how to perform calculation for all elements of list parellely or simultaneously to reduce the run time? - python-3.x

Question

I am extracting a dataframe from yahoo API for a list of companies but I want to do it paralelly(i.e, the dataframes for all the companies should be extracted simultaneously).So, it reduces my run time....
My code:
import pandas_datareader.data as web
import pandas as pd
import datetime
end_date = datetime.datetime.now().strftime('%d/%m/%Y')
temp = datetime.datetime.now() - datetime.timedelta(6*365/12)
start_date = temp.strftime('%d/%m/%Y')
f = web.DataReader('ACC.NS', 'yahoo', start_date, end_date)
print(f)
The output of this code is a dataframe shown below:
This i have done for single company....
I want to do it for a list of companies which is:
Company_Names = ['ACC', 'ADANIENT', 'ADANIPORTS', 'ADANIPOWER', 'AJANTPHARM', 'ALBK', 'AMARAJABAT', 'AMBUJACEM', 'APOLLOHOSP', 'APOLLOTYRE', 'ARVIND', 'ASHOKLEY', 'ASIANPAINT', 'AUROPHARMA', 'AXISBANK',
'BAJAJ-AUTO', 'BAJFINANCE', 'BAJAJFINSV', 'BALKRISIND', 'BANKBARODA', 'BANKINDIA', 'BATAINDIA', 'BEML', 'BERGEPAINT', 'BEL', 'BHARATFIN', 'BHARATFORG', 'BPCL', 'BHARTIARTL', 'INFRATEL', 'BHEL', 'BIOCON', 'BOSCHLTD', 'BRITANNIA',
'CADILAHC', 'CANFINHOME', 'CANBK', 'CAPF', 'CASTROLIND', 'CEATLTD', 'CENTURYTEX', 'CESC', 'CGPOWER', 'CHENNPETRO', 'CHOLAFIN', 'CIPLA', 'COALINDIA', 'COLPAL', 'CONCOR', 'CUMMINSIND', 'DABUR', 'DCBBANK',
'DHFL', 'DISHTV', 'DIVISLAB', 'DLF', 'DRREDDY', 'EICHERMOT', 'ENGINERSIN', 'EQUITAS', 'ESCORTS', 'EXIDEIND',
'FEDERALBNK', 'GAIL', 'GLENMARK', 'GMRINFRA', 'GODFRYPHLP', 'GODREJCP', 'GODREJIND', 'GRANULES', 'GRASIM', 'GSFC', 'HAVELLS', 'HCLTECH', 'HDFCBANK', 'HDFC', 'HEROMOTOCO', 'HEXAWARE', 'HINDALCO', 'HCC', 'HINDPETRO', 'HINDUNILVR',
'HINDZINC', 'ICICIBANK', 'ICICIPRULI', 'IDBI', 'IDEA', 'IDFCBANK', 'IDFC', 'IFCI', 'IBULHSGFIN', 'INDIANB', 'IOC', 'IGL', 'INDUSINDBK', 'INFIBEAM', 'INFY', 'INDIGO', 'IRB', 'ITC', 'JISLJALEQS', 'JPASSOCIAT', 'JETAIRWAYS', 'JINDALSTEL',
'JSWSTEEL', 'JUBLFOOD', 'JUSTDIAL', 'KAJARIACER', 'KTKBANK', 'KSCL', 'KOTAKBANK', 'KPIT', 'L&TFH', 'LT', 'LICHSGFIN', 'LUPIN', 'M&MFIN', 'MGL', 'M&M', 'MANAPPURAM', 'MRPL', 'MARICO', 'MARUTI', 'MFSL', 'MINDTREE', 'MOTHERSUMI', 'MRF', 'MCX',
'MUTHOOTFIN', 'NATIONALUM', 'NBCC', 'NCC', 'NESTLEIND', 'NHPC', 'NIITTECH', 'NMDC', 'NTPC', 'ONGC', 'OIL', 'OFSS', 'ORIENTBANK', 'PAGEIND', 'PCJEWELLER', 'PETRONET', 'PIDILITIND', 'PEL', 'PFC', 'POWERGRID', 'PTC', 'PNB', 'PVR', 'RAYMOND',
'RBLBANK', 'RELCAPITAL', 'RCOM', 'RELIANCE', 'RELINFRA', 'RPOWER', 'REPCOHOME', 'RECLTD', 'SHREECEM', 'SRTRANSFIN', 'SIEMENS', 'SREINFRA', 'SRF', 'SBIN', 'SAIL', 'STAR', 'SUNPHARMA', 'SUNTV', 'SUZLON', 'SYNDIBANK', 'TATACHEM', 'TATACOMM', 'TCS',
'TATAELXSI', 'TATAGLOBAL', 'TATAMTRDVR', 'TATAMOTORS', 'TATAPOWER', 'TATASTEEL', 'TECHM', 'INDIACEM', 'RAMCOCEM', 'SOUTHBANK', 'TITAN', 'TORNTPHARM', 'TORNTPOWER', 'TV18BRDCST', 'TVSMOTOR', 'UJJIVAN', 'ULTRACEMCO', 'UNIONBANK', 'UBL', 'UPL',
'VEDL', 'VGUARD', 'VOLTAS', 'WIPRO', 'WOCKPHARMA', 'YESBANK', 'ZEEL']
For all this companies the dataframe 'f' should be extracted parallely in order to save run time. Can anyone help me to solve this?