python - Populate new column based on existing column checked against regex pandas -

i have data frame in pandas below

df = pd.dataframe({'firstname':['vishal', 'nishal', 'indira', 'jagdish', 'tamnna'], 'actual age':[25,33,58,58,30]})    firstname  actual age 0    vishal          25  1   nishant          33 2    indira          58 3   jagdish          58    4    tamnna          30 

and regex:

\w+ish\w* 

what cant seem figure our provide result below:

  firstname  actual age  copydown 0    vishal          25    vishal 1   nishant          33   nishant 2    indira          58   nishant 3   jagdish          58   jagdish 4    tamnna          30   jagdish 

so want through firstname column, , if can match regex given, continue copying down value in new column until next match found, , keep doing until end.

any ideas? ive been stuck on days. copydown feature want implement might useful in denormalised datasets. (using dates stuff)

thanks in advance

here 1 way it. first identify whether there match. groupby using cumsum trick. finally, populate each sub group using first value.

import pandas pd import re  # data # ============================= print(df)     firstname  actual age 0    vishal          25 1   nishant          33 2    indira          58 3   jagdish          58 4    tamnna          30  # processing # ============================= pattern = re.compile(r'\w+ish\w*')  df['matched'] = [(pattern.match(x) not none) x in df.firstname.values] df['diff_names'] = df.matched.astype(int).cumsum()   def func(group):     group['copydown'] = group['firstname'].values[0]     return group.drop(['matched', 'diff_names'], axis=1)  df.groupby('diff_names').apply(func)     firstname  actual age copydown 0    vishal          25   vishal 1   nishant          33  nishant 2    indira          58  nishant 3   jagdish          58  jagdish 4    tamnna          30  jagdish