add a string prefix to each value in a string column using Pandas

Question

I would like to append a string to the start of each value in a said column of a pandas dataframe  elegantly   I already figured out how to kind-of do this and I am currently using   df ix  df  col      False    col      str  df  df  col      False    col     This seems one hell of an inelegant thing to do - do you know any other way  which maybe also adds the character to rows where that column is 0 or NaN    In case this is yet unclear  I would like to turn       col  1     a 2     0   into          col  1     stra 2     str0

User · Accepted Answer

df  col      str    df  col   astype str    Example    gt  gt  gt  df   pd DataFrame   col    a  0     gt  gt  gt  df   col 0   a 1   0  gt  gt  gt  df  col      str    df  col   astype str   gt  gt  gt  df     col 0  stra 1  str0

User · Answer

If you load you table file with dtype str  or convert column type to string df  a     df  a   astype str   then you can use such approach   df  a     col    df  a   str      This approach allows prepend  append  and subset string of df  Works on Pandas v0 23 4  v0 24 1  Don t know about earlier versions

User · Answer

As an alternative  you can also use an apply combined with format  or better with f-strings  which I find slightly more readable if one e g  also wants to add a suffix or manipulate the element itself   df   pd DataFrame   col    a   0     df  col     df  col   apply lambda x         format  str   x     which also yields the desired output       col 0  stra 1  str0   If you are using Python 3 6   you can also use f-strings   df  col     df  col   apply lambda x  f str x      yielding the same output   The f-string version is almost as fast as  RomanPekar s solution  python 3 6 4    df   pd DataFrame   col    a   0  200000     timeit df  col   apply lambda x  f str x    117 ms    451   s per loop  mean    std  dev  of 7 runs  10 loops each    timeit  str    df  col   astype str  112 ms    1 04 ms per loop  mean    std  dev  of 7 runs  10 loops each    Using format  however  is indeed far slower    timeit df  col   apply lambda x         format  str   x   185 ms    1 07 ms per loop  mean    std  dev  of 7 runs  10 loops each

User · Answer

Another solution with  loc   df   pd DataFrame   col     a   0    df loc df index   col      string    df  col   astype str    This is not as quick as solutions above   1ms per loop slower  but may be useful in case you need conditional change  like   mask    df  col      0  df loc mask   col      string    df  col   astype str

User · Answer

You can use pandas Series map    df  col   map  str    format    It will apply the word  str  before all your values

[python] add a string prefix to each value in a string column using Pandas

Examples related to python

Examples related to string

Examples related to pandas

Examples related to dataframe