我正在尝试使用Python在接下来的30天内每天计算同一家公司的股价。我使用了list和.append()的索引,一旦添加了更新的价格,初始值就会被替换。我怎样才能列出同一只股票30天内的价格?
*#Catalyst Pharmaceuticals
#New York Stack Exchange
import requests
import pytz
from bs4 import BeautifulSoup
import datetime
import csv
r=requests.get('https://robinhood.com/collections/technology')
html=r.content
soup=BeautifulSoup(html,'html.parser')
csv_file=open('Catalyst Pharmaceuticals Monthly.csv','a')
csv_writer=csv.writer(csv_file)
price_list = []
dttm = []
def websc():
global price_list
global dttm
global a_price
#i=10
for p in soup.find_all('a',{'class':'rh-hyperlink'})[2]:
a_price = p.text
dd=datetime.datetime.now(pytz.timezone("GMT"))
dd=dd.strftime("%Y-%m-%d %H:%M:%S")
price_list.append(a_price)
dttm.append(dd)
zipped = zip(price_list,dttm)
d = list(zipped)
print(d)
csv_writer.writerows(d)
csv_file.close()
websc()*发布于 2020-08-30 22:41:15
如果不想覆盖文件,则需要以追加模式打开文件,而不是以写入模式打开
发布于 2020-08-31 20:25:45
难道你不能循环一些报价器,把所有东西都放到一个数据帧中,然后再把它导出到CSV中吗?
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import scipy.optimize as sco
import datetime as dt
import math
from datetime import datetime, timedelta
from pandas_datareader import data as wb
from sklearn.cluster import KMeans
np.random.seed(777)
start = '2020-01-01'
end = '2020-08-27'
#N = 165
#start = datetime.now() - timedelta(days=N)
#end = dt.datetime.today()
tickers = ['AAPL','MSFT','GOOG','SBUX','MCD','NKE']
thelen = len(tickers)
price_data = []
for ticker in tickers:
try:
prices = wb.DataReader(ticker, start = start, end = end, data_source='yahoo')[['Adj Close']]
price_data.append(prices.assign(ticker=ticker)[['ticker', 'Adj Close']])
except:
print(ticker)
df = pd.concat(price_data)
df.dtypes
df.head()
df.shape
# finally....
df.to_csv('file_name.csv')尝试一下,如果你需要其他相关的东西,可以回帖。
https://stackoverflow.com/questions/63658091
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