python - Duplicating Values based on Series input -

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i'm trying write custom function extends replace functionality (with domain specific concerns) have series looks like:

0   1 1   2 2   4 3   4 4   4

and return values function (which can't modify unfortunately cause it's coming source) looks either series like:

1   2   b 4   c

or dataframe looks this

    cola colb colc 1      t    f 2   b    f    f 4   c    t    t

i'm trying return output either looks like

0   1   b 2   c 3   c 4   c

or

    cola colb colc 0      t    f 1   b    f    f 2   c    t    t 3   c    t    t 4   c    t    t

depending on type returned function. i'm able write script performs iteratively, feel there must more efficient, more pandas specific way of performing operation, before generate hideous nested monstrosity figured i'd check if there's well-supported way!

i don't know how data looks may need modify code following works using map:

in [32]: s.map(s1[1])  out[32]: 0 0    1    b 2    c 3    c 4    c name: 1, dtype: object

for second 1 can perform left merge have construct dataframe series:

in [41]: pd.dataframe(s).merge(df, left_on=[1], right_index=true, how='outer')  out[41]:    1 cola colb colc 0                   0  1       t    f 1  2    b    f    f 2  4    c    t    t 3  4    c    t    t 4  4    c    t    t

for above can set index after merge

edit

actually second problem it's easier use reindex , pass series values:

in [42]: df.reindex(s)  out[42]:   cola colb colc 1                1       t    f 2    b    f    f 4    c    t    t 4    c    t    t 4    c    t    t

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