same IV and greeks for all puts and calls

[buckrogerss]

using py_vollib_vectorized.api.price_dataframe on a dataframe with separated put and call rows, I get identical values for IV and all greeks for the same strike using this code:

    py_vollib_vectorized.api.price_dataframe(df, flag_col='putCall', underlying_price_col='underlying', strike_col='strikePrice', 
                                             annualized_tte_col='yearsToExpiration', riskfree_rate_col='riskfree', price_col='mid', 
                                             model='black_scholes', inplace=True)

this is the resulting dataframe:

putCall	bid	ask	mid	strikePrice	underlying	riskfree	yearsToExpiration	IV	delta	gamma	theta	rho	vega
c	10.9	11.75	11.325	320	330.5	0.05628	0.009998644	0.295633059	0.869912166	0.021662616	-0.319891087	0.027614338	0.069914516
c	8.1	9.7	8.9	322.5	330.5	0.05628	0.009998644	0.255320828	0.840031264	0.028832294	-0.323066229	0.02686937	0.080358425
c	6.75	7	6.875	325	330.5	0.05628	0.009998644	0.250937862	0.759211322	0.037553558	-0.406136786	0.024401107	0.102887507
c	5.05	5.2	5.125	327.5	330.5	0.05628	0.009998644	0.250810611	0.654893962	0.04445565	-0.479879727	0.021128867	0.121760934
c	3.55	3.7	3.625	330	330.5	0.05628	0.009998644	0.248345739	0.538257409	0.048384716	-0.509033454	0.01742454	0.131234044
c	2.4	2.43	2.415	332.5	330.5	0.05628	0.009998644	0.245168038	0.416486845	0.048155586	-0.485743472	0.013521562	0.128936795
c	1.48	1.59	1.535	335	330.5	0.05628	0.009998644	0.244567854	0.302309547	0.043167275	-0.420750648	0.009836511	0.115277751
c	0.92	0.99	0.955	337.5	330.5	0.05628	0.009998644	0.247850054	0.208801732	0.035067308	-0.336931764	0.006804493	0.094883334
c	0.57	0.58	0.575	340	330.5	0.05628	0.009998644	0.251753959	0.137681226	0.026449765	-0.249229534	0.004492274	0.072683235
p	0.57	0.6	0.585	320	330.5	0.05628	0.009998644	0.295633059	0.869912166	0.021662616	-0.319891087	0.027614338	0.069914516
p	0.89	0.92	0.905	322.5	330.5	0.05628	0.009998644	0.255320828	0.840031264	0.028832294	-0.323066229	0.02686937	0.080358425
p	1.39	1.45	1.42	325	330.5	0.05628	0.009998644	0.250937862	0.759211322	0.037553558	-0.406136786	0.024401107	0.102887507
p	2.13	2.21	2.17	327.5	330.5	0.05628	0.009998644	0.250810611	0.654893962	0.04445565	-0.479879727	0.021128867	0.121760934
p	3.1	3.25	3.175	330	330.5	0.05628	0.009998644	0.248345739	0.538257409	0.048384716	-0.509033454	0.01742454	0.131234044
p	4.4	4.6	4.5	332.5	330.5	0.05628	0.009998644	0.245168038	0.416486845	0.048155586	-0.485743472	0.013521562	0.128936795
p	6.05	6.25	6.15	335	330.5	0.05628	0.009998644	0.244567854	0.302309547	0.043167275	-0.420750648	0.009836511	0.115277751
p	7.95	8.8	8.375	337.5	330.5	0.05628	0.009998644	0.247850054	0.208801732	0.035067308	-0.336931764	0.006804493	0.094883334
p	10.05	10.95	10.5	340	330.5	0.05628	0.009998644	0.251753959	0.137681226	0.026449765	-0.249229534	0.004492274	0.072683235

I may be dumb and this is a black scholes limitation or something, but in practice, this is of course inaccurate

[buckrogerss]

adding that if you use, for example, the 320 call and put values with the individual vectorized_implied_volatility, vectorized_delta, vectorized_gamma, etc functions, the call/put values are not identical, as expected