slice | R Documentation |
slice()
lets you index rows by their (integer) locations. It allows you
to select, remove, and duplicate rows. It is accompanied by a number of
helpers for common use cases:
slice_head()
and slice_tail()
select the first or last rows.
slice_sample()
randomly selects rows.
slice_min()
and slice_max()
select rows with highest or lowest values
of a variable.
If .data
is a grouped_df, the operation will be performed on each group,
so that (e.g.) slice_head(df, n = 5)
will select the first five rows in
each group.
## S3 method for class 'Seurat'
slice(.data, ..., .by = NULL, .preserve = FALSE)
## S3 method for class 'Seurat'
slice_sample(
.data,
...,
n = NULL,
prop = NULL,
by = NULL,
weight_by = NULL,
replace = FALSE
)
## S3 method for class 'Seurat'
slice_head(.data, ..., n, prop, by = NULL)
## S3 method for class 'Seurat'
slice_tail(.data, ..., n, prop, by = NULL)
## S3 method for class 'Seurat'
slice_min(
.data,
order_by,
...,
n,
prop,
by = NULL,
with_ties = TRUE,
na_rm = FALSE
)
## S3 method for class 'Seurat'
slice_max(
.data,
order_by,
...,
n,
prop,
by = NULL,
with_ties = TRUE,
na_rm = FALSE
)
.data |
A data frame, data frame extension (e.g. a tibble), or a lazy data frame (e.g. from dbplyr or dtplyr). See Methods, below, for more details. |
... |
For Provide either positive values to keep, or negative values to drop. The values provided must be either all positive or all negative. Indices beyond the number of rows in the input are silently ignored. For |
.by , by |
< |
.preserve |
Relevant when the |
n , prop |
Provide either A negative value of |
weight_by |
< |
replace |
Should sampling be performed with ( |
order_by |
< |
with_ties |
Should ties be kept together? The default, |
na_rm |
Should missing values in |
Slice does not work with relational databases because they have no
intrinsic notion of row order. If you want to perform the equivalent
operation, use filter()
and row_number()
.
An object of the same type as .data
. The output has the following
properties:
Each row may appear 0, 1, or many times in the output.
Columns are not modified.
Groups are not modified.
Data frame attributes are preserved.
These function are generics, which means that packages can provide implementations (methods) for other classes. See the documentation of individual methods for extra arguments and differences in behaviour.
Methods available in currently loaded packages:
slice()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice")}.
slice_head()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_head")}.
slice_tail()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_tail")}.
slice_min()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_min")}.
slice_max()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_max")}.
slice_sample()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_sample")}.
These function are generics, which means that packages can provide implementations (methods) for other classes. See the documentation of individual methods for extra arguments and differences in behaviour.
Methods available in currently loaded packages:
slice()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice")}.
slice_head()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_head")}.
slice_tail()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_tail")}.
slice_min()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_min")}.
slice_max()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_max")}.
slice_sample()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_sample")}.
These function are generics, which means that packages can provide implementations (methods) for other classes. See the documentation of individual methods for extra arguments and differences in behaviour.
Methods available in currently loaded packages:
slice()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice")}.
slice_head()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_head")}.
slice_tail()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_tail")}.
slice_min()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_min")}.
slice_max()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_max")}.
slice_sample()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_sample")}.
These function are generics, which means that packages can provide implementations (methods) for other classes. See the documentation of individual methods for extra arguments and differences in behaviour.
Methods available in currently loaded packages:
slice()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice")}.
slice_head()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_head")}.
slice_tail()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_tail")}.
slice_min()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_min")}.
slice_max()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_max")}.
slice_sample()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_sample")}.
These function are generics, which means that packages can provide implementations (methods) for other classes. See the documentation of individual methods for extra arguments and differences in behaviour.
Methods available in currently loaded packages:
slice()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice")}.
slice_head()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_head")}.
slice_tail()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_tail")}.
slice_min()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_min")}.
slice_max()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_max")}.
slice_sample()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_sample")}.
These function are generics, which means that packages can provide implementations (methods) for other classes. See the documentation of individual methods for extra arguments and differences in behaviour.
Methods available in currently loaded packages:
slice()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice")}.
slice_head()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_head")}.
slice_tail()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_tail")}.
slice_min()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_min")}.
slice_max()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_max")}.
slice_sample()
: \Sexpr[stage=render,results=rd]{dplyr:::methods_rd("slice_sample")}.
Other single table verbs:
arrange()
,
mutate()
,
rename()
,
summarise()
data(pbmc_small)
pbmc_small |> slice(1)
# Slice group-wise using .by
pbmc_small |> slice(1:2, .by=groups)
# slice_sample() allows you to random select with or without replacement
pbmc_small |> slice_sample(n=5)
# if using replacement, and duplicate cells are returned, a tibble will be
# returned because duplicate cells cannot exist in Seurat objects
pbmc_small |> slice_sample(n=1, replace=TRUE) # returns Seurat
pbmc_small |> slice_sample(n=100, replace=TRUE) # returns tibble
# weight by a variable
pbmc_small |> slice_sample(n=5, weight_by=nCount_RNA)
# sample by group
pbmc_small |> slice_sample(n=5, by=groups)
# sample using proportions
pbmc_small |> slice_sample(prop=0.10)
# First rows based on existing order
pbmc_small |> slice_head(n=5)
# Last rows based on existing order
pbmc_small |> slice_tail(n=5)
# Rows with minimum and maximum values of a metadata variable
pbmc_small |> slice_min(nFeature_RNA, n=5)
# slice_min() and slice_max() may return more rows than requested
# in the presence of ties.
pbmc_small |> slice_min(nFeature_RNA, n=2)
# Use with_ties=FALSE to return exactly n matches
pbmc_small |> slice_min(nFeature_RNA, n=2, with_ties=FALSE)
# Or use additional variables to break the tie:
pbmc_small |> slice_min(tibble::tibble(nFeature_RNA, nCount_RNA), n=2)
# Use by for group-wise operations
pbmc_small |> slice_min(nFeature_RNA, n=5, by=groups)
# Rows with minimum and maximum values of a metadata variable
pbmc_small |> slice_max(nFeature_RNA, n=5)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.