我一直在从事一个涉及股票市场的项目,并为此创建了自己的类,但是当我运行这段代码时,我得到了一个错误
import stock_class as st
for i in names:
string = str(i)
stonk = st.stock(string, datetime.datetime(2016,12,31),datetime.datetime.now())
wSTD = stonk.standard_deviation() * weight[0]
当我在循环之外运行相同的代码时,它工作得很好,所以我认为这可能是一个奇怪的python问题,在这里,您不能用迭代变量声明实例类。不管看起来有多奇怪。以下是我在运行以下代码时遇到的错误:
pandas_datareader._utils.RemoteDataError: No data fetched for symbol CHOLF using YahooDailyReader
如果有人需要进一步的信息,请告诉我,谢谢
这是我创建并命名的图书馆:
import numpy as np
import pandas as pd
import yfinance as yf
import datetime as datetime
import pandas_datareader.data as web
import os
import math
class stock:
def __init__(self, name, start, end):
self.name = name #string
self.start = start
self.end = end # datetime funtion
def history_data(self):
hist = web.DataReader(self.name,'yahoo',self.start, self.end)
return hist
def returnP(self):
stonk = self.history_data()
close = stonk['Close']
returnlist = []
for i in range(len(close)):
if i != 0:
returnVal = (close[i]/close[i-1])-1
returnlist.append(returnVal)
else:
returnlist.append(0)
stonk['Return'] = returnlist #hopefully places a new column for the return rate
return stonk
def standard_deviation(self):
stonk = self.returnP()
array = []
mean = sum(stonk['Return'])/stonk.count()['Return']
for i in range(stonk.count()['Return']):
array.append((stonk['Return'][i] - mean)**2)
std = math.sqrt(sum(array)/len(array))
return std
def cum_return(self):
stonk = self.returnP()
stonk['Cumreturn'] = (stonk['Return']+1).cumprod()
return stonk
def yfticker(self): #should not be called by user
stonk = yf.Ticker(self.name)
info = stonk.info
return info
def PEG(self):
info = self.yfticker()
PEG = info['pegRatio']
return PEG
def FPE(self):
info = self.yfticker()
FPE = info['forwardPE']
return FPE
def price_book(self):
info = self.yfticker()
priceToBook = info['priceToBook']
return priceToBook
如前所述,此代码自身工作,下面是buy()函数中发生错误的代码
import stock_class as st
import pandas as pd
import pandas_datareader.data as web
import yfinance as yf
import datetime
import time
class descision:
def __init__(self, names, money): # takes an array of stocks so we can value
self.names = names # dem bitches ['tsla', 'fb', 'aapl', ... ]
self.money = money
def buy(self):
weight = [.5, .25, .25] # weights for STD, FPE, and PEG
money = self.money
split = money/10
names = self.names
pair = {}
buying = [] #going into dataframe
FPE = []
PEG = []
STD = []
price = [] # going into dataframe
date = []
amtBought = []
for i in names:
string = str(i)
print(i)
stonk = st.stock(string, datetime.datetime(2016,12,31),datetime.datetime.now())
print('1')
wSTD = stonk.standard_deviation() * weight[0]
print(wSTD)
wFPE = stonk.FPE() * weight[1]
wPEG = stonk.PEG() * weight[2]
heafty = (wSTD + wFPE + wPEG)
pair[i] = heafty
for i in range(10):
buying.append(max(pair))
pair.pop(max(pair))
for i in buying:
stock = yf.Ticker(i)
hist = stock/history('1d')
buyPrice = hist['Close'][-1]
price.append(buyPrice)
date.append(datetime.datetime.now())
amtBought.append(split/buyPrice)
tuples = list(zip(buying, price, date, amtBought))
df = pd.DataFrame(tuples, columns = ['Names', 'Buy Price',
'Date Purchased' ,' Amount'])
return df
# buy from the stocks in the growers with the least volitility,
# PE, and PEG
#def sell(self):
file = open('growers.txt','r')
names = []
money = 1000
for i in file:
names.append(str(i))
y = descision(names, money)
y.buy()
我希望我的编辑能提供足够的信息
在for循环的每次迭代中创建该类的对象似乎没有什么错。。。它更可能是关于股票市场的回报价值,而不是对象
只是为了向您展示您可以在循环内创建对象:
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