The parameter in a custom function when using pandas.Series.apply

Question

Here is a simple pandas Dataframe defined as follow:

df = pd.DataFrame( {
    'word':     ['flower', 'mountain', 'ocean', 'universe'],
    'k':        [1, 2, 3, 4]
} )

>>> df
   k      word
0  1    flower
1  2  mountain
2  3     ocean
3  4  universe

I want to change df into this ( replace every word with its first k letters )

>>> df
   k  word
0  1     f
1  2    mo
2  3   oce
3  4  univ

I have an idea to achieve this by using pandas.Series.apply with a custom function

def get_first_k_letters( x, k ):
    return x[:k]

df['word'] = df['word'].apply( get_first_k_letters, args=(3,) )

>>> df
   k word
0  1  flo
1  2  mou
2  3  oce
3  4  uni

I can easily replace every word with its first 3 letters by setting args=(3,).

But I want to replace every word with its first k letters ( k is not always the same ) and I don't know what is the setting for args in this case.

Could somebody help me? Thanks! ( Other methods without using pandas.Series.apply will also be OK! )

MaxU - stand with Ukraine · Accepted Answer · 2017-05-26 08:48:25Z

2

I'd consider this approach:

In [121]: df['word'] = [w[1][:w[0]] for w in df.values]

In [122]: df
Out[122]:
   k  word
0  1     f
1  2    mo
2  3   oce
3  4  univ

Timing: for 40.000 rows DF:

In [123]: df = pd.concat([df] * 10**4, ignore_index=True)

In [124]: df.shape
Out[124]: (40000, 2)

In [125]: %timeit df.apply(lambda x: get_first_k_letters(x['word'], x['k']), axis=1)
1 loop, best of 3: 4.04 s per loop

In [126]: %timeit [w[1][:w[0]] for w in df.values]
10 loops, best of 3: 52.5 ms per loop

In [127]: 4.04 * 1000 / 52.5
Out[127]: 76.95238095238095

answered May 26, 2017 at 8:48

MaxU - stand with Ukraine

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1 Comment

o0Helloworld0o Over a year ago

Thank you! You are a python specialist!

Mathias711 · Accepted Answer · 2017-05-26 08:54:02Z

2

You can do:

df.apply(lambda x: get_first_k_letters(x['word'], x['k']), axis=1)

Doing the apply with axis=1 option, yields each row into x (of the lambda. Giving axis=0 gives columns, not rows). Giving x['word'] and x['k'] to your function yields the correct outcome:

0       f
1      mo
2     oce
3    univ
dtype: object

edited May 26, 2017 at 8:54

answered May 26, 2017 at 8:24

Mathias711

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2 Comments

o0Helloworld0o Over a year ago

Nice solution! Thank you very much!

Mathias711 Over a year ago

@MaxU hehe, no problem. Your solution is indeed much faster for this specific case, but will not always work :)

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