Title: | Access Google Sheets using the Sheets API V4 |
---|---|
Description: | Interact with Google Sheets through the Sheets API v4 <https://developers.google.com/sheets/api>. "API" is an acronym for "application programming interface"; the Sheets API allows users to interact with Google Sheets programmatically, instead of via a web browser. The "v4" refers to the fact that the Sheets API is currently at version 4. This package can read and write both the metadata and the cell data in a Sheet. |
Authors: | Jennifer Bryan [cre, aut] , Posit Software, PBC [cph, fnd] |
Maintainer: | Jennifer Bryan <[email protected]> |
License: | MIT + file LICENSE |
Version: | 1.1.1.9000 |
Built: | 2024-10-31 20:28:50 UTC |
Source: | https://github.com/tidyverse/googlesheets4 |
Many functions in googlesheets4 use a range
argument to target specific
cells. The Sheets v4 API expects user-specified ranges to be expressed via
its A1 notation,
but googlesheets4 accepts and converts a few alternative specifications
provided by the functions in the cellranger package. Of course,
you can always provide A1-style ranges directly to functions like
read_sheet()
or range_read_cells()
. Why would you use the
cellranger helpers? Some ranges are practically impossible to
express in A1 notation, specifically when you want to describe rectangles
with some bounds that are specified and others determined by the data.
ss <- gs4_example("mini-gap") # Specify only the rows or only the columns read_sheet(ss, range = cell_rows(1:3)) read_sheet(ss, range = cell_cols("C:D")) read_sheet(ss, range = cell_cols(1)) # Specify upper or lower bound on row or column read_sheet(ss, range = cell_rows(c(NA, 4))) read_sheet(ss, range = cell_cols(c(NA, "D"))) read_sheet(ss, range = cell_rows(c(3, NA))) read_sheet(ss, range = cell_cols(c(2, NA))) read_sheet(ss, range = cell_cols(c("C", NA))) # Specify a partially open rectangle read_sheet(ss, range = cell_limits(c(2, 3), c(NA, NA)), col_names = FALSE) read_sheet(ss, range = cell_limits(c(1, 2), c(NA, 4)))
ss <- gs4_example("mini-gap") # Specify only the rows or only the columns read_sheet(ss, range = cell_rows(1:3)) read_sheet(ss, range = cell_cols("C:D")) read_sheet(ss, range = cell_cols(1)) # Specify upper or lower bound on row or column read_sheet(ss, range = cell_rows(c(NA, 4))) read_sheet(ss, range = cell_cols(c(NA, "D"))) read_sheet(ss, range = cell_rows(c(3, NA))) read_sheet(ss, range = cell_cols(c(2, NA))) read_sheet(ss, range = cell_cols(c("C", NA))) # Specify a partially open rectangle read_sheet(ss, range = cell_limits(c(2, 3), c(NA, NA)), col_names = FALSE) read_sheet(ss, range = cell_limits(c(1, 2), c(NA, 4)))
Some aspects of googlesheets4 behaviour can be controlled via an option.
local_gs4_quiet(env = parent.frame()) with_gs4_quiet(code)
local_gs4_quiet(env = parent.frame()) with_gs4_quiet(code)
env |
The environment to use for scoping |
code |
Code to execute quietly |
The googlesheets4_quiet
option can be used to suppress messages from
googlesheets4. By default, googlesheets4 always messages, i.e. it is not
quiet.
Set googlesheets4_quiet
to TRUE
to suppress messages, by one of these
means, in order of decreasing scope:
Put options(googlesheets4_quiet = TRUE)
in a start-up file, such as
.Rprofile
, or in your R script
Use local_gs4_quiet()
to silence googlesheets4 in a specific scope
Use with_gs4_quiet()
to run a small bit of code silently
local_gs4_quiet()
and with_gs4_quiet()
follow the conventions of the
the withr package (https://withr.r-lib.org).
Read about googlesheets4's main auth function, gs4_auth()
. It is powered
by the gargle package, which consults several options:
Default Google user or, more precisely, email
: see
gargle::gargle_oauth_email()
Whether or where to cache OAuth tokens: see
gargle::gargle_oauth_cache()
Whether to prefer "out-of-band" auth: see
gargle::gargle_oob_default()
Application Default Credentials: see gargle::credentials_app_default()
# message: "Creating new Sheet ..." (ss <- gs4_create("gs4-quiet-demo", sheets = "alpha")) # message: "Editing ..., Writing ..." range_write(ss, data = data.frame(x = 1, y = "a")) # suppress messages for a small amount of code with_gs4_quiet( ss %>% sheet_append(data.frame(x = 2, y = "b")) ) # message: "Writing ..., Appending ..." ss %>% sheet_append(data.frame(x = 3, y = "c")) # suppress messages until end of current scope local_gs4_quiet() ss %>% sheet_append(data.frame(x = 4, y = "d")) # see that all the data was, in fact, written read_sheet(ss) # clean up gs4_find("gs4-quiet-demo") %>% googledrive::drive_trash()
# message: "Creating new Sheet ..." (ss <- gs4_create("gs4-quiet-demo", sheets = "alpha")) # message: "Editing ..., Writing ..." range_write(ss, data = data.frame(x = 1, y = "a")) # suppress messages for a small amount of code with_gs4_quiet( ss %>% sheet_append(data.frame(x = 2, y = "b")) ) # message: "Writing ..., Appending ..." ss %>% sheet_append(data.frame(x = 3, y = "c")) # suppress messages until end of current scope local_gs4_quiet() ss %>% sheet_append(data.frame(x = 4, y = "d")) # see that all the data was, in fact, written read_sheet(ss) # clean up gs4_find("gs4-quiet-demo") %>% googledrive::drive_trash()
Authorize googlesheets4 to view and manage your Google Sheets. This function is a
wrapper around gargle::token_fetch()
.
By default, you are directed to a web browser, asked to sign in to your Google account, and to grant googlesheets4 permission to operate on your behalf with Google Sheets. By default, with your permission, these user credentials are cached in a folder below your home directory, from where they can be automatically refreshed, as necessary. Storage at the user level means the same token can be used across multiple projects and tokens are less likely to be synced to the cloud by accident.
gs4_auth( email = gargle::gargle_oauth_email(), path = NULL, subject = NULL, scopes = "spreadsheets", cache = gargle::gargle_oauth_cache(), use_oob = gargle::gargle_oob_default(), token = NULL )
gs4_auth( email = gargle::gargle_oauth_email(), path = NULL, subject = NULL, scopes = "spreadsheets", cache = gargle::gargle_oauth_cache(), use_oob = gargle::gargle_oob_default(), token = NULL )
email |
Optional. If specified,
Defaults to the option named |
path |
JSON identifying the service account, in one of the forms
supported for the |
subject |
An optional subject claim. Specify this if you wish to use the
service account represented by |
scopes |
One or more API scopes. Each scope can be specified in full or,
for Sheets API-specific scopes, in an abbreviated form that is recognized by
See https://developers.google.com/identity/protocols/oauth2/scopes#sheets for details on the permissions for each scope. |
cache |
Specifies the OAuth token cache. Defaults to the option named
|
use_oob |
Whether to use out-of-band authentication (or, perhaps, a
variant implemented by gargle and known as "pseudo-OOB") when first
acquiring the token. Defaults to the value returned by
If the OAuth client is provided implicitly by a wrapper package, its type
probably defaults to the value returned by
|
token |
A token with class Token2.0 or an object of
httr's class |
Most users, most of the time, do not need to call gs4_auth()
explicitly – it is triggered by the first action that requires
authorization. Even when called, the default arguments often suffice.
However, when necessary, gs4_auth()
allows the user to explicitly:
Declare which Google identity to use, via an email
specification.
Use a service account token or workload identity federation via
path
.
Bring your own token
.
Customize scopes
.
Use a non-default cache
folder or turn caching off.
Explicitly request out-of-band (OOB) auth via use_oob
.
If you are interacting with R within a browser (applies to RStudio
Server, Posit Workbench, Posit Cloud, and Google Colaboratory), you need
OOB auth or the pseudo-OOB variant. If this does not happen
automatically, you can request it explicitly with use_oob = TRUE
or,
more persistently, by setting an option via
options(gargle_oob_default = TRUE)
.
The choice between conventional OOB or pseudo-OOB auth is determined
by the type of OAuth client. If the client is of the "installed" type,
use_oob = TRUE
results in conventional OOB auth. If the client is of
the "web" type, use_oob = TRUE
results in pseudo-OOB auth. Packages
that provide a built-in OAuth client can usually detect which type of
client to use. But if you need to set this explicitly, use the
"gargle_oauth_client_type"
option:
options(gargle_oauth_client_type = "web") # pseudo-OOB # or, alternatively options(gargle_oauth_client_type = "installed") # conventional OOB
For details on the many ways to find a token, see
gargle::token_fetch()
. For deeper control over auth, use
gs4_auth_configure()
to bring your own OAuth client or API key.
To learn more about gargle options, see gargle::gargle_options.
Other auth functions:
gs4_auth_configure()
,
gs4_deauth()
,
gs4_scopes()
# load/refresh existing credentials, if available # otherwise, go to browser for authentication and authorization gs4_auth() # indicate the specific identity you want to auth as gs4_auth(email = "[email protected]") # force a new browser dance, i.e. don't even try to use existing user # credentials gs4_auth(email = NA) # use a 'read only' scope, so it's impossible to edit or delete Sheets gs4_auth(scopes = "spreadsheets.readonly") # use a service account token gs4_auth(path = "foofy-83ee9e7c9c48.json")
# load/refresh existing credentials, if available # otherwise, go to browser for authentication and authorization gs4_auth() # indicate the specific identity you want to auth as gs4_auth(email = "[email protected]") # force a new browser dance, i.e. don't even try to use existing user # credentials gs4_auth(email = NA) # use a 'read only' scope, so it's impossible to edit or delete Sheets gs4_auth(scopes = "spreadsheets.readonly") # use a service account token gs4_auth(path = "foofy-83ee9e7c9c48.json")
These functions give more control over and visibility into the auth
configuration than gs4_auth()
does. gs4_auth_configure()
lets the user specify their own:
OAuth client, which is used when obtaining a user token.
API key. If googlesheets4 is de-authorized via gs4_deauth()
, all
requests are sent with an API key in lieu of a token.
See the vignette("get-api-credentials", package = "gargle")
for more.
If the user does not configure these settings, internal defaults
are used.
gs4_oauth_client()
and gs4_api_key()
retrieve the
currently configured OAuth client and API key, respectively.
gs4_auth_configure(client, path, api_key, app = deprecated()) gs4_api_key() gs4_oauth_client()
gs4_auth_configure(client, path, api_key, app = deprecated()) gs4_api_key() gs4_oauth_client()
client |
A Google OAuth client, presumably constructed via
|
path |
JSON downloaded from Google Cloud Console, containing a client id and
secret, in one of the forms supported for the |
api_key |
API key. |
app |
gs4_auth_configure()
: An object of R6 class
gargle::AuthState, invisibly.
gs4_oauth_client()
: the current user-configured OAuth client.
gs4_api_key()
: the current user-configured API key.
Other auth functions:
gs4_auth()
,
gs4_deauth()
,
gs4_scopes()
# see and store the current user-configured OAuth client (probably `NULL`) (original_client <- gs4_oauth_client()) # see and store the current user-configured API key (probably `NULL`) (original_api_key <- gs4_api_key()) # the preferred way to configure your own client is via a JSON file # downloaded from Google Developers Console # this example JSON is indicative, but fake path_to_json <- system.file( "extdata", "client_secret_installed.googleusercontent.com.json", package = "gargle" ) gs4_auth_configure(path = path_to_json) # this is also obviously a fake API key gs4_auth_configure(api_key = "the_key_I_got_for_a_google_API") # confirm the changes gs4_oauth_client() gs4_api_key() # restore original auth config gs4_auth_configure(client = original_client, api_key = original_api_key)
# see and store the current user-configured OAuth client (probably `NULL`) (original_client <- gs4_oauth_client()) # see and store the current user-configured API key (probably `NULL`) (original_api_key <- gs4_api_key()) # the preferred way to configure your own client is via a JSON file # downloaded from Google Developers Console # this example JSON is indicative, but fake path_to_json <- system.file( "extdata", "client_secret_installed.googleusercontent.com.json", package = "gargle" ) gs4_auth_configure(path = path_to_json) # this is also obviously a fake API key gs4_auth_configure(api_key = "the_key_I_got_for_a_google_API") # confirm the changes gs4_oauth_client() gs4_api_key() # restore original auth config gs4_auth_configure(client = original_client, api_key = original_api_key)
Visits a Google Sheet in your default browser, if session is interactive.
gs4_browse(ss)
gs4_browse(ss)
ss |
Something that identifies a Google Sheet:
Processed through |
The Sheet's browser URL, invisibly.
gs4_example("mini-gap") %>% gs4_browse()
gs4_example("mini-gap") %>% gs4_browse()
Creates an entirely new (spread)Sheet (or, in Excel-speak, workbook).
Optionally, you can also provide names and/or data for the initial set of
(work)sheets. Any initial data provided via sheets
is styled as a table,
as described in sheet_write()
.
gs4_create(name = gs4_random(), ..., sheets = NULL)
gs4_create(name = gs4_random(), ..., sheets = NULL)
name |
The name of the new spreadsheet. |
... |
Optional spreadsheet properties that can be set through this API endpoint, such as locale and time zone. |
sheets |
Optional input for initializing (work)sheets. If unspecified, the Sheets API automatically creates an empty "Sheet1". You can provide a vector of sheet names, a data frame, or a (possibly named) list of data frames. See the examples. |
The input ss
, as an instance of sheets_id
Wraps the spreadsheets.create
endpoint:
There is an article on writing Sheets:
Other write functions:
gs4_formula()
,
range_delete()
,
range_flood()
,
range_write()
,
sheet_append()
,
sheet_write()
gs4_create("gs4-create-demo-1") gs4_create("gs4-create-demo-2", locale = "en_CA") gs4_create( "gs4-create-demo-3", locale = "fr_FR", timeZone = "Europe/Paris" ) gs4_create( "gs4-create-demo-4", sheets = c("alpha", "beta") ) my_data <- data.frame(x = 1) gs4_create( "gs4-create-demo-5", sheets = my_data ) gs4_create( "gs4-create-demo-6", sheets = list(chickwts = head(chickwts), mtcars = head(mtcars)) ) # Clean up gs4_find("gs4-create-demo") %>% googledrive::drive_trash()
gs4_create("gs4-create-demo-1") gs4_create("gs4-create-demo-2", locale = "en_CA") gs4_create( "gs4-create-demo-3", locale = "fr_FR", timeZone = "Europe/Paris" ) gs4_create( "gs4-create-demo-4", sheets = c("alpha", "beta") ) my_data <- data.frame(x = 1) gs4_create( "gs4-create-demo-5", sheets = my_data ) gs4_create( "gs4-create-demo-6", sheets = list(chickwts = head(chickwts), mtcars = head(mtcars)) ) # Clean up gs4_find("gs4-create-demo") %>% googledrive::drive_trash()
Put googlesheets4 into a de-authorized state. Instead of sending a token,
googlesheets4 will send an API key. This can be used to access public
resources for which no Google sign-in is required. This is handy for using
googlesheets4 in a non-interactive setting to make requests that do not
require a token. It will prevent the attempt to obtain a token
interactively in the browser. The user can configure their own API key
via gs4_auth_configure()
and retrieve that key via
gs4_api_key()
.
In the absence of a user-configured key, a built-in default key is used.
gs4_deauth()
gs4_deauth()
Other auth functions:
gs4_auth_configure()
,
gs4_auth()
,
gs4_scopes()
gs4_deauth() gs4_user() # get metadata on the public 'deaths' spreadsheet gs4_example("deaths") %>% gs4_get()
gs4_deauth() gs4_user() # get metadata on the public 'deaths' spreadsheet gs4_example("deaths") %>% gs4_get()
Returns a list of selected Sheets API v4 endpoints, as stored inside the
googlesheets4 package. The names of this list (or the id
sub-elements) are
the nicknames that can be used to specify an endpoint in
request_generate()
. For each endpoint, we store its nickname or id
, the
associated HTTP method
, the path
, and details about the parameters. This
list is derived programmatically from the Sheets API v4 Discovery
Document (https://www.googleapis.com/discovery/v1/apis/sheets/v4/rest
).
gs4_endpoints(i = NULL)
gs4_endpoints(i = NULL)
i |
The name(s) or integer index(ices) of the endpoints to return. Optional. By default, the entire list is returned. |
A list containing some or all of the subset of the Sheets API v4 endpoints that are used internally by googlesheets4.
str(gs4_endpoints(), max.level = 2) gs4_endpoints("sheets.spreadsheets.values.get") gs4_endpoints(4)
str(gs4_endpoints(), max.level = 2) gs4_endpoints("sheets.spreadsheets.values.get") gs4_endpoints(4)
googlesheets4 makes a variety of world-readable example Sheets available for
use in documentation and reprexes. These functions help you access the
example Sheets. See vignette("example-sheets", package = "googlesheets4")
for more.
gs4_examples(matches) gs4_example(matches)
gs4_examples(matches) gs4_example(matches)
matches |
A regular expression that matches the name of the desired
example Sheet(s). |
gs4_example()
: a sheets_id
gs4_examples()
: a named vector of all built-in examples, with class
drive_id
gs4_examples() gs4_examples("gap") gs4_example("gapminder") gs4_example("deaths")
gs4_examples() gs4_examples("gap") gs4_example("gapminder") gs4_example("deaths")
Finds your Google Sheets. This is a very thin wrapper around
googledrive::drive_find()
, that specifies you want to list Drive files
where type = "spreadsheet"
. Therefore, note that this will require auth for
googledrive! See the article Using googlesheets4 with googledrive
if you want to coordinate auth between googlesheets4 and googledrive. This
function will emit an informational message if you are currently logged in
with both googlesheets4 and googledrive, but as different users.
gs4_find(...)
gs4_find(...)
... |
Arguments (other than |
An object of class dribble
, a tibble with one row per file.
# see all your Sheets gs4_find() # see 5 Sheets, prioritized by creation time x <- gs4_find(order_by = "createdTime desc", n_max = 5) x # hoist the creation date, using other packages in the tidyverse # x %>% # tidyr::hoist(drive_resource, created_on = "createdTime") %>% # dplyr::mutate(created_on = as.Date(created_on))
# see all your Sheets gs4_find() # see 5 Sheets, prioritized by creation time x <- gs4_find(order_by = "createdTime desc", n_max = 5) x # hoist the creation date, using other packages in the tidyverse # x %>% # tidyr::hoist(drive_resource, created_on = "createdTime") %>% # dplyr::mutate(created_on = as.Date(created_on))
Creates a data frame that is useful for filling a spreadsheet, when you just
need a sheet to experiment with. The data frame has n
rows and m
columns
with these properties:
Column names match what Sheets displays: "A", "B", "C", and so on.
Inner cell values reflect the coordinates where each value will land in
the sheet, in A1-notation. So the first row is "B2", "C2", and so on.
Note that this n
-row data frame will occupy n + 1
rows in the sheet,
because the column names occupy the first row.
gs4_fodder(n = 10, m = n)
gs4_fodder(n = 10, m = n)
n |
Number of rows. |
m |
Number of columns. |
A data frame of character vectors.
gs4_fodder() gs4_fodder(5, 3)
gs4_fodder() gs4_fodder(5, 3)
In order to write a formula into Google Sheets, you need to store it as an
object of class googlesheets4_formula
. This is how we distinguish a
"regular" character string from a string that should be interpreted as a
formula. googlesheets4_formula
is an S3 class implemented using the vctrs package.
gs4_formula(x = character())
gs4_formula(x = character())
x |
Character. |
An S3 vector of class googlesheets4_formula
.
Other write functions:
gs4_create()
,
range_delete()
,
range_flood()
,
range_write()
,
sheet_append()
,
sheet_write()
dat <- data.frame(x = c(1, 5, 3, 2, 4, 6)) ss <- gs4_create("gs4-formula-demo", sheets = dat) ss summaries <- tibble::tribble( ~desc, ~summaries, "max", "=max(A:A)", "sum", "=sum(A:A)", "min", "=min(A:A)", "sparkline", "=SPARKLINE(A:A, {\"color\", \"blue\"})" ) # explicitly declare a column as `googlesheets4_formula` summaries$summaries <- gs4_formula(summaries$summaries) summaries range_write(ss, data = summaries, range = "C1", reformat = FALSE) miscellany <- tibble::tribble( ~desc, ~example, "hyperlink", "=HYPERLINK(\"http://www.google.com/\",\"Google\")", "image", "=IMAGE(\"https://www.google.com/images/srpr/logo3w.png\")" ) miscellany$example <- gs4_formula(miscellany$example) miscellany sheet_write(miscellany, ss = ss) # clean up gs4_find("gs4-formula-demo") %>% googledrive::drive_trash()
dat <- data.frame(x = c(1, 5, 3, 2, 4, 6)) ss <- gs4_create("gs4-formula-demo", sheets = dat) ss summaries <- tibble::tribble( ~desc, ~summaries, "max", "=max(A:A)", "sum", "=sum(A:A)", "min", "=min(A:A)", "sparkline", "=SPARKLINE(A:A, {\"color\", \"blue\"})" ) # explicitly declare a column as `googlesheets4_formula` summaries$summaries <- gs4_formula(summaries$summaries) summaries range_write(ss, data = summaries, range = "C1", reformat = FALSE) miscellany <- tibble::tribble( ~desc, ~example, "hyperlink", "=HYPERLINK(\"http://www.google.com/\",\"Google\")", "image", "=IMAGE(\"https://www.google.com/images/srpr/logo3w.png\")" ) miscellany$example <- gs4_formula(miscellany$example) miscellany sheet_write(miscellany, ss = ss) # clean up gs4_find("gs4-formula-demo") %>% googledrive::drive_trash()
Retrieve spreadsheet-specific metadata, such as details on the individual (work)sheets or named ranges.
gs4_get()
complements googledrive::drive_get()
, which
returns metadata that exists for any file on Drive.
gs4_get(ss)
gs4_get(ss)
ss |
Something that identifies a Google Sheet:
Processed through |
A list with S3 class googlesheets4_spreadsheet
, for printing
purposes.
Wraps the spreadsheets.get
endpoint:
gs4_get(gs4_example("mini-gap"))
gs4_get(gs4_example("mini-gap"))
Reports whether googlesheets4 has stored a token, ready for use in downstream requests.
gs4_has_token()
gs4_has_token()
Logical.
Other low-level API functions:
gs4_token()
,
request_generate()
,
request_make()
gs4_has_token()
gs4_has_token()
Generates a random name, suitable for a newly created Sheet, using
ids::adjective_animal()
.
gs4_random(n = 1)
gs4_random(n = 1)
n |
Number of names to generate. |
A character vector.
gs4_random()
gs4_random()
When called with no arguments, gs4_scopes()
returns a named character
vector of scopes associated with the Sheets API. If gs4_scopes(scopes =)
is
given, an abbreviated entry such as "sheets.readonly"
is expanded to a full
scope ("https://www.googleapis.com/auth/sheets.readonly"
in this case).
Unrecognized scopes are passed through unchanged.
gs4_scopes(scopes = NULL)
gs4_scopes(scopes = NULL)
scopes |
One or more API scopes. Each scope can be specified in full or,
for Sheets API-specific scopes, in an abbreviated form that is recognized by
See https://developers.google.com/identity/protocols/oauth2/scopes#sheets for details on the permissions for each scope. |
A character vector of scopes.
https://developers.google.com/identity/protocols/oauth2/scopes#sheets for details on the permissions for each scope.
Other auth functions:
gs4_auth_configure()
,
gs4_auth()
,
gs4_deauth()
gs4_scopes("spreadsheets") gs4_scopes("spreadsheets.readonly") gs4_scopes("drive") gs4_scopes()
gs4_scopes("spreadsheets") gs4_scopes("spreadsheets.readonly") gs4_scopes("drive") gs4_scopes()
For internal use or for those programming around the Sheets API.
Returns a token pre-processed with httr::config()
. Most users
do not need to handle tokens "by hand" or, even if they need some
control, gs4_auth()
is what they need. If there is no current
token, gs4_auth()
is called to either load from cache or
initiate OAuth2.0 flow.
If auth has been deactivated via gs4_deauth()
, gs4_token()
returns NULL
.
gs4_token()
gs4_token()
A request
object (an S3 class provided by httr).
Other low-level API functions:
gs4_has_token()
,
request_generate()
,
request_make()
req <- request_generate( "sheets.spreadsheets.get", list(spreadsheetId = "abc"), token = gs4_token() ) req
req <- request_generate( "sheets.spreadsheets.get", list(spreadsheetId = "abc"), token = gs4_token() ) req
Reveals the email address of the user associated with the current token. If no token has been loaded yet, this function does not initiate auth.
gs4_user()
gs4_user()
An email address or, if no token has been loaded, NULL
.
gargle::token_userinfo()
, gargle::token_email()
,
gargle::token_tokeninfo()
gs4_user()
gs4_user()
Applies automatic resizing to either columns or rows of a (work)sheet. The width or height of targeted columns or rows, respectively, is determined from the current cell contents. This only affects the appearance of a sheet in the browser and doesn't affect its values or dimensions in any way.
range_autofit(ss, sheet = NULL, range = NULL, dimension = c("columns", "rows"))
range_autofit(ss, sheet = NULL, range = NULL, dimension = c("columns", "rows"))
ss |
Something that identifies a Google Sheet:
Processed through |
sheet |
Sheet to modify, in the sense of "worksheet" or "tab". You can identify a sheet by name, with a string, or by position, with a number. Ignored if the sheet is specified via |
range |
Which columns or rows to resize. Optional. If you want to resize
all columns or all rows, use |
dimension |
Ignored if |
The input ss
, as an instance of sheets_id
Makes an AutoResizeDimensionsRequest
:
dat <- tibble::tibble( fruit = c("date", "lime", "pear", "plum") ) ss <- gs4_create("range-autofit-demo", sheets = dat) ss # open in the browser gs4_browse(ss) # shrink column A to fit the short fruit names range_autofit(ss) # in the browser, notice how the column width shrank # send some longer fruit names dat2 <- tibble::tibble( fruit = c("cucumber", "honeydew") ) ss %>% sheet_append(dat2) # in the browser, see that column A is now too narrow to show the data range_autofit(ss) # in the browser, see the column A reveals all the data now # clean up gs4_find("range-autofit-demo") %>% googledrive::drive_trash()
dat <- tibble::tibble( fruit = c("date", "lime", "pear", "plum") ) ss <- gs4_create("range-autofit-demo", sheets = dat) ss # open in the browser gs4_browse(ss) # shrink column A to fit the short fruit names range_autofit(ss) # in the browser, notice how the column width shrank # send some longer fruit names dat2 <- tibble::tibble( fruit = c("cucumber", "honeydew") ) ss %>% sheet_append(dat2) # in the browser, see that column A is now too narrow to show the data range_autofit(ss) # in the browser, see the column A reveals all the data now # clean up gs4_find("range-autofit-demo") %>% googledrive::drive_trash()
Deletes a range of cells and shifts other cells into the deleted area. There are several related tasks that are implemented by other functions:
To clear cells of their value and/or format, use range_clear()
.
To delete an entire (work)sheet, use sheet_delete()
.
To change the dimensions of a (work)sheet, use sheet_resize()
.
range_delete(ss, sheet = NULL, range, shift = NULL)
range_delete(ss, sheet = NULL, range, shift = NULL)
ss |
Something that identifies a Google Sheet:
Processed through |
sheet |
Sheet to delete, in the sense of "worksheet" or "tab". You can identify a sheet by name, with a string, or by position, with a number. Ignored if the sheet is specified via |
range |
Cells to delete. There are a couple differences between
|
shift |
Must be one of "up" or "left", if specified. Required if |
The input ss
, as an instance of sheets_id
Makes a DeleteRangeRequest
:
Other write functions:
gs4_create()
,
gs4_formula()
,
range_flood()
,
range_write()
,
sheet_append()
,
sheet_write()
# create a data frame to use as initial data df <- gs4_fodder(10) # create Sheet ss <- gs4_create("range-delete-example", sheets = list(df)) # delete some rows range_delete(ss, range = "2:4") # delete a column range_delete(ss, range = "C") # delete a rectangle and specify how to shift remaining cells range_delete(ss, range = "B3:F4", shift = "left") # clean up gs4_find("range-delete-example") %>% googledrive::drive_trash()
# create a data frame to use as initial data df <- gs4_fodder(10) # create Sheet ss <- gs4_create("range-delete-example", sheets = list(df)) # delete some rows range_delete(ss, range = "2:4") # delete a column range_delete(ss, range = "C") # delete a rectangle and specify how to shift remaining cells range_delete(ss, range = "B3:F4", shift = "left") # clean up gs4_find("range-delete-example") %>% googledrive::drive_trash()
range_flood()
"floods" a range of cells with the same content.
range_clear()
is a wrapper that handles the common special case of
clearing the cell value. Both functions, by default, also clear the format,
but this can be specified via reformat
.
range_flood(ss, sheet = NULL, range = NULL, cell = NULL, reformat = TRUE) range_clear(ss, sheet = NULL, range = NULL, reformat = TRUE)
range_flood(ss, sheet = NULL, range = NULL, cell = NULL, reformat = TRUE) range_clear(ss, sheet = NULL, range = NULL, reformat = TRUE)
ss |
Something that identifies a Google Sheet:
Processed through |
sheet |
Sheet to write into, in the sense of "worksheet" or "tab". You can identify a sheet by name, with a string, or by position, with a number. |
range |
A cell range to read from. If |
cell |
The value to fill the cells in the |
reformat |
Logical, indicates whether to reformat the affected cells.
Currently googlesheets4 provides no real support for formatting, so
|
The input ss
, as an instance of sheets_id
Makes a RepeatCellRequest
:
Other write functions:
gs4_create()
,
gs4_formula()
,
range_delete()
,
range_write()
,
sheet_append()
,
sheet_write()
# create a data frame to use as initial data df <- gs4_fodder(10) # create Sheet ss <- gs4_create("range-flood-demo", sheets = list(df)) # default behavior (`cell = NULL`): clear value and format range_flood(ss, range = "A1:B3") # clear value but preserve format range_flood(ss, range = "C1:D3", reformat = FALSE) # send new value range_flood(ss, range = "4:5", cell = ";-)") # send formatting # WARNING: use these unexported, internal functions at your own risk! # This not (yet) officially supported, but it's possible. blue_background <- googlesheets4:::CellData( userEnteredFormat = googlesheets4:::new( "CellFormat", backgroundColor = googlesheets4:::new( "Color", red = 159 / 255, green = 183 / 255, blue = 196 / 255 ) ) ) range_flood(ss, range = "I:J", cell = blue_background) # range_clear() is a shortcut where `cell = NULL` always range_clear(ss, range = "9:9") range_clear(ss, range = "10:10", reformat = FALSE) # clean up gs4_find("range-flood-demo") %>% googledrive::drive_trash()
# create a data frame to use as initial data df <- gs4_fodder(10) # create Sheet ss <- gs4_create("range-flood-demo", sheets = list(df)) # default behavior (`cell = NULL`): clear value and format range_flood(ss, range = "A1:B3") # clear value but preserve format range_flood(ss, range = "C1:D3", reformat = FALSE) # send new value range_flood(ss, range = "4:5", cell = ";-)") # send formatting # WARNING: use these unexported, internal functions at your own risk! # This not (yet) officially supported, but it's possible. blue_background <- googlesheets4:::CellData( userEnteredFormat = googlesheets4:::new( "CellFormat", backgroundColor = googlesheets4:::new( "Color", red = 159 / 255, green = 183 / 255, blue = 196 / 255 ) ) ) range_flood(ss, range = "I:J", cell = blue_background) # range_clear() is a shortcut where `cell = NULL` always range_clear(ss, range = "9:9") range_clear(ss, range = "10:10", reformat = FALSE) # clean up gs4_find("range-flood-demo") %>% googledrive::drive_trash()
This is the main "read" function of the googlesheets4 package. It goes by two names, because we want it to make sense in two contexts:
read_sheet()
evokes other table-reading functions, like
readr::read_csv()
and readxl::read_excel()
. The sheet
in this case
refers to a Google (spread)Sheet.
range_read()
is the right name according to the naming convention used
throughout the googlesheets4 package.
read_sheet()
and range_read()
are synonyms and you can use either one.
range_read( ss, sheet = NULL, range = NULL, col_names = TRUE, col_types = NULL, na = "", trim_ws = TRUE, skip = 0, n_max = Inf, guess_max = min(1000, n_max), .name_repair = "unique" ) read_sheet( ss, sheet = NULL, range = NULL, col_names = TRUE, col_types = NULL, na = "", trim_ws = TRUE, skip = 0, n_max = Inf, guess_max = min(1000, n_max), .name_repair = "unique" )
range_read( ss, sheet = NULL, range = NULL, col_names = TRUE, col_types = NULL, na = "", trim_ws = TRUE, skip = 0, n_max = Inf, guess_max = min(1000, n_max), .name_repair = "unique" ) read_sheet( ss, sheet = NULL, range = NULL, col_names = TRUE, col_types = NULL, na = "", trim_ws = TRUE, skip = 0, n_max = Inf, guess_max = min(1000, n_max), .name_repair = "unique" )
ss |
Something that identifies a Google Sheet:
Processed through |
sheet |
Sheet to read, in the sense of "worksheet" or "tab". You can identify a sheet by name, with a string, or by position, with a number. Ignored if the sheet is specified via |
range |
A cell range to read from. If |
col_names |
|
col_types |
Column types. Either |
na |
Character vector of strings to interpret as missing values. By default, blank cells are treated as missing data. |
trim_ws |
Logical. Should leading and trailing whitespace be trimmed from cell contents? |
skip |
Minimum number of rows to skip before reading anything, be it
column names or data. Leading empty rows are automatically skipped, so this
is a lower bound. Ignored if |
n_max |
Maximum number of data rows to parse into the returned tibble.
Trailing empty rows are automatically skipped, so this is an upper bound on
the number of rows in the result. Ignored if |
guess_max |
Maximum number of data rows to use for guessing column types. |
.name_repair |
Handling of column names. By default, googlesheets4
ensures column names are not empty and are unique. There is full support
for |
A tibble
Column types must be specified in a single string of readr-style short codes, e.g. "cci?l" means "character, character, integer, guess, logical". This is not where googlesheets4's col spec will end up, but it gets the ball rolling in a way that is consistent with readr and doesn't reinvent any wheels.
Shortcodes for column types:
_
or -
: Skip. Data in a skipped column is still requested from the
API (the high-level functions in this package are rectangle-oriented), but
is not parsed into the data frame output.
?
: Guess. A type is guessed for each cell and then a consensus type is
selected for the column. If no atomic type is suitable for all cells, a
list-column is created, in which each cell is converted to an R object of
"best" type. If no column types are specified, i.e. col_types = NULL
,
all types are guessed.
l
: Logical.
i
: Integer. This type is never guessed from the data, because Sheets
have no formal cell type for integers.
d
or n
: Numeric, in the sense of "double".
D
: Date. This type is never guessed from the data, because date cells
are just serial datetimes that bear a "date" format.
t
: Time of day. This type is never guessed from the data, because time
cells are just serial datetimes that bear a "time" format. Not implemented
yet; returns POSIXct.
T
: Datetime, specifically POSIXct.
c
: Character.
C
: Cell. This type is unique to googlesheets4. This returns raw cell
data, as an R list, which consists of everything sent by the Sheets API for
that cell. Has S3 type of "CELL_SOMETHING"
and "SHEETS_CELL"
. Mostly
useful internally, but exposed for those who want direct access to, e.g.,
formulas and formats.
L
: List, as in "list-column". Each cell is a length-1 atomic vector of
its discovered type.
Still to come: duration (code will be :
) and factor (code will be
f
).
ss <- gs4_example("deaths") read_sheet(ss, range = "A5:F15") read_sheet(ss, range = "other!A5:F15", col_types = "ccilDD") read_sheet(ss, range = "arts_data", col_types = "ccilDD") read_sheet(gs4_example("mini-gap")) read_sheet( gs4_example("mini-gap"), sheet = "Europe", range = "A:D", col_types = "ccid" )
ss <- gs4_example("deaths") read_sheet(ss, range = "A5:F15") read_sheet(ss, range = "other!A5:F15", col_types = "ccilDD") read_sheet(ss, range = "arts_data", col_types = "ccilDD") read_sheet(gs4_example("mini-gap")) read_sheet( gs4_example("mini-gap"), sheet = "Europe", range = "A:D", col_types = "ccid" )
This low-level function returns cell data in a tibble with one row per cell.
This tibble has integer variables row
and col
(referring to location
with the Google Sheet), an A1-style reference loc
, and a cell
list-column. The flagship function read_sheet()
, a.k.a. range_read()
, is
what most users are looking for, rather than range_read_cells()
.
read_sheet()
is basically range_read_cells()
(this function), followed by
spread_sheet()
, which looks after reshaping and column typing. But if you
really want raw cell data from the API, range_read_cells()
is for you!
range_read_cells( ss, sheet = NULL, range = NULL, skip = 0, n_max = Inf, cell_data = c("default", "full"), discard_empty = TRUE )
range_read_cells( ss, sheet = NULL, range = NULL, skip = 0, n_max = Inf, cell_data = c("default", "full"), discard_empty = TRUE )
ss |
Something that identifies a Google Sheet:
Processed through |
sheet |
Sheet to read, in the sense of "worksheet" or "tab". You can identify a sheet by name, with a string, or by position, with a number. Ignored if the sheet is specified via |
range |
A cell range to read from. If |
skip |
Minimum number of rows to skip before reading anything, be it
column names or data. Leading empty rows are automatically skipped, so this
is a lower bound. Ignored if |
n_max |
Maximum number of data rows to parse into the returned tibble.
Trailing empty rows are automatically skipped, so this is an upper bound on
the number of rows in the result. Ignored if |
cell_data |
How much detail to get for each cell. |
discard_empty |
Whether to discard cells that have no data. Literally,
we check for an |
A tibble with one row per cell in the range
.
Wraps the spreadsheets.get
endpoint:
range_read_cells(gs4_example("deaths"), range = "arts_data") # if you want detailed and exhaustive cell data, do this range_read_cells( gs4_example("formulas-and-formats"), cell_data = "full", discard_empty = FALSE )
range_read_cells(gs4_example("deaths"), range = "arts_data") # if you want detailed and exhaustive cell data, do this range_read_cells( gs4_example("formulas-and-formats"), cell_data = "full", discard_empty = FALSE )
This function uses a quick-and-dirty method to read a Sheet that bypasses the
Sheets API and, instead, parses a CSV representation of the data. This can be
much faster than range_read()
– noticeably so for "large" spreadsheets.
There are real downsides, though, so we recommend this approach only when the
speed difference justifies it. Here are the limitations we must accept to get
faster reading:
Only formatted cell values are available, not underlying values or details on the formats.
We can't target a named range as the range
.
We have no access to the data type of a cell, i.e. we don't know that it's logical, numeric, or datetime. That must be re-discovered based on the CSV data (or specified by the user).
Auth and error handling have to be handled a bit differently internally, which may lead to behaviour that differs from other functions in googlesheets4.
Note that the Sheets API is still used to retrieve metadata on the target
Sheet, in order to support range specification. range_speedread()
also
sends an auth token with the request, unless a previous call to
gs4_deauth()
has put googlesheets4 into a de-authorized state.
range_speedread(ss, sheet = NULL, range = NULL, skip = 0, ...)
range_speedread(ss, sheet = NULL, range = NULL, skip = 0, ...)
ss |
Something that identifies a Google Sheet:
Processed through |
sheet |
Sheet to read, in the sense of "worksheet" or "tab". You can identify a sheet by name, with a string, or by position, with a number. Ignored if the sheet is specified via |
range |
A cell range to read from. If |
skip |
Minimum number of rows to skip before reading anything, be it
column names or data. Leading empty rows are automatically skipped, so this
is a lower bound. Ignored if |
... |
Passed along to the CSV parsing function (currently
|
A tibble
if (require("readr")) { # since cell type is not available, use readr's col type specification range_speedread( gs4_example("deaths"), sheet = "other", range = "A5:F15", col_types = cols( Age = col_integer(), `Date of birth` = col_date("%m/%d/%Y"), `Date of death` = col_date("%m/%d/%Y") ) ) } # write a Sheet that, by default, is NOT world-readable (ss <- sheet_write(chickwts)) # demo that range_speedread() sends a token, which is why we can read this range_speedread(ss) # clean up googledrive::drive_trash(ss)
if (require("readr")) { # since cell type is not available, use readr's col type specification range_speedread( gs4_example("deaths"), sheet = "other", range = "A5:F15", col_types = cols( Age = col_integer(), `Date of birth` = col_date("%m/%d/%Y"), `Date of death` = col_date("%m/%d/%Y") ) ) } # write a Sheet that, by default, is NOT world-readable (ss <- sheet_write(chickwts)) # demo that range_speedread() sends a token, which is why we can read this range_speedread(ss) # clean up googledrive::drive_trash(ss)
Writes a data frame into a range of cells. Main differences from
sheet_write()
(a.k.a. write_sheet()
):
Narrower scope. range_write()
literally targets some cells, not a whole
(work)sheet.
The edited rectangle is not explicitly styled as a table. Nothing special is done re: formatting a header row or freezing rows.
Column names can be suppressed. This means that, although data
must
be a data frame (at least for now), range_write()
can actually be used
to write arbitrary data.
The target (spread)Sheet and (work)sheet must already exist. There is no ability to create a Sheet or add a worksheet.
The target sheet dimensions are not "trimmed" to shrink-wrap the data
.
However, the sheet might gain rows and/or columns, in order to write
data
to the user-specified range
.
If you just want to add rows to an existing table, the function you probably
want is sheet_append()
.
range_write( ss, data, sheet = NULL, range = NULL, col_names = TRUE, reformat = TRUE )
range_write( ss, data, sheet = NULL, range = NULL, col_names = TRUE, reformat = TRUE )
ss |
Something that identifies a Google Sheet:
Processed through |
data |
A data frame. |
sheet |
Sheet to write into, in the sense of "worksheet" or "tab". You can identify a sheet by name, with a string, or by position, with a number. Ignored if the sheet is specified via |
range |
Where to write. This
|
col_names |
Logical, indicates whether to send the column names of
|
reformat |
Logical, indicates whether to reformat the affected cells.
Currently googlesheets4 provides no real support for formatting, so
|
The input ss
, as an instance of sheets_id
The range
argument of range_write()
is special, because the Sheets API
can implement it in 2 different ways:
If range
represents exactly 1 cell, like "B3", it is taken as the start
(or upper left corner) of the targeted cell rectangle. The edited cells are
determined implicitly by the extent of the data
we are writing. This
frees you from doing fiddly range computations based on the dimensions of
the data
.
If range
describes a rectangle with multiple cells, it is interpreted
as the actual rectangle to edit. It is possible to describe a rectangle
that is unbounded on the right (e.g. "B2:4"), on the bottom (e.g. "A4:C"),
or on both the right and the bottom (e.g.
cell_limits(c(2, 3), c(NA, NA))
. Note that all cells inside the
rectangle receive updated data and format. Important implication: if the
data
object isn't big enough to fill the target rectangle, the cells that
don't receive new data are effectively cleared, i.e. the existing value
and format are deleted.
If sheet size needs to change, makes an UpdateSheetPropertiesRequest
:
The main data write is done via an UpdateCellsRequest
:
Other write functions:
gs4_create()
,
gs4_formula()
,
range_delete()
,
range_flood()
,
sheet_append()
,
sheet_write()
# create a Sheet with some initial, empty (work)sheets (ss <- gs4_create("range-write-demo", sheets = c("alpha", "beta"))) df <- data.frame( x = 1:3, y = letters[1:3] ) # write df somewhere other than the "upper left corner" range_write(ss, data = df, range = "D6") # view your magnificent creation in the browser gs4_browse(ss) # send data of disparate types to a 1-row rectangle dat <- tibble::tibble( string = "string", logical = TRUE, datetime = Sys.time() ) range_write(ss, data = dat, sheet = "beta", col_names = FALSE) # send data of disparate types to a 1-column rectangle dat <- tibble::tibble( x = list(Sys.time(), FALSE, "string") ) range_write(ss, data = dat, range = "beta!C5", col_names = FALSE) # clean up gs4_find("range-write-demo") %>% googledrive::drive_trash()
# create a Sheet with some initial, empty (work)sheets (ss <- gs4_create("range-write-demo", sheets = c("alpha", "beta"))) df <- data.frame( x = 1:3, y = letters[1:3] ) # write df somewhere other than the "upper left corner" range_write(ss, data = df, range = "D6") # view your magnificent creation in the browser gs4_browse(ss) # send data of disparate types to a 1-row rectangle dat <- tibble::tibble( string = "string", logical = TRUE, datetime = Sys.time() ) range_write(ss, data = dat, sheet = "beta", col_names = FALSE) # send data of disparate types to a 1-column rectangle dat <- tibble::tibble( x = list(Sys.time(), FALSE, "string") ) range_write(ss, data = dat, range = "beta!C5", col_names = FALSE) # clean up gs4_find("range-write-demo") %>% googledrive::drive_trash()
Generate a request, using knowledge of the Sheets API from its Discovery
Document (https://www.googleapis.com/discovery/v1/apis/sheets/v4/rest
). Use
request_make()
to execute the request. Most users should, instead, use
higher-level wrappers that facilitate common tasks, such as reading or
writing worksheets or cell ranges. The functions here are intended for
internal use and for programming around the Sheets API.
request_generate()
lets you provide the bare minimum of input.
It takes a nickname for an endpoint and:
Uses the API spec to look up the method
, path
, and base_url
.
Checks params
for validity and completeness with respect to the
endpoint. Uses params
for URL endpoint substitution and separates
remaining parameters into those destined for the body versus the query.
Adds an API key to the query if and only if token = NULL
.
request_generate( endpoint = character(), params = list(), key = NULL, token = gs4_token() )
request_generate( endpoint = character(), params = list(), key = NULL, token = gs4_token() )
endpoint |
Character. Nickname for one of the selected Sheets API v4
endpoints built into googlesheets4. Learn more in |
params |
Named list. Parameters destined for endpoint URL substitution, the query, or the body. |
key |
API key. Needed for requests that don't contain a token. The need
for an API key in the absence of a token is explained in Google's document
"Credentials, access, security, and identity"
( |
token |
Set this to |
list()
Components are method
, url
, body
, and token
,
suitable as input for request_make()
.
gargle::request_develop()
, gargle::request_build()
,
gargle::request_make()
Other low-level API functions:
gs4_has_token()
,
gs4_token()
,
request_make()
req <- request_generate( "sheets.spreadsheets.get", list(spreadsheetId = gs4_example("deaths")), key = "PRETEND_I_AM_AN_API_KEY", token = NULL ) req
req <- request_generate( "sheets.spreadsheets.get", list(spreadsheetId = gs4_example("deaths")), key = "PRETEND_I_AM_AN_API_KEY", token = NULL ) req
Low-level function to execute a Sheets API request. Most users should, instead, use higher-level wrappers that facilitate common tasks, such as reading or writing worksheets or cell ranges. The functions here are intended for internal use and for programming around the Sheets API.
request_make(x, ..., encode = "json")
request_make(x, ..., encode = "json")
x |
List. Holds the components for an HTTP request, presumably created
with |
... |
Optional arguments passed through to the HTTP method. |
encode |
If the body is a named list, how should it be encoded? This has
the same meaning as |
make_request()
is a very thin wrapper around gargle::request_retry()
,
only adding the googlesheets4 user agent. Typically the input has been
created with request_generate()
or gargle::request_build()
and the output
is processed with process_response()
.
gargle::request_retry()
retries requests that error with 429 RESOURCE_EXHAUSTED
. Its basic scheme is exponential backoff, with one tweak
that is very specific to the Sheets API, which has documented usage limits:
"a limit of 500 requests per 100 seconds per project and 100 requests per 100 seconds per user"
Note that the "project" here means everyone using googlesheets4 who hasn't configured their own OAuth client. This is potentially a lot of users, all acting independently.
If you hit the "100 requests per 100 seconds per user" limit (which really does mean YOU), the first wait time is a bit more than 100 seconds, then we revert to exponential backoff.
If you experience lots of retries, especially with 100 second delays, it
means your use of googlesheets4 is more than casual and it's time for you
to get your own OAuth client or use a service account token. This is explained
in the gargle vignette vignette("get-api-credentials", package = "gargle")
.
Object of class response
from httr.
Other low-level API functions:
gs4_has_token()
,
gs4_token()
,
request_generate()
Adds one or more (work)sheets to an existing (spread)Sheet. Note that sheet names must be unique.
sheet_add(ss, sheet = NULL, ..., .before = NULL, .after = NULL)
sheet_add(ss, sheet = NULL, ..., .before = NULL, .after = NULL)
ss |
Something that identifies a Google Sheet:
Processed through |
sheet |
One or more new sheet names. If unspecified, one new sheet is added and Sheets autogenerates a name of the form "SheetN". |
... |
Optional parameters to specify additional properties, common to
all of the new sheet(s). Not relevant to most users. Specify fields of the
|
.before , .after
|
Optional specification of where to put the new sheet(s). Specify, at most, one of |
The input ss
, as an instance of sheets_id
Makes a batch of AddSheetRequest
s (one per sheet):
Other worksheet functions:
sheet_append()
,
sheet_copy()
,
sheet_delete()
,
sheet_properties()
,
sheet_relocate()
,
sheet_rename()
,
sheet_resize()
,
sheet_write()
ss <- gs4_create("add-sheets-to-me") # the only required argument is the target spreadsheet ss %>% sheet_add() # but you CAN specify sheet name and/or position ss %>% sheet_add("apple", .after = 1) ss %>% sheet_add("banana", .after = "apple") # add multiple sheets at once ss %>% sheet_add(c("coconut", "dragonfruit")) # keeners can even specify additional sheet properties ss %>% sheet_add( sheet = "eggplant", .before = 1, gridProperties = list( rowCount = 3, columnCount = 6, frozenRowCount = 1 ) ) # get an overview of the sheets sheet_properties(ss) # clean up gs4_find("add-sheets-to-me") %>% googledrive::drive_trash()
ss <- gs4_create("add-sheets-to-me") # the only required argument is the target spreadsheet ss %>% sheet_add() # but you CAN specify sheet name and/or position ss %>% sheet_add("apple", .after = 1) ss %>% sheet_add("banana", .after = "apple") # add multiple sheets at once ss %>% sheet_add(c("coconut", "dragonfruit")) # keeners can even specify additional sheet properties ss %>% sheet_add( sheet = "eggplant", .before = 1, gridProperties = list( rowCount = 3, columnCount = 6, frozenRowCount = 1 ) ) # get an overview of the sheets sheet_properties(ss) # clean up gs4_find("add-sheets-to-me") %>% googledrive::drive_trash()
Adds one or more new rows after the last row with data in a (work)sheet, increasing the row dimension of the sheet if necessary.
sheet_append(ss, data, sheet = 1)
sheet_append(ss, data, sheet = 1)
ss |
Something that identifies a Google Sheet:
Processed through |
data |
A data frame. |
sheet |
Sheet to append to, in the sense of "worksheet" or "tab". You can identify a sheet by name, with a string, or by position, with a number. |
The input ss
, as an instance of sheets_id
Makes an AppendCellsRequest
:
Other write functions:
gs4_create()
,
gs4_formula()
,
range_delete()
,
range_flood()
,
range_write()
,
sheet_write()
Other worksheet functions:
sheet_add()
,
sheet_copy()
,
sheet_delete()
,
sheet_properties()
,
sheet_relocate()
,
sheet_rename()
,
sheet_resize()
,
sheet_write()
# we will recreate the table of "other" deaths from this example Sheet (deaths <- gs4_example("deaths") %>% range_read(range = "other_data", col_types = "????DD")) # split the data into 3 pieces, which we will send separately deaths_one <- deaths[1:5, ] deaths_two <- deaths[6, ] deaths_three <- deaths[7:10, ] # create a Sheet and send the first chunk of data ss <- gs4_create("sheet-append-demo", sheets = list(deaths = deaths_one)) # append a single row ss %>% sheet_append(deaths_two) # append remaining rows ss %>% sheet_append(deaths_three) # read and check against the original deaths_replica <- range_read(ss, col_types = "????DD") identical(deaths, deaths_replica) # clean up gs4_find("sheet-append-demo") %>% googledrive::drive_trash()
# we will recreate the table of "other" deaths from this example Sheet (deaths <- gs4_example("deaths") %>% range_read(range = "other_data", col_types = "????DD")) # split the data into 3 pieces, which we will send separately deaths_one <- deaths[1:5, ] deaths_two <- deaths[6, ] deaths_three <- deaths[7:10, ] # create a Sheet and send the first chunk of data ss <- gs4_create("sheet-append-demo", sheets = list(deaths = deaths_one)) # append a single row ss %>% sheet_append(deaths_two) # append remaining rows ss %>% sheet_append(deaths_three) # read and check against the original deaths_replica <- range_read(ss, col_types = "????DD") identical(deaths, deaths_replica) # clean up gs4_find("sheet-append-demo") %>% googledrive::drive_trash()
Copies a (work)sheet, within its current (spread)Sheet or to another Sheet.
sheet_copy( from_ss, from_sheet = NULL, to_ss = from_ss, to_sheet = NULL, .before = NULL, .after = NULL )
sheet_copy( from_ss, from_sheet = NULL, to_ss = from_ss, to_sheet = NULL, .before = NULL, .after = NULL )
from_ss |
Something that identifies a Google Sheet:
Processed through |
from_sheet |
Sheet to copy, in the sense of "worksheet" or "tab". You can identify a sheet by name, with a string, or by position, with a number. Defaults to the first visible sheet. |
to_ss |
The Sheet to copy to. Accepts all the same types of input as
|
to_sheet |
Optional. Name of the new sheet, as a string. If you don't
specify this, Google generates a name, along the lines of "Copy of blah".
Note that sheet names must be unique within a Sheet, so if the automatic
name would violate this, Google also de-duplicates it for you, meaning you
could conceivably end up with "Copy of blah 2". If you have better ideas
about sheet names, specify |
.before , .after
|
Optional specification of where to put the new sheet. Specify, at most, one of |
The receiving Sheet, to_ ss
, as an instance of sheets_id
.
If the copy happens within one Sheet, makes a DuplicateSheetRequest
:
If the copy is from one Sheet to another, wraps the
spreadsheets.sheets/copyTo
endpoint:
and possibly makes a subsequent UpdateSheetPropertiesRequest
:
Other worksheet functions:
sheet_add()
,
sheet_append()
,
sheet_delete()
,
sheet_properties()
,
sheet_relocate()
,
sheet_rename()
,
sheet_resize()
,
sheet_write()
ss_aaa <- gs4_create( "sheet-copy-demo-aaa", sheets = list(mtcars = head(mtcars), chickwts = head(chickwts)) ) # copy 'mtcars' sheet within existing Sheet, accept autogenerated name ss_aaa %>% sheet_copy() # copy 'mtcars' sheet within existing Sheet # specify new sheet's name and location ss_aaa %>% sheet_copy(to_sheet = "mtcars-the-sequel", .after = 1) # make a second Sheet ss_bbb <- gs4_create("sheet-copy-demo-bbb") # copy 'chickwts' sheet from first Sheet to second # accept auto-generated name and default location ss_aaa %>% sheet_copy("chickwts", to_ss = ss_bbb) # copy 'chickwts' sheet from first Sheet to second, # WITH a specific name and into a specific location ss_aaa %>% sheet_copy( "chickwts", to_ss = ss_bbb, to_sheet = "chicks-two", .before = 1 ) # clean up gs4_find("sheet-copy-demo") %>% googledrive::drive_trash()
ss_aaa <- gs4_create( "sheet-copy-demo-aaa", sheets = list(mtcars = head(mtcars), chickwts = head(chickwts)) ) # copy 'mtcars' sheet within existing Sheet, accept autogenerated name ss_aaa %>% sheet_copy() # copy 'mtcars' sheet within existing Sheet # specify new sheet's name and location ss_aaa %>% sheet_copy(to_sheet = "mtcars-the-sequel", .after = 1) # make a second Sheet ss_bbb <- gs4_create("sheet-copy-demo-bbb") # copy 'chickwts' sheet from first Sheet to second # accept auto-generated name and default location ss_aaa %>% sheet_copy("chickwts", to_ss = ss_bbb) # copy 'chickwts' sheet from first Sheet to second, # WITH a specific name and into a specific location ss_aaa %>% sheet_copy( "chickwts", to_ss = ss_bbb, to_sheet = "chicks-two", .before = 1 ) # clean up gs4_find("sheet-copy-demo") %>% googledrive::drive_trash()
Deletes one or more (work)sheets from a (spread)Sheet.
sheet_delete(ss, sheet)
sheet_delete(ss, sheet)
ss |
Something that identifies a Google Sheet:
Processed through |
sheet |
Sheet to delete, in the sense of "worksheet" or "tab". You can identify a sheet by name, with a string, or by position, with a number. You can pass a vector to delete multiple sheets at once or even a list, if you need to mix names and positions. |
The input ss
, as an instance of sheets_id
Makes an DeleteSheetsRequest
:
Other worksheet functions:
sheet_add()
,
sheet_append()
,
sheet_copy()
,
sheet_properties()
,
sheet_relocate()
,
sheet_rename()
,
sheet_resize()
,
sheet_write()
ss <- gs4_create("delete-sheets-from-me") sheet_add(ss, c("alpha", "beta", "gamma", "delta")) # get an overview of the sheets sheet_properties(ss) # delete sheets sheet_delete(ss, 1) sheet_delete(ss, "gamma") sheet_delete(ss, list("alpha", 2)) # get an overview of the sheets sheet_properties(ss) # clean up gs4_find("delete-sheets-from-me") %>% googledrive::drive_trash()
ss <- gs4_create("delete-sheets-from-me") sheet_add(ss, c("alpha", "beta", "gamma", "delta")) # get an overview of the sheets sheet_properties(ss) # delete sheets sheet_delete(ss, 1) sheet_delete(ss, "gamma") sheet_delete(ss, list("alpha", 2)) # get an overview of the sheets sheet_properties(ss) # clean up gs4_find("delete-sheets-from-me") %>% googledrive::drive_trash()
Reveals full metadata or just the names for the (work)sheets inside a (spread)Sheet.
sheet_properties(ss) sheet_names(ss)
sheet_properties(ss) sheet_names(ss)
ss |
Something that identifies a Google Sheet:
Processed through |
sheet_properties()
: A tibble with one row per (work)sheet.
sheet_names()
: A character vector of (work)sheet names.
Other worksheet functions:
sheet_add()
,
sheet_append()
,
sheet_copy()
,
sheet_delete()
,
sheet_relocate()
,
sheet_rename()
,
sheet_resize()
,
sheet_write()
ss <- gs4_example("gapminder") sheet_properties(ss) sheet_names(ss)
ss <- gs4_example("gapminder") sheet_properties(ss) sheet_names(ss)
Move (work)sheets around within a (spread)Sheet. The outcome is most predictable for these common and simple use cases:
Reorder and move one or more sheets to the front.
Move a single sheet to a specific (but arbitrary) location.
Move multiple sheets to the back with .after = 100
(.after
can be
any number greater than or equal to the number of sheets).
If your relocation task is more complicated and you are puzzled by the
result, break it into a sequence of simpler calls to
sheet_relocate()
.
sheet_relocate(ss, sheet, .before = if (is.null(.after)) 1, .after = NULL)
sheet_relocate(ss, sheet, .before = if (is.null(.after)) 1, .after = NULL)
ss |
Something that identifies a Google Sheet:
Processed through |
sheet |
Sheet to relocate, in the sense of "worksheet" or "tab". You can identify a sheet by name, with a string, or by position, with a number. You can pass a vector to move multiple sheets at once or even a list, if you need to mix names and positions. |
.before , .after
|
Specification of where to locate the sheets(s)
identified by |
The input ss
, as an instance of sheets_id
Constructs a batch of UpdateSheetPropertiesRequest
s (one per sheet):
Other worksheet functions:
sheet_add()
,
sheet_append()
,
sheet_copy()
,
sheet_delete()
,
sheet_properties()
,
sheet_rename()
,
sheet_resize()
,
sheet_write()
sheet_names <- c("alfa", "bravo", "charlie", "delta", "echo", "foxtrot") ss <- gs4_create("sheet-relocate-demo", sheets = sheet_names) sheet_names(ss) # move one sheet, forwards then backwards ss %>% sheet_relocate("echo", .before = "bravo") %>% sheet_names() ss %>% sheet_relocate("echo", .after = "delta") %>% sheet_names() # reorder and move multiple sheets to the front ss %>% sheet_relocate(list("foxtrot", 4)) %>% sheet_names() # put the sheets back in the original order ss %>% sheet_relocate(sheet_names) %>% sheet_names() # reorder and move multiple sheets to the back ss %>% sheet_relocate(c("bravo", "alfa", "echo"), .after = 10) %>% sheet_names() # clean up gs4_find("sheet-relocate-demo") %>% googledrive::drive_trash()
sheet_names <- c("alfa", "bravo", "charlie", "delta", "echo", "foxtrot") ss <- gs4_create("sheet-relocate-demo", sheets = sheet_names) sheet_names(ss) # move one sheet, forwards then backwards ss %>% sheet_relocate("echo", .before = "bravo") %>% sheet_names() ss %>% sheet_relocate("echo", .after = "delta") %>% sheet_names() # reorder and move multiple sheets to the front ss %>% sheet_relocate(list("foxtrot", 4)) %>% sheet_names() # put the sheets back in the original order ss %>% sheet_relocate(sheet_names) %>% sheet_names() # reorder and move multiple sheets to the back ss %>% sheet_relocate(c("bravo", "alfa", "echo"), .after = 10) %>% sheet_names() # clean up gs4_find("sheet-relocate-demo") %>% googledrive::drive_trash()
Changes the name of a (work)sheet.
sheet_rename(ss, sheet = NULL, new_name)
sheet_rename(ss, sheet = NULL, new_name)
ss |
Something that identifies a Google Sheet:
Processed through |
sheet |
Sheet to rename, in the sense of "worksheet" or "tab". You can identify a sheet by name, with a string, or by position, with a number. Defaults to the first visible sheet. |
new_name |
New name of the sheet, as a string. This is required. |
The input ss
, as an instance of sheets_id
Makes an UpdateSheetPropertiesRequest
:
Other worksheet functions:
sheet_add()
,
sheet_append()
,
sheet_copy()
,
sheet_delete()
,
sheet_properties()
,
sheet_relocate()
,
sheet_resize()
,
sheet_write()
ss <- gs4_create( "sheet-rename-demo", sheets = list(cars = head(cars), chickwts = head(chickwts)) ) sheet_names(ss) ss %>% sheet_rename(1, new_name = "automobiles") %>% sheet_rename("chickwts", new_name = "poultry") # clean up gs4_find("sheet-rename-demo") %>% googledrive::drive_trash()
ss <- gs4_create( "sheet-rename-demo", sheets = list(cars = head(cars), chickwts = head(chickwts)) ) sheet_names(ss) ss %>% sheet_rename(1, new_name = "automobiles") %>% sheet_rename("chickwts", new_name = "poultry") # clean up gs4_find("sheet-rename-demo") %>% googledrive::drive_trash()
Changes the number of rows and/or columns in a (work)sheet.
sheet_resize(ss, sheet = NULL, nrow = NULL, ncol = NULL, exact = FALSE)
sheet_resize(ss, sheet = NULL, nrow = NULL, ncol = NULL, exact = FALSE)
ss |
Something that identifies a Google Sheet:
Processed through |
sheet |
Sheet to resize, in the sense of "worksheet" or "tab". You can identify a sheet by name, with a string, or by position, with a number. |
nrow , ncol
|
Desired number of rows or columns, respectively. The default
of |
exact |
Logical, indicating whether to impose |
The input ss
, as an instance of sheets_id
Makes an UpdateSheetPropertiesRequest
:
Other worksheet functions:
sheet_add()
,
sheet_append()
,
sheet_copy()
,
sheet_delete()
,
sheet_properties()
,
sheet_relocate()
,
sheet_rename()
,
sheet_write()
# create a Sheet with the default initial worksheet (ss <- gs4_create("sheet-resize-demo")) # see (work)sheet dims sheet_properties(ss) # no resize occurs sheet_resize(ss, nrow = 2, ncol = 6) # reduce sheet size sheet_resize(ss, nrow = 5, ncol = 7, exact = TRUE) # add rows sheet_resize(ss, nrow = 7) # add columns sheet_resize(ss, ncol = 10) # add rows and columns sheet_resize(ss, nrow = 9, ncol = 12) # re-inspect (work)sheet dims sheet_properties(ss) # clean up gs4_find("sheet-resize-demo") %>% googledrive::drive_trash()
# create a Sheet with the default initial worksheet (ss <- gs4_create("sheet-resize-demo")) # see (work)sheet dims sheet_properties(ss) # no resize occurs sheet_resize(ss, nrow = 2, ncol = 6) # reduce sheet size sheet_resize(ss, nrow = 5, ncol = 7, exact = TRUE) # add rows sheet_resize(ss, nrow = 7) # add columns sheet_resize(ss, ncol = 10) # add rows and columns sheet_resize(ss, nrow = 9, ncol = 12) # re-inspect (work)sheet dims sheet_properties(ss) # clean up gs4_find("sheet-resize-demo") %>% googledrive::drive_trash()
This is one of the main ways to write data with googlesheets4. This function writes a data frame into a (work)sheet inside a (spread)Sheet. The target sheet is styled as a table:
Special formatting is applied to the header row, which holds column names.
The first row (header row) is frozen.
The sheet's dimensions are set to "shrink wrap" the data
.
If no existing Sheet is specified via ss
, this function delegates to
gs4_create()
and the new Sheet's name is randomly generated. If that's
undesirable, call gs4_create()
directly to get more control.
If no sheet
is specified or if sheet
doesn't identify an existing sheet,
a new sheet is added to receive the data
. If sheet
specifies an existing
sheet, it is effectively overwritten! All pre-existing values, formats, and
dimensions are cleared and the targeted sheet gets new values and dimensions
from data
.
This function goes by two names, because we want it to make sense in two contexts:
write_sheet()
evokes other table-writing functions, like
readr::write_csv()
. The sheet
here technically refers to an individual
(work)sheet (but also sort of refers to the associated Google
(spread)Sheet).
sheet_write()
is the right name according to the naming convention used
throughout the googlesheets4 package.
write_sheet()
and sheet_write()
are equivalent and you can use either one.
sheet_write(data, ss = NULL, sheet = NULL) write_sheet(data, ss = NULL, sheet = NULL)
sheet_write(data, ss = NULL, sheet = NULL) write_sheet(data, ss = NULL, sheet = NULL)
data |
A data frame. If it has zero rows, we send one empty pseudo-row
of data, so that we can apply the usual table styling. This empty row goes
away (gets filled, actually) the first time you send more data with
|
ss |
Something that identifies a Google Sheet:
Processed through |
sheet |
Sheet to write into, in the sense of "worksheet" or "tab". You can identify a sheet by name, with a string, or by position, with a number. |
The input ss
, as an instance of sheets_id
Other write functions:
gs4_create()
,
gs4_formula()
,
range_delete()
,
range_flood()
,
range_write()
,
sheet_append()
Other worksheet functions:
sheet_add()
,
sheet_append()
,
sheet_copy()
,
sheet_delete()
,
sheet_properties()
,
sheet_relocate()
,
sheet_rename()
,
sheet_resize()
df <- data.frame( x = 1:3, y = letters[1:3] ) # specify only a data frame, get a new Sheet, with a random name ss <- write_sheet(df) read_sheet(ss) # clean up googledrive::drive_trash(ss) # create a Sheet with some initial, placeholder data ss <- gs4_create( "sheet-write-demo", sheets = list(alpha = data.frame(x = 1), omega = data.frame(x = 1)) ) # write df into its own, new sheet sheet_write(df, ss = ss) # write mtcars into the sheet named "omega" sheet_write(mtcars, ss = ss, sheet = "omega") # get an overview of the sheets sheet_properties(ss) # view your magnificent creation in the browser gs4_browse(ss) # clean up gs4_find("sheet-write-demo") %>% googledrive::drive_trash()
df <- data.frame( x = 1:3, y = letters[1:3] ) # specify only a data frame, get a new Sheet, with a random name ss <- write_sheet(df) read_sheet(ss) # clean up googledrive::drive_trash(ss) # create a Sheet with some initial, placeholder data ss <- gs4_create( "sheet-write-demo", sheets = list(alpha = data.frame(x = 1), omega = data.frame(x = 1)) ) # write df into its own, new sheet sheet_write(df, ss = ss) # write mtcars into the sheet named "omega" sheet_write(mtcars, ss = ss, sheet = "omega") # get an overview of the sheets sheet_properties(ss) # view your magnificent creation in the browser gs4_browse(ss) # clean up gs4_find("sheet-write-demo") %>% googledrive::drive_trash()
sheets_id
classsheets_id
is an S3 class that marks a string as a Google Sheet's id, which
the Sheets API docs refer to as spreadsheetId
.
Any object of class sheets_id
also has the drive_id
class, which is used by googledrive for the same purpose. This means you
can provide a sheets_id
to googledrive functions, in order to do anything
with your Sheet that has nothing to do with it being a spreadsheet. Examples:
change the Sheet's name, parent folder, or permissions. Read more about using
googlesheets4 and googledrive together in vignette("drive-and-sheets")
.
Note that a sheets_id
object is intended to hold just one id, while the
parent class drive_id
can be used for multiple ids.
as_sheets_id()
is a generic function that converts various inputs into an
instance of sheets_id
. See more below.
When you print a sheets_id
, we attempt to reveal the Sheet's current
metadata, via gs4_get()
. This can fail for a variety of reasons (e.g. if
you're offline), but the input sheets_id
is always revealed and returned,
invisibly.
as_sheets_id(x, ...)
as_sheets_id(x, ...)
x |
Something that contains a Google Sheet id: an id string, a
|
... |
Other arguments passed down to methods. (Not used.) |
as_sheets_id()
These inputs can be converted to a sheets_id
:
Spreadsheet id, "a string containing letters, numbers, and some special
characters", typically 44 characters long, in our experience. Example:
1qpyC0XzvTcKT6EISywvqESX3A0MwQoFDE8p-Bll4hps
.
A URL, from which we can excavate a spreadsheet or file id. Example:
"https://docs.google.com/spreadsheets/d/1BzfL0kZUz1TsI5zxJF1WNF01IxvC67FbOJUiiGMZ_mQ/edit#gid=1150108545"
.
A one-row dribble
, a "Drive tibble" used by the
googledrive package. In general, a dribble
can represent several
files, one row per file. Since googlesheets4 is not vectorized over
spreadsheets, we are only prepared to accept a one-row dribble
.
googledrive::drive_get("YOUR_SHEET_NAME")
is a great way to look up a Sheet via its name.
gs4_find("YOUR_SHEET_NAME")
is another good way
to get your hands on a Sheet.
Spreadsheet meta data, as returned by, e.g., gs4_get()
. Literally,
this is an object of class googlesheets4_spreadsheet
.
mini_gap_id <- gs4_example("mini-gap") class(mini_gap_id) mini_gap_id as_sheets_id("abc")
mini_gap_id <- gs4_example("mini-gap") class(mini_gap_id) mini_gap_id as_sheets_id("abc")
Reshapes a data frame of cells (presumably the output of
range_read_cells()
) into another data frame, i.e., puts it back into the
shape of the source spreadsheet. This function exists primarily for internal
use and for testing. The flagship function range_read()
, a.k.a.
read_sheet()
, is what most users are looking for. It is basically
range_read_cells()
+ spread_sheet()
.
spread_sheet( df, col_names = TRUE, col_types = NULL, na = "", trim_ws = TRUE, guess_max = min(1000, max(df$row)), .name_repair = "unique" )
spread_sheet( df, col_names = TRUE, col_types = NULL, na = "", trim_ws = TRUE, guess_max = min(1000, max(df$row)), .name_repair = "unique" )
df |
A data frame with one row per (nonempty) cell, integer variables
|
col_names |
|
col_types |
Column types. Either |
na |
Character vector of strings to interpret as missing values. By default, blank cells are treated as missing data. |
trim_ws |
Logical. Should leading and trailing whitespace be trimmed from cell contents? |
guess_max |
Maximum number of data rows to use for guessing column types. |
.name_repair |
Handling of column names. By default, googlesheets4
ensures column names are not empty and are unique. There is full support
for |
A tibble in the shape of the original spreadsheet, but enforcing
user's wishes regarding column names, column types, NA
strings, and
whitespace trimming.
df <- gs4_example("mini-gap") %>% range_read_cells() spread_sheet(df) # ^^ gets same result as ... read_sheet(gs4_example("mini-gap"))
df <- gs4_example("mini-gap") %>% range_read_cells() spread_sheet(df) # ^^ gets same result as ... read_sheet(gs4_example("mini-gap"))