Package 'Ipaper'

Title: Collection of personal practical R functions
Description: Awesome functions in R.
Authors: Dongdong Kong [aut, cre]
Maintainer: Dongdong Kong <[email protected]>
License: GPL-3
Version: 0.1.11
Built: 2026-05-08 04:42:18 UTC
Source: https://github.com/rpkgs/Ipaper

Help Index

Add n-day flag

Description

To aggregated data into n-day (e.g. 8-day, 16-day) like MODIS product, a n-day flag is need.

Usage

add_dn(d, days = 8)

Arguments

d

data.frame or data.table
days

Integer number or vector, can't have duplicated value.

Examples

date <- seq.Date(as.Date("2010-01-01"), as.Date("2010-12-31"), by = "day")
d <- data.frame(date)
dnew <- add_dn(d, days = c(8, 16))

apply function for 3d array

Description

NA values will be removed automatically

Usage

apply_3d(
  array,
  dim = 3,
  FUN = rowMeans2,
  by = NULL,
  scale = 1,
  na.rm = TRUE,
  ...
)

Arguments

array

A 3d array
dim

giving the subscripts to split up data by.
FUN

function, should only be row applied function, e.g. matrixStats::rowMeans2, matrixStats::rowMins, matrixStats::rowRanges. Because 3d array will be convert to matrix first, with the aggregated dim in the last dimension.
by

  • If not provided (NULL), the aggregated dim will be disappear. For example, daily precipitation ⁠[nrow, ncol, 31-days]⁠ aggregate into monthly ⁠[nrow, ncol]⁠.

  • If provided, by should be equal to the aggregated dim. For example, daily precipitation ⁠[nrow, ncol, 365-days]⁠ aggregate into monthly ⁠[nrow, ncol, 12-months]⁠. In that situation, by should be equal to 365, and be format(date, '%Y%m').

scale

in the same length of by, or a const value, value_returned = FUN(x)*scale. This parameter is designed for converting monthly to yearly, meanwhile multiply days in month. Currently, same group should have the same scale factor. Otherwise, only the first is used.

See Also

apply_row matrixStats::rowRanges

Examples

set.seed(1)
size <- c(10, 8, 31)
arr <- array(rnorm(10 * 8 * 31), dim = size)

by <- c(rep(1, 10), rep(2, 21))
r2 <- apply_3d(arr, 3, by = by, FUN = rowMeans)

## Not run: 
arr_yearly <- apply_3d(arr, by = year(dates), scale = days_in_month(dates))

## End(Not run)

apply_col

Description

  • apply_col: aggregate by col, return a ⁠[ngrp, ncol]⁠ matrix

  • apply_row: aggregate by row, return a ⁠[nrow, ngrp]⁠ matrix

Usage

apply_col(mat, by, FUN = colMeans2, scale = 1, ...)

apply_row(mat, by, FUN = rowMeans2, scale = 1, ...)

Arguments

mat

matrix, ⁠[nrow, ncol]⁠
by

integer vector, with the dim of ⁠[ntime]⁠
scale

in the same length of by, or a const value, value_returned = FUN(x)*scale. This parameter is designed for converting monthly to yearly, meanwhile multiply days in month. Currently, same group should have the same scale factor. Otherwise, only the first is used.

Details

For example, setting the dimension of mat is ⁠[ngrid, ntime]⁠, if you want to aggregate by time, apply_row should be used here; if you want to aggregate by region (grids), apply_col should be used.

Note

This function also suits for big.matrix object.

Examples

mat <- matrix(rnorm(4 * 6), 4, 6)
mat_bycol <- apply_col(mat, c(1, 1, 2, 2), colMeans)
mat_byrow <- apply_row(mat, c(1, 1, 2, 2, 3, 3), rowMeans)

array_3dTo2d

Description

array_3dTo2d

Usage

array_3dTo2d(array, I_grid = NULL)

array_2dTo3d(array, I_grid = NULL, dim)

Arguments

array

array with the dimension of ⁠[nlon, nlat, ntime]⁠
I_grid

subindex of ⁠[nrow, ncol]⁠
dim

⁠[nrow, ncol]⁠

Value

⁠[nlat*nlon, ntime]⁠

Convert array to data.table

Description

Convert array to data.table

Usage

array2dt(arr, dimnames)

dt2array(dt, value_col = "value")

Arguments

arr

input array
dimnames

list of dimension names, e.g., dimnames(arr)

Value

data.table

Examples

library(Ipaper)

arr <- array(1:6,
  dim = c(2, 3),
  dimnames = list(
    site = c("A", "B"),
    date = c("d1", "d2", "d3")
    # var = c("v1", "v2", "v3", "v4")
  )
)

# array -> dt
dt <- array2dt(arr, dimnames(arr))
print(dt)

# dt -> array
arr2 <- dt2array(dt)
all.equal(arr, arr2)

generate R script of character vector

Description

generate R script of character vector

Usage

char2script(x, collapse = "\"", verbose = TRUE)

code_ChrVec(x, collapse = "\"", verbose = TRUE)

Arguments

x

character vector, data.frame or list.
collapse

an optional character string to separate the results. Not NA_character_.

chunk

Description

chunk

Usage

chunk(x, nchunk = 6)

References

https://stackoverflow.com/questions/3318333/split-a-vector-into-chunks-in-r

clamp

Description

clamp values in the range of lims

Usage

clamp(x, lims = c(0, 1), fill.na = FALSE)

clamp_min(x, value = 0)

clamp_max(x, value = 0)

Arguments

x

Numeric vector
lims

limits
fill.na

If true, values of lims are set to NA; else, values are just constrained in the range of lims.

Examples

clamp(1:10, lims = c(4, 7), fill.na = TRUE)

cut_plevels

Description

cut_plevels

Usage

cut_plevels(x, pvalue = c(0.01, 0.05, 0.1), verbose = FALSE)

Arguments

x

numeric vector
pvalue

p <= ⁠x%⁠, means its significant at ⁠x%⁠ level

Examples

x <- c(-0.09, -0.4, 0.04, 0.15)
cut_plevels(x, verbose = TRUE)

The corresponding date of the first day of month

Description

The corresponding date of the first day of month

Usage

date_ym(date)

date_y(date)

date_yj(year, doy)

date_ydn(year, dn, delta = 8)

Open directory in Explorer

Description

open assign path in windows explorer, and default path is current directory. This function is only designed for windows system.

Usage

dir.show(path = getwd(), verbose = FALSE)

Arguments

path

the path you want to open

dir2

Description

dir2

Usage

dir2(path = ".", pattern = NULL, full.names = TRUE, ...)

Arguments

path

a character vector of full path names; the default corresponds to the working directory, getwd(). Tilde expansion (see path.expand) is performed. Missing values will be ignored. Elements with a marked encoding will be converted to the native encoding (and if that fails, considered non-existent).
pattern

an optional regular expression. Only file names which match the regular expression will be returned.
full.names

a logical value. If TRUE, the directory path is prepended to the file names to give a relative file path. If FALSE, the file names (rather than paths) are returned.
...

other parameters to base::dir()

See Also

base::dir()

dt_day2year

Description

dt_day2year

Usage

dt_day2year(
  dat,
  nmiss_day_per_mon = 3,
  nmiss_MonPerYear = 0,
  nmin_year = 55,
  ...
)

Arguments

dat

A data.table, at least with the columns of c("site", "date", "value")

Split data.table, apply function, and return results in a data.table.

Description

For each subset of a data.table, apply function then combine results into a data.table.

Usage

dt_ddply(
  .data,
  .variables,
  .f = NULL,
  ...,
  .progress = "none",
  .drop = TRUE,
  .parallel = FALSE
)

dt_ldply(
  .data,
  .f = NULL,
  ...,
  .progress = "none",
  .parallel = FALSE,
  .id = NA
)

dt_dlply(
  .data,
  .variables,
  .f = NULL,
  ...,
  .progress = "none",
  .drop = TRUE,
  .parallel = FALSE
)

Arguments

.data

data frame to be processed
.variables

variables to split data frame by, as as.quoted variables, a formula or character vector
.f

A function, specified in one of the following ways:

  • A named function, e.g. mean.

  • An anonymous function, e.g. ⁠\(x) x + 1⁠ or function(x) x + 1.

  • A formula, e.g. ~ .x + 1. Use .x to refer to the first argument. No longer recommended.

  • A string, integer, or list, e.g. "idx", 1, or list("idx", 1) which are shorthand for ⁠\(x) pluck(x, "idx")⁠, ⁠\(x) pluck(x, 1)⁠, and ⁠\(x) pluck(x, "idx", 1)⁠ respectively. Optionally supply .default to set a default value if the indexed element is NULL or does not exist.

[Experimental]

Wrap a function with in_parallel() to declare that it should be performed in parallel. See in_parallel() for more details. Use of ... is not permitted in this context.
...

other arguments passed on to .fun
.progress

name of the progress bar to use, see create_progress_bar
.drop

should combinations of variables that do not appear in the input data be preserved (FALSE) or dropped (TRUE, default)
.parallel

if TRUE, apply function in parallel, using parallel backend provided by foreach

Examples

dt <- data.table(x = 1:10, y = 1:5)
dt_dlply(dt, .(y), ~.[which.max(x)])
dt_ddply(dt, .(y), ~ top_n(., 1, x))

data.frame manipulating function by dplyr::across

Description

data.frame manipulating function by dplyr::across

Usage

dt_round(d, digits = 2)

dt_chr2num(d, fun = as.numeric)

export data

Description

export data

Usage

export(x, path, ..., nthreads = 6)

Details

Support rda, rds, fst, csv, qs

get file name and extension

Description

get file name and extension

Usage

file_ext(file)

file_name(file)

Arguments

file

file path

Examples

file_name("./a.pdf")
file_ext("./a.pdf")

file_size

Description

file_size

Usage

file_size(file)

Arguments

file

file path

flipud and fliplr

Description

flipud and fliplr

Usage

flipud(x, ...)

fliplr(x)

fprintf Print sprintf result into console, just like C style fprintf function

Description

fprintf Print sprintf result into console, just like C style fprintf function

Usage

fprintf(fmt, ...)

Arguments

fmt

a character vector of format strings, each of up to 8192 bytes.
...

other parameters will be passed to sprintf

Examples

cat(fprintf("%s\n", "Hello phenofit!"))

fread_dir

Description

fread_dir

Usage

fread_dir(indir, pattern = "*.csv", ..., .progress = "text", list2df = FALSE)

Arguments

...

others to data.table::fread()

GET or SET working directory

Description

  • getwd_clip: get directory path in clipboard, same as getwd function

  • setwd_clip: set directory path in clipboard, same as setwd function

Usage

getwd_clip()

setwd_clip()

Note

Only works in windows

References

  1. https://stackoverflow.com/questions/10959521/how-to-write-to-clipboard-on-ubuntu-linux-in-r

Examples

## Not run: 
getwd_clip()
setwd_clip()
dir.show()

## End(Not run)

git tools

Description

git tools

Usage

git_push(f = FALSE)

git_commit_amend()

git_commit(title = Sys.time())

git_set_remote(url)

github

Description

github

Usage

github(path = getwd())

grouped_list

Description

grouped_list

Usage

group_map2(df, .f, result.name = "data", ..., .keep = FALSE, .progress = FALSE)

grouped_list

Description

grouped_list

Usage

grouped_list(data, group)

Arguments

data

A list object, length(data) = nrow(group), with elements in the same order as group rows
group

A data.frame or data.table object

ifelse2

Description

ternary operator just like java test ? yes : no

Usage

ifelse2(test, yes, no)

Arguments

test

an object which can be coerced to logical mode.
yes

return values for true elements of test.
no

return values for false elements of test.

Examples

x <- ifelse2(TRUE, 1:4, 1:10)

import data to R

Description

import data to R

Usage

import(path, ..., nthreads = 6)

Arguments

nthreads

The number of threads to use when reading data (the initial value is 1L). When TBB is not available, values greater than 1 emit a warning and fall back to 1.

Details

Support rda, rds, fst, csv, qs2

Attempts to install a package directly from gitee.

Description

Attempts to install a package directly from gitee.

Usage

install_gitee(repo)

Arguments

Repository

address in the format ⁠username/repo[/subdir][@ref|#pull]⁠. Alternatively, you can specify subdir and/or ref using the respective parameters (see below); if both is specified, the values in repo take precedence.

Examples

## Not run: 
install_gitee("adv-r/Ipaper")

## End(Not run)

blind shortcuts to rstudio addin

Description

blind shortcuts to rstudio addin

Usage

key_blind()

killCluster

Description

killCluster

Usage

killCluster()

label_tag

Description

label_tag

Usage

label_tag(labels, tag = TRUE, expression = TRUE, letter_begin = 1)

char2expr(labels)

Arguments

labels

character vector or expression vector
tag

boolean

Examples

label_tag(1:5)
char2expr(1:5)

listk

Description

listk

Usage

listk(...)

Arguments

...

objects, possibly named.

Examples

a <- 1
b <- 1:2
c <- 1:3
l1 <- listk(a, b, c)
l2 <- listk(a, b, c = 1:3)
l3 <- listk(a = 1, b = 1:2, c = 1:3)
l4 <- listk(1, 1:2, c)

plyr function in purrr style

Description

plyr function in purrr style

Usage

llply(.data, .f = NULL, .progress = "none", .parallel = FALSE, ...)

ldply(.data, .f = NULL, ...)

laply(.data, .f = NULL, ...)

map_simplify(.data, .f = NULL, ...)

Arguments

.data

list to be processed
.progress

name of the progress bar to use, see create_progress_bar
.parallel

if TRUE, apply function in parallel, using parallel backend provided by foreach
...

other arguments passed on to .f

References

  1. https://github.com/TylerGrantSmith/purrrgress

Examples

x <- list(a = 1:10, beta = exp(-3:3), logic = c(TRUE, FALSE, FALSE, TRUE))
llply(x, mean, .progress = "text")
llply(x, ~ mean(.x), .progress = TRUE)
llply(x, quantile, probs = 1:3 / 4)

melt_list

Description

melt_list

Usage

melt_list(list, ..., na.rm = TRUE, str2num = TRUE, str2factor = TRUE)

melt_tree(x, names, ...)

Arguments

list

A list object, with the same colnames data.frame in every element.
...

other parameters to melt
na.rm

Boolean
var.name

vector of id variables. Can be integer (variable position) or string (variable name). If blank, will use all non-measured variables.

References

  1. https://stackoverflow.com/questions/15673550/why-is-rbindlist-better-than-rbind

Examples

# data.frame
df <- data.frame(year = 2010, day = 1:3, month = 1, site = "A")
l <- list(a = df, b = df)

melt_list(l, 'id') %>% as_tibble()
melt_list(l, 'id' = 1) %>% as_tibble()
melt_list(set_names(l, NULL), 'id') %>% as_tibble()

# data.table
df <- data.table::data.table(year = 2010, day = 1:3, month = 1, site = "A")
l <- list(a = df, b = df)
melt_list(l, "id")
melt_list(l, id = c("a", "b"))
# int `id` is much more efficient
melt_list(l, id = c(1, 2))

mkdir

Description

mkdir

Usage

mkdir(path)

file_mv(files, outdir)

file_cp(files, outdir)

check_dir(path)

Arguments

path

character vectors

obj_size

Description

Get object size in unit

Usage

obj_size(obj, unit = "Mb")

obj.size(obj, unit = "Mb")

Arguments

obj

Object
unit

"Kb", "Mb" or "Gb"

Examples

obj_size(1:100)

parse_deg

Description

  • *: zero or more

  • +: one or more

  • ⁠?⁠: zero or one

Usage

parse_deg(xs)

convert windows path to wsl

Description

In windows system, conversion will not be applied.

Usage

path.mnt(path)

path_mnt(path)

Arguments

path

character vector of file paths.

pdf_view

Description

pdf_view

Usage

pdf_view(file, ...)

SumatraPDF(path = getwd(), verbose = FALSE)

evince(path = getwd(), verbose = FALSE)

Arguments

file

the path of pdf file

Note

not work in wsl

print.data.table

Description

print.data.table

Usage

## S3 method for class 'data.table'
print(d, n = NULL, ..., maxrows = 1e+06)

Examples

d <- data.table(1:100)
options(datatable.print.nrow = 100)
print(d)

Modified purrr functions with progress bar

Description

Modified purrr functions with progress bar

Usage

pro_map(.x, .f, ..., .progress = FALSE)

Arguments

.x

A list or atomic vector.
.f

A function, specified in one of the following ways:

  • A named function, e.g. mean.

  • An anonymous function, e.g. ⁠\(x) x + 1⁠ or function(x) x + 1.

  • A formula, e.g. ~ .x + 1. Use .x to refer to the first argument. No longer recommended.

  • A string, integer, or list, e.g. "idx", 1, or list("idx", 1) which are shorthand for ⁠\(x) pluck(x, "idx")⁠, ⁠\(x) pluck(x, 1)⁠, and ⁠\(x) pluck(x, "idx", 1)⁠ respectively. Optionally supply .default to set a default value if the indexed element is NULL or does not exist.

[Experimental]

Wrap a function with in_parallel() to declare that it should be performed in parallel. See in_parallel() for more details. Use of ... is not permitted in this context.
...

Additional arguments passed on to the mapped function.

We now generally recommend against using ... to pass additional (constant) arguments to .f. Instead use a shorthand anonymous function: 

# Instead of
x |> map(f, 1, 2, collapse = ",")
# do:
x |> map(\(x) f(x, 1, 2, collapse = ","))

This makes it easier to understand which arguments belong to which function and will tend to yield better error messages.
.progress

Whether to show a progress bar. Use TRUE to turn on a basic progress bar, use a string to give it a name, or see progress_bars for more details.

Helper function for generating progress bar functions

Description

Helper function for generating progress bar functions

Usage

progressively(
  .mapper,
  .farg = NULL,
  .xarg = NULL,
  .yarg = NULL,
  .larg = NULL,
  .atarg = NULL,
  .parg = NULL
)

read csv or xls/xlsx file

Description

read csv or xls/xlsx file

Usage

read_excel(f, ...)

Arguments

...

others to fun, one of data.table::fread(), readxl::read_xls(), read_xlsx()

read_xlsx

Description

read_xlsx

Usage

read_xlsx(file, sheet = 1, ...)

read_xlsx2list

Description

If excel file hava many sheets, this function also works.

Usage

read_xlsx2list(file, ...)

Arguments

file

xlsx or xls file path
...

other parameters to readxl::read_excel()

print the running ID in the console

Description

print the running ID in the console

Usage

runningId(i, step = 1, N, prefix = "")

Arguments

i

the running Id.
step

how long of print step.
N

The number of total iteration
prefix

prefix string

Examples

for (i in 1:10) {
  runningId(i, prefix = "phenofit")
}

Set dimensions of an Object

Description

Set dimensions of an Object

Usage

set_dim(x, dim)

Arguments

x

an R object, for example a matrix, array or data frame.

See Also

base::dim

Examples

x <- 1:12
set_dim(x, c(3, 4))

set_jupyter

Description

set_jupyter

Usage

set_jupyter(width = 10, height = 6, res = 200)

set_dirRoot(verbose = TRUE, dir = getwd())

References

  1. https://stackoverflow.com/questions/42729049/how-to-change-the-size-of-r-plots-in-jupyter

slope_arr

Description

slope_arr

Usage

slope_arr(arr, FUN = rtrend::slope_mk, return.list = FALSE)

Arguments

arr

a matrix (⁠[ngrid, ntime]⁠) or array (⁠[nlon, nlat, ntime]⁠).
FUN

slope functions, see rtrend::slope_mk().
return.list

boolean,

  • TRUE: list(slope, pvalue) will be return

  • FALSE: a array, with the dim of ⁠[nx, ny, 2]⁠.

Value

t, A 3d array, with the dim of ⁠[nx, ny, 2]⁠.

  • t[,,1]: slope

  • t[,,2]: pvalue

which functions

Description

which functions

Usage

which.na(x)

which.notna(x)

which.isnull(x)

which.null(x)

which.notnull(x)

which.notempty(x)

which.empty(x)

which.dup(x)

Arguments

x

numeric vector

write figures into disk

Description

write figure to pdf, tif, png, jpg, svg, or emf, according to file suffix.

Usage

write_fig(
  p,
  file = "Rplot.pdf",
  width = 10,
  height = 5,
  devices = NULL,
  res = 300,
  show = TRUE,
  use.cairo_pdf = TRUE,
  use.file_show = FALSE
)

Arguments

p

could be one of grid, ggplot or ⁠plot expression⁠
file

file path of output figure
width

the width of the device in inches.
height

the height of the device in inches.
devices

can be c("pdf", "tif", "tiff", "png", "jpg", "svg", "emf"). If not specified, devices will be determined according to the postpix of file. The default type is pdf.
res

The nominal resolution in ppi which will be recorded in the bitmap file, if a positive integer. Also used for units other than the default. If not specified, taken as 72 ppi to set the size of text and line widths.
show

Boolean. Whether show file after finished writing?
use.cairo_pdf

This parameter is for pdf type. whether to use grDevices::cairo_pdf? cairo_pdf supports self defined font, but can not create multiple page pdf.
use.file_show

boolean. If true, file.show will be used mandatorily.

See Also

grDevices::cairo_pdf(), grDevices::png(), Cairo::Cairo()

Examples

## Not run: 
library(ggplot2)
p <- ggplot(mpg, aes(class, hwy))
p1 <- p + geom_boxplot2()

## ggplot version
write_fig(p1, "Fig. 1. ggplot.pdf", show = TRUE)
# pdf_view("Fig. 1. ggplot.pdf")
write_fig(p1, "Fig. 1. ggplot", show = TRUE)
write_fig(p1, "Fig. 1. ggplot.pdf", show = TRUE, 
    devices = c("jpg", "png", "svg", "pdf", "tif", "emf"))

## lattice
x <- seq(pi/4, 5 * pi, length.out = 100)
y <- seq(pi/4, 5 * pi, length.out = 100)
r <- as.vector(sqrt(outer(x^2, y^2, "+")))
grid <- expand.grid(x=x, y=y)
grid$z <- cos(r^2) * exp(-r/(pi^3))
p <- levelplot(z~x*y, grid, cuts = 50, scales=list(log="e"), xlab="",
          ylab="", main="Weird Function", sub="with log scales",
          colorkey = FALSE, region = TRUE)

write_fig(p, "fig_lattice", show = TRUE)

## grid expression
g <- grid::circleGrob()
write_fig(g, "fig_grid", show = TRUE)

## R expression
write_fig({
    rx <- range(x <- 10*1:nrow(volcano))
    ry <- range(y <- 10*1:ncol(volcano))
    ry <- ry + c(-1, 1) * (diff(rx) - diff(ry))/2
    tcol <- terrain.colors(12)
    # par(opar); 
    # opar <- par(pty = "s", bg = "lightcyan")
    plot(x = 0, y = 0, type = "n", xlim = rx, ylim = ry, xlab = "", ylab = "")
    u <- par("usr")
    rect(u[1], u[3], u[2], u[4], col = tcol[8], border = "red")
    contour(x, y, volcano, col = tcol[2], lty = "solid", add = TRUE,
            vfont = c("sans serif", "plain"))
    title("A Topographic Map of Maunga Whau", font = 4)
    abline(h = 200*0:4, v = 200*0:4, col = "lightgray", lty = 2, lwd = 0.1)
}, "fig_expr.pdf")

# quote expression also works
expr = quote({
    rx <- range(x <- 10*1:nrow(volcano))
    ry <- range(y <- 10*1:ncol(volcano))
    ry <- ry + c(-1, 1) * (diff(rx) - diff(ry))/2
    tcol <- terrain.colors(12)
    # par(opar); 
    # opar <- par(pty = "s", bg = "lightcyan")
    plot(x = 0, y = 0, type = "n", xlim = rx, ylim = ry, xlab = "", ylab = "")
    u <- par("usr")
    rect(u[1], u[3], u[2], u[4], col = tcol[8], border = "red")
    contour(x, y, volcano, col = tcol[2], lty = "solid", add = TRUE,
            vfont = c("sans serif", "plain"))
    title("A Topographic Map of Maunga Whau", font = 4)
    abline(h = 200*0:4, v = 200*0:4, col = "lightgray", lty = 2, lwd = 0.1)
})
write_fig(expr, "fig_expr2.pdf")

## End(Not run)

write_sheet

Description

Write a single data frame into one sheet of a Workbook. file can be a wbWorkbook object or a file path string. When a file path is given, the workbook is loaded (or created if the file does not exist), the sheet is written, and the file is saved back automatically.

Write a list of data frames into a Workbook, one sheet per element. file can be a wbWorkbook object or a file path string. When a file path is given, the workbook is loaded (or created if absent), written, and saved back automatically. The file extension is normalised to .xlsx.

Usage

write_sheet(d, file, sheetName, overwrite = FALSE)

write_sheets(lst, file, .progress = "none", show = FALSE, overwrite_wb = TRUE)

write_list2xlsx(
  lst,
  file,
  .progress = "none",
  show = FALSE,
  overwrite_wb = TRUE
)

Arguments

d

A data frame.
file

A file path string or an existing wbWorkbook object.
sheetName

Sheet name string.
overwrite

if TRUE and sheetName already exists, replace it.
lst

List of data frames. Names are used as sheet names.
.progress

name of the progress bar to use, see create_progress_bar.
show

open the file after saving (only applies when file is a path).
overwrite_wb

if TRUE (default) always create a fresh workbook when file is a path, even if the file already exists. Set to FALSE to load and append to an existing file.

Value

The (modified) wbWorkbook object, invisibly.

The (modified) wbWorkbook object, invisibly.