recommendations.py

import requests
import pandas as pd 
from yahoo_fin import stock_info as si 
from pandas_datareader import DataReader
import numpy as np

tickers = si.tickers_sp500()
recommendations = []

for ticker in tickers:
    lhs_url = 'https://query2.finance.yahoo.com/v10/finance/quoteSummary/'
    rhs_url = '?formatted=true&crumb=swg7qs5y9UP&lang=en-US&region=US&' \
              'modules=upgradeDowngradeHistory,recommendationTrend,' \
              'financialData,earningsHistory,earningsTrend,industryTrend&' \
              'corsDomain=finance.yahoo.com'
              
    url =  lhs_url + ticker + rhs_url
    r = requests.get(url)
    if not r.ok:
        recommendation = 0
    try:
        result = r.json()['quoteSummary']['result'][0]
        recommendation =result['financialData']['recommendationMean']['fmt']
    except:
        recommendation = 0
    
    recommendations.append(recommendation)    
    print("--------------------------------------------")
    print ("{} has an average recommendation of: ".format(ticker), recommendation)
    
dataframe = pd.DataFrame(list(zip(tickers, recommendations)), columns =['Company', 'Recommendation'])
df  = dataframe.sort_values('Recommendation', ascending = True)
df.to_csv('recommendations.csv')

print (df)