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<blockquote>
<p>File "SCTR.py", line 53, in
ppoHist=ta.PPO(StockData['Last'],12,26)
TypeError: Argument 'real' has incorrect type (expected numpy.ndarray, got Series)</p>
</blockquote>
<p>请检查这段代码,我上面提到的错误是编译后反映出来的,我现在完全不知道。在</p>
<pre><code>from nsepy import get_history
from datetime import date
import pandas as pd
import requests
from io import BytesIO
import certifi
from dateutil.relativedelta import relativedelta
#import numpy as np
#import matplotlib.pyplot as plt
import datetime
import numpy as np
import matplotlib.colors as colors
import matplotlib.finance as finance
import matplotlib.dates as mdates
import matplotlib.ticker as mticker
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager
import talib as ta
from talib import MA_Type
url1 = 'https://www1.nseindia.com/content/indices/ind_nifty_Alpha_Index.csv'
def datainpy(url):
headers = { 'Accept' : '*/*',
'User-Agent' : 'Mozilla/5.0',
'Refers' : 'http://www.nseindia.com',
'Connection' : 'keep-alive'
}
getContents = requests.get(url,headers=headers).content
symbol_list=pd.read_csv(BytesIO(getContents))
print(symbol_list.head())
for eachSymbol in symbol_list['Symbol'][1:8]:
stock = get_history(symbol = eachSymbol,
start = date(2016,3,20),
end = date(2016,3,30))
stock.drop_duplicates(inplace=True)
stock.drop(stock.columns[[0,1,2,7,8,10,11,12,13]], axis = 1, inplace = True)
print (stock.head())
print(stock.head())
stock.index=pd.to_datetime(stock.index)
#stock.to_csv('./HistoricalData//' + eachSymbol + '.csv' , date_format='%Y%m%d')
return stock;
StockData=datainpy(url=url1)
print(StockData.head())
type(StockData)
ppoHist=ta.PPO(StockData['Last'],12,26)
print(ppoHist.head())
</code></pre>
<p>我想基本上生成SCTR(股票图表技术排名)即PPO,DMA(200),RSI等在一个csv中为“每个符号”。在</p>