bind_rows: Efficiently bind multiple data frames by row and column

In stemangiola/tidyBulk: Brings transcriptomics to the tidyverse

Efficiently bind multiple data frames by row and column

Description

This is an efficient implementation of the common pattern of 'do.call(rbind, dfs)' or 'do.call(cbind, dfs)' for binding many data frames into one.

Arguments

...	Data frames to combine. Each argument can either be a data frame, a list that could be a data frame, or a list of data frames. When row-binding, columns are matched by name, and any missing columns will be filled with NA. When column-binding, rows are matched by position, so all data frames must have the same number of rows. To match by value, not position, see mutate-joins.
.id	Data frame identifier. When '.id' is supplied, a new column of identifiers is created to link each row to its original data frame. The labels are taken from the named arguments to 'bind_rows()'. When a list of data frames is supplied, the labels are taken from the names of the list. If no names are found a numeric sequence is used instead.
add.cell.ids	from Seurat 3.0 A character vector of length(x = c(x, y)). Appends the corresponding values to the start of each objects' cell names.

Details

The output of 'bind_rows()' will contain a column if that column appears in any of the inputs.

Value

'bind_rows()' and 'bind_cols()' return the same type as the first input, either a data frame, 'tbl_df', or 'grouped_df'.

Examples

data(se_mini)

se_mini_tidybulk = se_mini |> tidybulk()
bind_rows(    se_mini_tidybulk, se_mini_tidybulk  )

tt_bind = se_mini_tidybulk |> select(time, condition)
se_mini_tidybulk |> bind_cols(tt_bind)

stemangiola/tidyBulk documentation built on Nov. 21, 2024, 8:14 a.m.