r - dplyr summarise over nested group_by -

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i have data frame this:

       date amount category 1  02.07.15      1        1 2  02.07.15      2        1 3  02.07.15      3        1 4  02.07.15      4        2 5  03.07.15      5        2 6  04.07.15      6        3 7  05.07.15      7        3 8  06.07.15      8        3 9  07.07.15      9        4 10 08.07.15     10        5 11 09.07.15     11        6 12 10.07.15     12        4 13 11.07.15     13        4 14 12.07.15     14        5 15 13.07.15     15        5 16 14.07.15     16        6 17 15.07.15     17        6 18 16.07.15     18        5 19 17.07.15     19        4

i calculate sum of amount each single day in category. attempts (see code) both not sufficient.

summarise(group_by(testdata, category), sum(amount))

wrong output --> here sum calculated on each group

  category sum(amount) 1        1           6 2        2           9 3        3          21 4        4          53 5        5          57 6        6          44  summarise(group_by(testdata, date), sum(amount), categories = tostring(category))

wrong output --> here sum calculated on each day categories not considered

       date sum(amount) categories 1  02.07.15          10 1, 1, 1, 2 2  03.07.15           5          2 3  04.07.15           6          3 4  05.07.15           7          3 5  06.07.15           8          3 6  07.07.15           9          4 7  08.07.15          10          5 8  09.07.15          11          6 9  10.07.15          12          4 10 11.07.15          13          4 11 12.07.15          14          5 12 13.07.15          15          5 13 14.07.15          16          6 14 15.07.15          17          6 15 16.07.15          18          5 16 17.07.15          19          4

so far did not succeed in combining both statements. how can nest both group_by statements calculate sum of amount each single day in each category?

nesting groups like:

summarise(group_by(group_by(testdata, date), category), sum(amount), dates = tostring(date))

   category sum(amount)                                  dates 1        1           6           02.07.15, 02.07.15, 02.07.15 2        2           9                     02.07.15, 03.07.15 3        3          21           04.07.15, 05.07.15, 06.07.15 4        4          53 07.07.15, 10.07.15, 11.07.15, 17.07.15 5        5          57 08.07.15, 12.07.15, 13.07.15, 16.07.15 6        6          44           09.07.15, 14.07.15, 15.07.15

does not work intended.

i have heard of dplyr - summarise weighted data summarise_each not work:

summarise_each(testdata, funs(category)) error not find function category

you can try

 testdata %>%         group_by(date,category) %>%         summarise(amount= sum(amount))

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