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Home/ Questions/Q 9071305
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Editorial Team
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Editorial Team
Asked: June 16, 20262026-06-16T17:52:38+00:00 2026-06-16T17:52:38+00:00

I have a dataframe like so: item price source day book 5 shop 2012-01-01

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I have a dataframe like so:

item   price source   day
book   5     shop     2012-01-01
car    100   shop     2012-01-01
desk   10    shop     2012-01-01
book   4     internet 2012-01-01
car    99    internet 2012-01-01
desk   9     internet 2012-01-01
book   6     shop     2012-01-02
car    101   shop     2012-01-02
desk   11    shop     2012-01-02
book   4     internet 2012-01-02
car    100   internet 2012-01-02
desk   10    internet 2012-01-02

I would like, per day, each price per item, like:

item price.shop price.internet day
book 5          4              2012-01-01
car  100        99             2012-01-01
desk 10         9              2012-01-01
book 6          5              2012-01-02
car  101        100            2012-01-02
desk 11         10             2012-01-02

I have been trying my best with

melt‘ing and then

cast(df, item ~ source + variable)

But can’t get the desired result. I think the issue is becase i have in essence two “per thing” conditions (per day, per source) and so dont have the correct equation.

Thanks for any help

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1 Answer

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  1. Editorial Team
    Editorial Team
    2026-06-16T17:52:39+00:00Added an answer on June 16, 2026 at 5:52 pm

    Not a plyr.reshape2 answer but using base:reshape():

    > reshape(dat, idvar=c("item", "day"),  timevar="source", direction="wide")
      item        day price.shop price.internet
    1 book 2012-01-01          5              4
    2  car 2012-01-01        100             99
    3 desk 2012-01-01         10              9
    7 book 2012-01-02          6              4
    8  car 2012-01-02        101            100
    9 desk 2012-01-02         11             10
    

    I suppose one could also could have tried a merge(subset_shop, subset_internet, 1:2, all=TRUE) strategy.

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