I have following dataframe:
pri sec
TOM AB,CD,EF
JACK XY,YZ
HARRY FG
NICK KY,NY,SD,EF,FR
I need following output with column nam
Use join + split + add_prefix:
df = df.join(df['sec'].str.split(',', expand=True).add_prefix('sec'))
print (df)
pri sec sec0 sec1 sec2 sec3 sec4
0 TOM AB,CD,EF AB CD EF None None
1 JACK XY,YZ XY YZ None None None
2 HARRY FG FG None None None None
3 NICK KY,NY,SD,EF,FR KY NY SD EF FR
And if need NaN
s add fillna:
df = df.join(df['sec'].str.split(',', expand=True).add_prefix('sec').fillna(np.nan))
print (df)
pri sec sec0 sec1 sec2 sec3 sec4
0 TOM AB,CD,EF AB CD EF NaN NaN
1 JACK XY,YZ XY YZ NaN NaN NaN
2 HARRY FG FG NaN NaN NaN NaN
3 NICK KY,NY,SD,EF,FR KY NY SD EF FR