I have data frame like this: 

```
        Date Trade.Name            SKU Sales.in.USD Sum.Units Sales.in.Loc.currency
1 01.03.2010     Brand1 Brand1 CAPS 32      37994.9    4135.5             1123107.3
2 01.03.2010     Brand1 Brand1 CAPS 16      37918.5    5752.7             1167896.0
3 01.03.2010     Brand1 Brand1 CAPS 48      37875.0    2888.9             1245879.5
4 01.04.2010     Brand1 Brand1 CAPS 16      37192.4    6427.6             1099386.2
5 01.04.2010     Brand1 Brand1 CAPS 16      36591.8    5536.0             1073304.0
6 01.03.2010     Brand2 Brand2 CAPS 28          6.4       0.7                 207.4
7 01.03.2010     Brand2 Brand2 CAPS 28          6.4       0.7                 226.5
8 01.04.2010     Brand2 Brand2 CAPS 28          6.3       0.6                 195.4
9 01.04.2010     Brand2 Brand2 CAPS 28          6.3       0.6                 196.1

```

And I want aggregate it by `SKU` and get data frame like this one:

```
        Date Trade.Name Sales.in.USD    Sum.Units Sales.in.Loc.currency
1 01.03.2010     Brand1 113788.39180 113788.39180          113788.39180
2 01.04.2010     Brand1  73784.26045  73784.26045           73784.26045
3 01.03.2010     Brand2     12.71363     12.71363              12.71363
4 01.04.2010     Brand2     12.59949     12.59949              12.59949

```

I know I can use `dplyr` package but I don't know how to summarize it by multiple criteria: by `Date` and by `SKU`