tidyverse | R Documentation |
sftime
objects'tidyverse' methods for sftime
objects. Geometries are sticky, use
as.data.frame
to let dplyr
's own methods drop them. Use
these methods without the .sftime
suffix and after loading the
'tidyverse' package with the generic (or after loading package 'tidyverse').
inner_join.sftime(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...) left_join.sftime(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...) right_join.sftime(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...) full_join.sftime(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...) semi_join.sftime(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...) anti_join.sftime(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...) filter.sftime(.data, ..., .dots) arrange.sftime(.data, ..., .dots) group_by.sftime(.data, ..., add = FALSE) ungroup.sftime(.data, ...) rowwise.sftime(.data, ...) mutate.sftime(.data, ..., .dots) transmute.sftime(.data, ..., .dots) select.sftime(.data, ...) rename.sftime(.data, ...) slice.sftime(.data, ..., .dots) summarise.sftime(.data, ..., .dots, do_union = TRUE, is_coverage = FALSE) summarize.sftime(.data, ..., .dots, do_union = TRUE, is_coverage = FALSE) distinct.sftime(.data, ..., .keep_all = FALSE) ## S3 method for class 'sftime' gather( data, key, value, ..., na.rm = FALSE, convert = FALSE, factor_key = FALSE ) ## S3 method for class 'sftime' pivot_longer( data, cols, names_to = "name", names_prefix = NULL, names_sep = NULL, names_pattern = NULL, names_ptypes = NULL, names_transform = NULL, names_repair = "check_unique", values_to = "value", values_drop_na = FALSE, values_ptypes = NULL, values_transform = NULL, ... ) ## S3 method for class 'sftime' spread(data, key, value, fill = NA, convert = FALSE, drop = TRUE, sep = NULL) sample_n.sftime( tbl, size, replace = FALSE, weight = NULL, .env = parent.frame() ) sample_frac.sftime( tbl, size = 1, replace = FALSE, weight = NULL, .env = parent.frame() ) ## S3 method for class 'sftime' nest(.data, ...) ## S3 method for class 'sftime' unnest(data, ..., .preserve = NULL) ## S3 method for class 'sftime' separate( data, col, into, sep = "[^[:alnum:]]+", remove = TRUE, convert = FALSE, extra = "warn", fill = "warn", ... ) ## S3 method for class 'sftime' unite(data, col, ..., sep = "_", remove = TRUE) ## S3 method for class 'sftime' separate_rows(data, ..., sep = "[^[:alnum:]]+", convert = FALSE)
x |
An object of class |
y |
A pair of data frames, data frame extensions (e.g. a tibble), or lazy data frames (e.g. from dbplyr or dtplyr). See Methods, below, for more details. |
by |
A character vector of variables to join by. If To join by different variables on To join by multiple variables, use a vector with length > 1.
For example, To perform a cross-join, generating all combinations of |
copy |
If |
suffix |
If there are non-joined duplicate variables in |
... |
other arguments |
.data |
An object of class |
.dots |
see corresponding function in package |
add |
see corresponding function in dplyr |
do_union |
logical; in case |
is_coverage |
logical; if |
.keep_all |
see corresponding function in dplyr |
data |
see original function docs |
key |
see original function docs |
value |
see original function docs |
na.rm |
see original function docs |
convert |
see separate_rows |
factor_key |
see original function docs |
cols |
< |
names_to |
A string specifying the name of the column to create
from the data stored in the column names of Can be a character vector, creating multiple columns, if
|
names_prefix |
A regular expression used to remove matching text from the start of each variable name. |
names_sep |
If
If these arguments do not give you enough control, use
|
names_pattern |
If
If these arguments do not give you enough control, use
|
names_ptypes |
A list of column name-prototype pairs.
A prototype (or ptype for short) is a zero-length vector (like If not specified, the type of the columns generated from |
names_transform |
A list of column name-function pairs.
Use these arguments if you need to change the type of specific columns.
For example, |
names_repair |
What happens if the output has invalid column names?
The default, |
values_to |
A string specifying the name of the column to create
from the data stored in cell values. If |
values_drop_na |
If |
values_ptypes |
A list of column name-prototype pairs.
A prototype (or ptype for short) is a zero-length vector (like If not specified, the type of the columns generated from |
values_transform |
A list of column name-function pairs.
Use these arguments if you need to change the type of specific columns.
For example, |
fill |
see original function docs |
drop |
see original function docs |
sep |
see separate_rows |
tbl |
see original function docs |
size |
see original function docs |
replace |
see original function docs |
weight |
see original function docs |
.env |
see original function docs |
.preserve |
see unnest |
col |
see separate |
into |
see separate |
remove |
see separate |
extra |
see separate |
For _join
methods: An object of class sftime
representing the joining result of x
and y
. See
mutate-joins
.
For filter
: See filter
.
For arrange
: See arrange
.
For group_by
and ungroup
: A grouped sftime
object. See arrange
.
For rowwise
: An sftime
object. See
rowwise
.
For mutate
and transmute
: See
mutate
.
For select
: See select
. If the active
time column is not explicitly selected, a sf
object is returned.
For rename
: See rename
.
For slice
: See slice
.
For summarize
and summarise
: See
summarise
.
For distinct
: See distinct
.
For gather
: See gather
.
g1 <- st_sfc(st_point(1:2), st_point(c(5, 8)), st_point(c(2, 9))) x1 <- st_sftime(a = 1:3, geometry = g1, time = Sys.time()) g2 <- st_sfc(st_point(c(4, 6)), st_point(c(4, 6)), st_point(c(4, 6))) x2 <- st_sftime(a = 2:4, geometry = g2, time = Sys.time()) library(dplyr) ## inner_join inner_join(x1, as.data.frame(x2), by = "a") # note: the active time column is # time.x and the active geometry column geometry.x inner_join(x2, as.data.frame(x1), by = "a") ## left_join left_join(x1, as.data.frame(x2), by = "a") left_join(x2, as.data.frame(x1), by = "a") ## right_join right_join(x1, as.data.frame(x2), by = "a") right_join(x2, as.data.frame(x1), by = "a") ## full_join full_join(x1, as.data.frame(x2), by = "a") full_join(x2, as.data.frame(x1), by = "a") ## semi_join semi_join(x1, as.data.frame(x2), by = "a") semi_join(x2, as.data.frame(x1), by = "a") ## anti_join anti_join(x1, as.data.frame(x2), by = "a") anti_join(x2, as.data.frame(x1), by = "a") ## filter filter(x1, a <= 2) ## arrange arrange(x1, dplyr::desc(a)) ## group_by group_by(x1, time) ## ungroup ungroup(group_by(x1, time)) ## rowwise x1 %>% mutate(a1 = 5:7) %>% rowwise() %>% mutate(a2 = mean(a, a1)) ## mutate x1 %>% mutate(a1 = 5:7) ## transmute x1 %>% transmute(a1 = 5:7) ## select x1 %>% select(-time) %>% select(geometry) ## rename x1 %>% rename(a1 = a) ## slice x1 %>% slice(1:2) ## summarise x1 %>% summarise(time = mean(time)) x1 %>% summarize(time = mean(time)) ## distinct x1 %>% distinct(geometry) ## gather library(tidyr) x1 %>% mutate(a1 = 5:7) %>% gather(key = "variable", value = "value", a, a1) ## pivot_longer x1 %>% mutate(a1 = 5:7) %>% pivot_longer(cols = c("a", "a1"), names_to = "variable", values_to = "value") ## spread x1 %>% mutate(a1 = 5:7) %>% gather(key = "variable", value = "value", a, a1) %>% spread(key = "variable", value = "value") ## sample_n set.seed(234) x1 %>% sample_n(size = 10, replace = TRUE) ## sample_frac x1 %>% sample_frac(size = 10, replace = TRUE) %>% sample_frac(size = 0.1, replace = FALSE) ## nest x1 %>% nest(a1 = -time) ## unnest x1 %>% mutate(a1 = list(1, c(1, 2), 5)) %>% unnest(a1) ## separate x1 %>% mutate(x = c(NA, "a.b", "a.d")) %>% separate(x, c("A", "B")) ## unite x1 %>% mutate(x = c(NA, "a.b", "a.d")) %>% separate(x, c("A", "B")) %>% unite(x, c("A", "B")) ## separate_rows x1 %>% mutate(z = c("1", "2,3,4", "5,6")) %>% separate_rows(z, convert = TRUE)
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