Split a string column based on a logic into two new columns in pandas

I have a dataframe df :-

I want to generate these two additional columns based on Type column ,All wordsending with Fs seperated in one and all Ts seperated in another column respectively.If Type is No Types then No Types in both the columns:-

>Solution :

I would use str.extract and a regex:

# extract F and T parts
df2 = df['Type'].str.extract('(.*\dF)?,?(\d+T.*)?')

df[['Fcol', 'Tcol']] = df2.fillna('Absent')

# identify no F nor T
m = df2.isna().all(axis=1)
# and fill original values for those
df.loc[m, ['Fcol', 'Tcol']] = df.loc[m, 'Type']

Output:

               Type        Fcol      Tcol
0    9F,5F/6F,3T,1T    9F,5F/6F     3T,1T
1  18F/19F,2F,9T,4T  18F/19F,2F     9T,4T
2           17F/12F     17F/12F    Absent
3                3T      Absent        3T
4          No Types    No Types  No Types

regex demo