How can I improve my stock lookup code to run in under 5 minutes?

Question

I have a list of stock symbols, for which I need to extract financial data. I wrote a function to get all data I need (see below).

I tested it on 35 stocks, it took me 9 min to run. The real dataset has more than 600 stock symbols, which would take hours of running.

Can you review my code and advise on how to make it run in less than 5 minutes, please?

Here are financial indicators I need for each stock:

# Free Cash Flow 
# EV/EBIDTA
# P/E Ratio
# YoY Growth for Profit Margins
# EV/ Revenue

Here is sample dataset:

	Symbol
0	AAOI
1	AAPL
2	ACCD
3	ACEV
4	ACEVU

Here is the code:

(Short Explanation: trying to get 5 financial indicators listed above for each stock, and if there is some missing data, then simply assign np.NaN value)

array=df['Symbol']
fin_df=pd.DataFrame()
for item in array:
    
    #part 1
    symbol=yf.Ticker(item)
    info_df=pd.DataFrame(pd.Series(symbol.info)).T
    values=['symbol','freeCashflow','enterpriseToEbitda','enterpriseToRevenue']
    for value in values:
        if value not in list(info_df.columns):
            info_df[value]=np.NaN
        else:
            pass
    info_df=info_df[['symbol','freeCashflow','enterpriseToEbitda','enterpriseToRevenue']]
    
    
    #part 2
    info_2=symbol.financials.T
    try:
        info_df['YoY Profit Margins Growth']=round(info_2['Gross Profit'][0]/info_2['Gross Profit'][1],2)
    except:
        info_df['YoY Profit Margins Growth']=np.NaN
    
    
    #part 3
    #info_3=pd.DataFrame(pd.Series(si.get_quote_table(item))).T
    info_3=pd.DataFrame()
    try:
        info_3['PE Ratio (TTM)']=pd.Series(si.get_quote_table(item)).T['PE Ratio (TTM)']
    except:
        info_3['PE Ratio (TTM)']=np.NaN
        
    info_df['PERatio']=info_3['PE Ratio (TTM)']
    fin_df=pd.concat([fin_df,info_df])


fin_df.reset_index(drop=True, inplace=True)
fin_df

Is there is a way to make the function more efficient in terms of time?

Answer 1

I know this post is pretty old, but I just came across it now. Check out the 'yfinance' library. There's all kinds of stuff available over there!!

import pandas_datareader as web
import pandas as pd
 
df = web.DataReader('AAPL', data_source='yahoo', start='2011-01-01', end='2021-01-12')
df.head()

import yfinance as yf
aapl = yf.Ticker("AAPL")
aapl
 
 
# get stock info
aapl.info
 
# get historical market data
hist = aapl.history(period="max")
 
# show actions (dividends, splits)
aapl.actions
 
# show dividends
aapl.dividends
 
# show splits
aapl.splits
 
# show financials
aapl.financials
aapl.quarterly_financials
 
# show major holders
aapl.major_holders
 
# show institutional holders
aapl.institutional_holders
 
# show balance sheet
aapl.balance_sheet
aapl.quarterly_balance_sheet
 
# show cashflow
aapl.cashflow
aapl.quarterly_cashflow
 
# show earnings
aapl.earnings
aapl.quarterly_earnings
 
# show sustainability
aapl.sustainability
 
# show analysts recommendations
aapl.recommendations
 
# show next event (earnings, etc)
aapl.calendar
 
# show ISIN code - *experimental*
# ISIN = International Securities Identification Number
aapl.isin
 
# show options expirations
aapl.options
 
# get option chain for specific expiration
opt = aapl.option_chain('YYYY-MM-DD')

Quarterly Financials Example:

                                           2022-09-24     2022-06-25  \
Research Development                     6761000000.0   6797000000.0   
Effect Of Accounting Charges                     None           None   
Income Before Tax                       24657000000.0  23066000000.0   
Minority Interest                                None           None   
Net Income                              20721000000.0  19442000000.0   
Selling General Administrative           6440000000.0   6012000000.0   
Gross Profit                            38095000000.0  35885000000.0   
Ebit                                    24894000000.0  23076000000.0   
Operating Income                        24894000000.0  23076000000.0   
Other Operating Expenses                         None           None   
Interest Expense                         -827000000.0   -719000000.0   
Extraordinary Items                              None           None   
Non Recurring                                    None           None   
Other Items                                      None           None   
Income Tax Expense                       3936000000.0   3624000000.0   
Total Revenue                           90146000000.0  82959000000.0   
Total Operating Expenses                65252000000.0  59883000000.0   
Cost Of Revenue                         52051000000.0  47074000000.0   
Total Other Income Expense Net           -237000000.0    -10000000.0   
Discontinued Operations                          None           None   
Net Income From Continuing Ops          20721000000.0  19442000000.0   
Net Income Applicable To Common Shares  20721000000.0  19442000000.0   

                                           2022-03-26      2021-12-25  
Research Development                     6387000000.0    6306000000.0  
Effect Of Accounting Charges                     None            None  
Income Before Tax                       30139000000.0   41241000000.0  
Minority Interest                                None            None  
Net Income                              25010000000.0   34630000000.0  
Selling General Administrative           6193000000.0    6449000000.0  
Gross Profit                            42559000000.0   54243000000.0  
Ebit                                    29979000000.0   41488000000.0  
Operating Income                        29979000000.0   41488000000.0  
Other Operating Expenses                         None            None  
Interest Expense                         -691000000.0    -694000000.0  
Extraordinary Items                              None            None  
Non Recurring                                    None            None  
Other Items                                      None            None  
Income Tax Expense                       5129000000.0    6611000000.0  
Total Revenue                           97278000000.0  123945000000.0  
Total Operating Expenses                67299000000.0   82457000000.0  
Cost Of Revenue                         54719000000.0   69702000000.0  
Total Other Income Expense Net            160000000.0    -247000000.0  
Discontinued Operations                          None            None  
Net Income From Continuing Ops          25010000000.0   34630000000.0  
Net Income Applicable To Common Shares  25010000000.0   34630000000.0