<jupyter_start><jupyter_text>Market Datags_quant allows for easy access to market data.<jupyter_code>from gs_quant.data import Dataset
from datetime import date, timedelta
from gs_quant.session import Environment, GsSession
# external users should substitute their client id and secret; please skip this step if using internal jupyterhub
GsSession.use(Environment.PROD, client_id=None, client_secret=None, scopes=('read_product_data',))
# Get IRSWAP Data
ds_rate = Dataset('SWAPRATES_STANDARD')  # Get a swap rate data set
ds_rate.get_coverage()                   # Lets see what's available
start_date = date(2019, 1, 1)
end_date = date.today() - timedelta(days=1)
data = ds_rate.get_data(start_date, end_date,
                        assetId='MABXTJXXN8WJR7R8', tenor='10y')
print(data.head())
ds_rate_vol = Dataset('SWAPTIONVOL_STANDARD') # Get a swaption vol data set
ds_rate_vol.get_coverage()                    # Lets see what's available
data = ds_rate_vol.get_data(start_date, end_date, assetId='MAFYB8Z4R1377A19')
print(list(data))
print(data.head())<jupyter_output><empty_output>