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fix finviz #11

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fix finviz #11

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15 changes: 6 additions & 9 deletions stockgrader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,7 @@
import time
import collections
import warnings
import re

warnings.filterwarnings('ignore')

Expand Down Expand Up @@ -84,10 +85,10 @@ def getNumStocks(url):
page = requests.get(url, headers=headers, proxies = {"http": next(proxyPool)})
soup = BeautifulSoup(page.content, 'html.parser')

tableRows = soup.find_all('a', class_ = 'screener-link')
tableRows = soup.find_all('div', id = 'screener-total')

raw_num = str(tableRows[0])
num_stocks = raw_num[raw_num.find('">') + 2 : raw_num.find('</a>')]
num_stocks = re.search(r'\d{4,5}', raw_num).group()

return float(num_stocks)

Expand Down Expand Up @@ -137,10 +138,7 @@ def get_company_data(url, debug=False):

pbar.update(20)

allStockData = pd.concat(dataframes)
allStockData.columns = list(allStockData.iloc[0])
allStockData = allStockData[1:]

allStockData = pd.concat(dataframes)


def remove_outliers(S, std):
Expand All @@ -162,7 +160,7 @@ def get_sector_data():

for metric in metrics:

rows[metric] = rows[metric].str.rstrip('%')
rows[metric] = rows[metric].astype(str).str.rstrip('%')
rows[metric] = pd.to_numeric(rows[metric], errors='coerce')
data = remove_outliers(rows[metric], 2)

Expand Down Expand Up @@ -305,8 +303,7 @@ def export_to_csv(filename):
allStockData['Percent Diff'] = (pd.to_numeric(allStockData['Target Price'], errors='coerce') - pd.to_numeric(allStockData['Price'], errors='coerce')) / pd.to_numeric(allStockData['Price'], errors='coerce') * 100

ordered_columns = 'Ticker, Company, Market Cap, Overall Rating, Sector, Industry, Country, Valuation Grade, Profitability Grade, Growth Grade, Performance Grade, Fwd P/E, PEG, P/S, P/B, P/C, P/FCF, Dividend, Payout Ratio, EPS this Y, EPS next Y, EPS past 5Y, EPS next 5Y, Sales past 5Y, EPS Q/Q, Sales Q/Q, Insider Own, Insider Trans, Inst Own, Inst Trans, Short Ratio, ROA, ROE, ROI, Curr R, Quick R, LTDebt/Eq, Debt/Eq, Gross M, Oper M, Profit M, Perf Month, Perf Quart, Perf Half, Perf Year, Perf YTD, Volatility M, SMA20, SMA50, SMA200, 52W High, 52W Low, RSI, Earnings, Price, Target Price, Percent Diff'

stock_csv_data = allStockData

stock_csv_data = allStockData[ordered_columns.replace(', ', ',').split(',')]
stock_csv_data.to_csv(filename, index=False)

Expand Down