Apply two different formulas based on the cell content of a dataframe

January 20, 2022

i have this dataframe named optiondf:

     strike  type settle openInterest volume
0     10000  Call  24'24        0      0
1     15000  Call  0            0      0
2     20000  Call  23'56        0      0
3     25000  Call  1            0      0
4     30000  Call  23'24        0      0

I would like to be able to do some operations on the "settle" column.
I would like to filter based on whether or not the symbol " ‘ " is present in the value in the column.

In case contains " ‘ " putting this calculation as the value of the cell, which I have already verified, has no problems in calculating itself

pd.to_numeric(optiondf['settle'].str.split(pat="'").str[0])+pd.to_numeric(optiondf['settle'].str.split(pat="'").str[-1])*(1/64)

In case not contains " ‘ " I would just like to convert the value to a number, like this:

optiondf['settle']=pd.to_numeric(optiondf['settle'])

I have tried with this pandas feature but without success, I probably am doing something wrong:

optiondf['settle'].str.contains("'")=....

>Solution :

You could construct a lambda that applies to different functions:

def func_a(x):
    v = x.split("'")
    return v[0] + v[1] / 64

optiondf['settle'] = optiondf['settle'].apply(lambda x: func_a(x) if "'" in x else pd.to_numeric(x))