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This article mainly introduces how to use aggregate to group data processing, has a certain reference value, interested friends can refer to, I hope you can learn a lot after reading this article, the following let the editor with you to understand.

Use aggregate to group the data, including summation, mean, maximum, median and so on.

Aggregate is a powerful function. It first groups the data (by rows), and then performs functional statistics on each set of data. It has three uses according to the data object, which are applied to data boxes (data.frame), formulas (formula), and time series (ts) respectively:

Aggregate (x, by, FUN,..., simplify = TRUE) aggregate (formula, data, FUN,..., subset, na.action = na.omit) aggregate (x, nfrequency = 1, FUN = sum, ndeltat = 1, ts.eps = getOption ("ts.eps"),...)

For data grouping processing, for example, some data are as follows:

Dat ID sample1 sample2 sample3 type1 A 12 2 12 A 2 4 9 23 A 4 3 1 34 C 5 5 8 15 C 6 9 7 26 C 3 1 3 37 D 9 10 9 18 D 11 18 12

Group and sum the data according to type, mean or median, etc., take sum as an example:

> temp=aggregate (dat [, 2:4], by=list (dat$type), FUN=sum) > temp Group.1 sample1 sample2 sample31 1 15 17 192 2 19 31 173 3 7 4 4 >

The first parameter must be numeric, so the first column is removed, and the type is removed, and the resulting data Group.1 is the type type.

If you do it for both ID and type, the following results can be obtained:

> temp=aggregate (dat [, 2:4], by=list (dat$ID,dat$type) FUN=sum) > temp Group.1 Group.2 sample1 sample2 sample31 A 1 1 2 22 C 1 5 5 83 D 1 9 10 94 A 22 4 95 C 26 9 76 D 2 11 18 17 A 3 4 3 18 C 3 3 1 3

Mean, median, max and other operations are the same

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