In the following pandas.DataFframe:
pandas.DataFframe
df = alfa beta ceta a,b,c c,d,e g,e,h a,b d,e,f g,h,k j,k c,k,l f,k,n
This is the numpy version of @NickilMaveli's answer.
numpy
mask = np.core.defchararray.count(df.alfa.values.astype(str), ',') <= 1 pd.DataFrame(df.values[mask], df.index[mask], df.columns) alfa beta ceta 1 a,b d,e,f g,h,k 2 j,k c,k,l f,k,n
naive timing