fit each group and extract coefficients

[Progressive]

I have a data frame df as follows:

	Board	Time	CO	H2
0	B000653BE	05.11.2018 13:28	89720	20320
1	B000653BE	05.11.2018 13:32	112760	35070
2	B000653BE	05.11.2018 13:36	130783	47063
(...)
Board	Time	CO	H2
B000653BF	08.11.2018 14:04	261254	217003
B000653BF	08.11.2018 14:08	261395	216402
B000653C2	05.11.2018 13:28	95564	49094
B000653C2	05.11.2018 13:32	90978	73274
B000653C2	05.11.2018 13:36	87743	93204
(...)

And I want to fit each group of Board via

def func_exp(x, a, b, c):
        #c = 0
        return a * np.exp(b * x) + c
        
def exponential_regression (x_data, y_data):
    popt, pcov = curve_fit(func_exp, 
                           x_data, 
                           y_data,          
                           p0 = (1000.1, 0.01, 1000000),        
                           maxfev=5000
                           )
    print(popt)   
    return func_exp(x_data, *popt)

but I can't figure out how to proceed. I thought about

df.groupby('Board').apply(exponential_regression(df.index, df["H2"]))

but I only get different errors (when I try to adjust the syntax somehow..)
I'm totally used to R, there I know how to proceed but I don't know how to do the same in python. However, I need to fit each group in regards to H2 and CO and extract the corresponding regression coefficients.

Can somebody please help me?