo', start, end)
df13 = web.DataReader('DCAR', 'yahoo', start, end)
df14 = web.DataReader('LAIX', 'yahoo', start, end)
df15 = web.DataReader('MRNS', 'yahoo', start, end)
df16 = web.DataReader('DRRX', 'yahoo', start, end)
df17 = web.DataReader('NLNK', 'yahoo', start, end)
df18 = web.DataReader('CANF', 'yahoo', start, end)
df19 = web.DataReader('CBKC', 'yahoo', start, end)
df20 = web.DataReader('GSAT', 'yahoo', start, end)
df21 = web.DataReader('CYDY', 'yahoo', start, end)
df22 = web.DataReader('SDRL', 'yahoo', start, end)
df23 = web.DataReader('MRSN', 'yahoo', start, end)
df24 = web.DataReader('ASRT', 'yahoo', start, end)
df25 = web.DataReader('BB', 'yahoo', start, end)
df26= web.DataReader('FCEL', 'yahoo', start, end)
df27 = web.DataReader('MDNAF', 'yahoo', start, end)
df28 = web.DataReader('INPX', 'yahoo', start, end)
df29 = web.DataReader('TKRFF', 'yahoo', start, end)
df30 = web.DataReader('PRTK', 'yahoo', start, end)
df.append(df2)
df52 = df.append(df2)
df52.append(df3)
df53 = df52.append(df3)
df53.append(df4)
df54 = df53.append(df4)
df54.append(df5)
df55 = df54.append(df5)
df55.append(df6)
df56 = df55.append(df6)
df56.append(df7)
df57 = df56.append(df7)
df57.append(df8)
df58 = df57.append(df8)
df58.append(df9)
df59 = df58.append(df9)
df59.append(df10)
df60 = df59.append(df10)
df60.append(df11)
df61 = df60.append(df11)
df61.append(df12)
df62 = df61.append(df12)
df62.append(df13)
df63 = df62.append(df13)
df63.append(df14)
df64 = df63.append(df14)
df64.append(df15)
df65 = df64.append(df15)
df65.append(df16)
df66 = df65.append(df16)
df66.append(df17)
df67 = df66.append(df17)
df67.append(df18)
df68 = df67.append(df18)
df68.append(df19)
df69 = df68.append(df19)
df69.append(df20)
df70 = df69.append(df20)
df70.append(df21)
df71 = df70.append(df21)
df71.append(df22)
df72 = df71.append(df22)
df72.append(df23)
df73 = df72.append(df23)
df73.append(df24)
df74 = df73.append(df24)
df74.append(df25)
df75 = df74.append(df25)
df75.append(df26)
df76 = df75.append(df26)
df76.append(df27)
df77 = df76.append(df27)
df77.append(df28)
df78 = df77.append(df28)
df78.append(df29)
df79 = df78.append(df29)
df79.append(df30)
df80 = df79.append(df30)
print(df80)
df80.to_csv('Gap-Ups.csv')
df80 = pd.read_csv('Gap-Ups.csv', parse_dates=True, index_col=0)
答案 0 :(得分:1)
我建议使用while
软件包。 https://pypi.org/project/yfinance/
您可以使用
yfinance
,它会返回一个带有所有股票数据的单个熊猫数据框,无论您输入的股票行情多少。我相信它也会返回市值,但不会返回浮动数据。
答案 1 :(得分:1)
使用pd.concat
:
#Enter here all the list
companies_list = ['SDRL','SLNO','PTI']
df = pd.concat([web.DataReader(company, 'yahoo', start, end)
for company in companies_list])
尽管通过这种方式您不会区分数据的来源,所以我建议将其与axis = 1
或使用数据帧字典进行串联。
#Enter here all the list
companies_list = ['SDRL','SLNO','PTI']
df = pd.concat([(web.DataReader(company, 'yahoo', start, end)
.add_suffix(f'_{company}'))
for company in companies_list],axis = 1)
创建DataFrame的字典
d_company = {company:web.DataReader(company, 'yahoo', start, end)
for company in companies_list}