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DOC: update the str_cat() docstring (Delhi) #20171

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Mar 14, 2018
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DOC: update the str_cat() docstring (Delhi) #20171

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Update str_cat Documentation
vipinkjonwal Mar 10, 2018
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Update str_cat Documentation
vipinkjonwal Mar 10, 2018
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Update str_cat Documentation
vipinkjonwal Mar 10, 2018
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Update str_cat Documentation
vipinkjonwal Mar 10, 2018
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DOC : Update cat_str
vipinkjonwal Mar 10, 2018
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simplify extended summary
jorisvandenbossche Mar 14, 2018
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22 changes: 15 additions & 7 deletions pandas/core/strings.py
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Original file line number Diff line number Diff line change
Expand Up @@ -51,11 +51,19 @@ def str_cat(arr, others=None, sep=None, na_rep=None):
"""
Concatenate strings in the Series/Index with given separator.

This function concatenates elements of Series/Index and elements
of lists or list-like objects having same length.
The concatenation is done at corresponding indices of
iterable specified by `Series` when two or more iterables
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This part is not fully clear to me: " corresponding indices of iterable"

Can you give a small example of what you want to explain here?

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@vipinkjonwal vipinkjonwal Mar 10, 2018 •
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Corresponding indices indicates that the concatenation is being done in one to one correspondence with the indices i.e, index of iterable, let say list.

For example :

pd.Series(['a', 'b', 'c']).str.cat(['A', 'B', 'C'], sep=',')
index
0 a,A (a with A i.e, 0th index of list in Series and 0th index of list in cat(list...) )
1 b,B (b with B)
2 c,C (c with C)

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Ah, OK. In that case, I think it is fine to say that "concatenates the Series/Index and other element-wise"

are present. The final concatenation is done with a given `sep`
and a string is returned.

Parameters
----------
others : list-like, or list of list-likes
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Can you add , optional at the end of the line?

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Yes. Adding.

If None, returns str concatenating strings of the Series
sep : string or None, default None
If None, returns str concatenating strings of the Series.
sep : string or None, default None.
If None, concatenates without any separator.
na_rep : string or None, default None
If None, NA in the series are ignored.

Expand All @@ -68,29 +76,29 @@ def str_cat(arr, others=None, sep=None, na_rep=None):
When ``na_rep`` is `None` (default behavior), NaN value(s)
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I would also say something here about not passing other that then all values in the Series are concatenated in a single string (so to indicate you first give an example of this part of the behaviour of the method)

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Added :-)

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Did you add this?

in the Series are ignored.

>>> Series(['a','b',np.nan,'c']).str.cat(sep=' ')
>>> pd.Series(['a','b',np.nan,'c']).str.cat(sep=' ')
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Can you split this example in two steps?

s = pd.Series(...)
s.str.cat(sep=..)

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Yes, I can do this way as well.

'a b c'

>>> Series(['a','b',np.nan,'c']).str.cat(sep=' ', na_rep='?')
>>> pd.Series(['a','b',np.nan,'c']).str.cat(sep=' ', na_rep='?')
'a b ? c'

If ``others`` is specified, corresponding values are
concatenated with the separator. Result will be a Series of strings.

>>> Series(['a', 'b', 'c']).str.cat(['A', 'B', 'C'], sep=',')
>>> pd.Series(['a', 'b', 'c']).str.cat(['A', 'B', 'C'], sep=',')
0 a,A
1 b,B
2 c,C
dtype: object

Otherwise, strings in the Series are concatenated. Result will be a string.

>>> Series(['a', 'b', 'c']).str.cat(sep=',')
>>> pd.Series(['a', 'b', 'c']).str.cat(sep=',')
'a,b,c'

Also, you can pass a list of list-likes.

>>> Series(['a', 'b']).str.cat([['x', 'y'], ['1', '2']], sep=',')
>>> pd.Series(['a', 'b']).str.cat([['x', 'y'], ['1', '2']], sep=',')
0 a,x,1
1 b,y,2
dtype: object
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