How to Replicate SQL's RANK, DENSE_RANK, LEAD, and LAG Functions in R?

How to Emulate SQL's Rank Functions in R

Partitioning and ranking data are common operations in SQL, and R users often need similar functionality. For example, the Oracle ROW_NUMBER(), RANK(), and DENSE_RANK() functions assign integer values to rows based on their order within groups or over an entire table.

The R Equivalent of SQL's Rank Functions

The data.table package provides functionality similar to SQL's partition and ranking capabilities. In R, rank functions are represented as follows:

Rank:

rank(x, ties.method = "min")

Dense Rank:

as.integer(factor(x))

Example

To illustrate the use of these functions, consider the following data:

library(data.table)

DT <- data.table(ID = seq_len(4 * 3), group = rep(1:4, each = 3), value = rnorm(4 * 3),
                 info = c(sample(c("a", "b"), 4 * 2, replace = TRUE),
                         sample(c("c", "d"), 4, replace = TRUE)),
                 key = "ID")

Rank Each ID by Value Within Group

DT[, valRank := rank(-value), by = "group"]

Dense Rank Values by Info Within Group

DT[, infoRank := rank(info, ties.method = "min"), by = "group"]
DT[, infoRankDense := as.integer(factor(info)), by="group"]

Emulating LEAD and LAG

LEAD and LAG functions are used to return the value of the next or previous row in a group. In R, this can be achieved using the J() function:

Previous Row:

DT[, prev := DT[J(group, idRank - 1), value, mult = 'last']]

Next Row:

DT[, nex := DT[J(group, idRank + 1), value, mult = 'first']]

Offsetting the Row Index

To retrieve values from rows further away (e.g., the previous or next two rows), offset the idRank accordingly:

Previous Two Rows:

DT[, prev2 := DT[J(group, idRank - 2), value, mult = 'last']]

Next Two Rows:

DT[, nex2 := DT[J(group, idRank + 2), value, mult = 'first']]

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