So I have a data frame that has a date column, an hour column and a series of other numerical columns. Each row in the data frame is 1 hour of 1 day for an entire year.

The data frame looks like this:

```
Date Hour Melbourne Southern Flagstaff
1 2009-05-01 0 0 5 17
2 2009-05-01 2 0 2 1
3 2009-05-01 1 0 11 0
4 2009-05-01 3 0 3 8
5 2009-05-01 4 0 1 0
6 2009-05-01 5 0 49 79
7 2009-05-01 6 0 425 610
```

The hours are out of order because this is subsetted from another data frame.

I would like to sum the values in the numerical columns by month and possibly by day. Does anyone know how I can do this?

Answer:

I create the data set by

```
data <- read.table( text=" Date Hour Melbourne Southern Flagstaff
1 2009-05-01 0 0 5 17
2 2009-05-01 2 0 2 1
3 2009-05-01 1 0 11 0
4 2009-05-01 3 0 3 8
5 2009-05-01 4 0 1 0
6 2009-05-01 5 0 49 79
7 2009-05-01 6 0 425 610",
header=TRUE,stringsAsFactors=FALSE)
```

You can do the summation with the function `aggregate`

:

```
byday <- aggregate(cbind(Melbourne,Southern,Flagstaff)~Date,
data=data,FUN=sum)
library(lubridate)
bymonth <- aggregate(cbind(Melbourne,Southern,Flagstaff)~month(Date),
data=data,FUN=sum)
```

Look at `?aggregate`

to understand the function better. Starting with the last argument (because that makes explaining easier) the arguments do the following:

`FUN`

is the function that should be used for the aggregation. I use`sum`

to sum up the values, but i could also be`mean`

,`max`

or some function you wrote yourself.`data`

is used to indicate that data frame that I want to aggregate.- The first argument tells the function what exactly I want to aggregate. On the left side of the
`~`

, I indicate the variables I want to aggregate. If there is more than one, they are combined with`cbind`

. On the right hand side is the variable by which the data should be split. Putting`Date`

means that aggregate will sum up the variables for each distinct value of`Date`

.

For the aggregation by month, I used the function `month`

from the package `lubridate`

. It does what one expects: it returns a numeric value indicating the month for a given date. Maybe you first need to install the package by `install.packages("lubridate")`

.

If you prefer not to use lubridate, you could do the following instead:

```
data <- transform(data,month=as.numeric(format(as.Date(Date),"%m")))
bymonth <- aggregate(cbind(Melbourne,Southern,Flagstaff)~month,
data=data,FUN=sum)
```

Here I added a new column to data that contains the month and then aggregated by that column.

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