我在这里遗漏了一些非常基本的东西,但这已经是漫长的一天,我不确定会发生什么。在下面的示例中,我将循环遍历列表调用“ tickers”三次。我想将某些分析的结果附加到每个循环末尾的列表中,因此要附加三个,而不是100个以上。这是我的代码。
from pandas_datareader import data as wb
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.pylab import rcParams
from sklearn.preprocessing import MinMaxScaler
start = '2020-03-01'
end = '2020-09-22'
tickers = ['TAN','QCLN','PBW']
thelen = len(tickers)
z=0
all_stocks=[]
price_data = []
for ticker in tickers:
prices = wb.DataReader(ticker, start = start, end = end, data_source='yahoo')[['Open','Adj Close']]
price_data.append(prices.assign(ticker=ticker)[['ticker', 'Open', 'Adj Close']])
#names = np.reshape(price_data, (len(price_data), 1))
df = pd.concat(price_data)
df.reset_index(inplace=True)
# doing some analysis in here, then writing results to a dataframe...
z=z+1
print(str(z) + ' of ' + str(thelen))
all_stocks.append(ticker + ' act: ' + str(new_seriesdata['Adj Close'].iloc[-1]) + ' prd: ' + str(myclosing_priceresult))
现在,我获得了数据框中最后一个行情自动收录器中的所有项目,但前两个已消失。我需要代码+ str(new_seriesdata ['Adj Close']。iloc [-1]),这是数据框中的最后一项。
答案 0 :(得分:2)
prices
进行就地更新。
prices
都会更改price_data = []
price_data = [prices, prices, prices]
prices
,请使用.copy()
df = pd.concat(price_data)
不应出现在循环中df.groupby('ticker')
并汇总计算。price_data = []
for ticker in tickers:
prices = wb.DataReader(ticker, start = start, end = end, data_source='yahoo')[['Open','Adj Close']]
price_data.append(prices.assign(ticker=ticker)[['ticker', 'Open', 'Adj Close']].copy())
df = pd.concat(price_data).reset_index()
df.head()
Date ticker Open Adj Close
0 2020-03-02 TAN 36.630001 36.990002
1 2020-03-03 TAN 37.770000 37.130001
2 2020-03-04 TAN 38.130001 38.520000
3 2020-03-05 TAN 37.639999 38.330002
4 2020-03-06 TAN 37.299999 36.880001
df.tail()
Date ticker Open Adj Close
424 2020-09-16 PBW 57.410000 57.650002
425 2020-09-17 PBW 56.130001 56.480000
426 2020-09-18 PBW 57.189999 57.310001
427 2020-09-21 PBW 56.139999 56.639999
428 2020-09-22 PBW 56.580002 56.509998
答案 1 :(得分:1)
当前,您将在循环的最后递归之后追加到all_stocks
。要解决此问题,您要做的就是将附加移入for
循环中,以便每次循环都被调用。
由于python关心缩进,因此将行移动到循环中所需要做的就是使它缩进:
for ticker in tickers:
prices = wb.DataReader(ticker, start = start, end = end, data_source='yahoo')[['Open','Adj Close']]
price_data.append(prices.assign(ticker=ticker)[['ticker', 'Open', 'Adj Close']])
#names = np.reshape(price_data, (len(price_data), 1))
df = pd.concat(price_data)
df.reset_index(inplace=True)
# doing some analysis in here, then writing results to a dataframe...
z=z+1
print(str(z) + ' of ' + str(thelen))
# NOTE: Change comes below
all_stocks.append(ticker + ' act: ' + str(new_seriesdata['Adj Close'].iloc[-1]) + ' prd: ' + str(myclosing_priceresult))
别担心,这是一个普遍的问题,每个人都会发生