merge_data_tables: Merge data tables

In kim: A Toolkit for Behavioral Scientists

Merge data tables

Description

Merge two data.table objects. If there are any duplicated ID values and column names across the two data tables, the cell values in the first data.table will remain intact and the cell values in the second data.table will be discarded for the resulting merged data table.

Usage

merge_data_tables(dt1 = NULL, dt2 = NULL, id = NULL, silent = TRUE)

Arguments

dt1	the first data.table which will remain intact
dt2	the second data.table which will be joined outside of (around) the first data.table. If there are any duplicated ID values and column names across the two data tables, the cell values in the first data.table will remain intact and the cell values in the second data.table will be discarded for the resulting merged data table.
id	name(s) of the column(s) that will contain the ID values in the two data tables. The name(s) of the ID column(s) must be identical in the two data tables.
silent	If silent = TRUE, no message will be printed regarding how many ID values and column names were duplicated. If silent = FALSE, messages will be printed regarding how many column names were duplicated. In cases where only one column was used as the 'id' column (which is the most common case), silent = FALSE will also print messages regarding how many input ID values were duplicated. By default, silent = FALSE.

Value

a data.table object, which merges (joins) the second data.table around the first data.table.

Examples

## Example 1: Typical Usage
data_1 <- data.table::data.table(
id_col = c(4, 2, 1, 3),
a = 3:6,
b = 5:8,
c = c("w", "x", "y", "z"))
data_2 <- data.table::data.table(
id_col = c(1, 99, 4),
e = 6:8,
b = c("p", "q", "r"),
d = c(TRUE, FALSE, FALSE))
# check the two example data tables
data_1
data_2
# check the result of merging the two data tables above and
# note how data_1 (the upper left portion) is intact in the resulting
# data table
merge_data_tables(dt1 = data_1, dt2 = data_2, id = "id_col")
# compare the result with above with the result from the `merge` function
merge(data_1, data_2, by = "id_col", all = TRUE)
## Example 2: Some values can be converted
data_3 <- data.table::data.table(
id_col = 99,
a = "abc",
b = TRUE,
c = TRUE)
data_1
data_3
merge_data_tables(data_1, data_3, id = "id_col")
# In the example above, note how the value of TRUE gets
# converted to 1 in the last row of Column 'b' in the resulting data table
## Example 3: A simpler case
data_4 <- data.table::data.table(
id_col = c(5, 3),
a = c("a", NA))
data_5 <- data.table::data.table(
id_col = 1,
a = 2)
# check the two example data tables
data_4
data_5
merge_data_tables(data_4, data_5, id = "id_col")
## Example 4: Merging data tables using multiple ID columns
data_6 <- data.table::data.table(
id_col_1 = 3:1,
id_col_2 = c("a", "b", "c"),
id_col_3 = 4:6,
a = 7:9,
b = 10:12)
data_7 <- data.table::data.table(
id_col_1 = c(3, 2),
id_col_3 = c(3, 5),
id_col_2 = c("a", "b"),
c = 13:14,
a = 15:16)
# check the example data sets
data_6
data_7
# merge data sets using the three id columns
suppressWarnings(merge_data_tables(
dt1 = data_6,
dt2 = data_7,
id = c("id_col_1", "id_col_2", "id_col_3")))

kim documentation built on Oct. 9, 2023, 5:08 p.m.