tibble() constructs a data frame. It is used like base::data.frame(), butwith a couple notable differences:
The returned data frame has the class
tbl_df, inaddition todata.frame. This allows so-called "tibbles" to exhibit somespecial behaviour, such as enhanced printing. Tibbles arefully described intbl_df.tibble()is much lazier thanbase::data.frame()in terms oftransforming the user's input.Character vectors are not coerced to factor.
List-columns are expressly anticipated and do not require special tricks.
Column names are not modified.
Inner names in columns are left unchanged.
tibble()builds columns sequentially. When defining a column, you canrefer to columns created earlier in the call. Only columns of length oneare recycled.If a column evaluates to a data frame or tibble, it is nested or spliced.If it evaluates to a matrix or a array, it remains a matrix or array,respectively.See examples.
tibble_row() constructs a data frame that is guaranteed to occupy one row.Vector columns are required to have size one, non-vector columns are wrappedin a list.
Usage
Arguments
- ...
<
dynamic-dots>A set of name-value pairs. These arguments areprocessed withrlang::quos()and support unquote via!!andunquote-splice via!!!. Use:=to create columns that start with a dot.Arguments are evaluated sequentially.You can refer to previously created elements directly or using the .datapronoun.To refer explicitly to objects in the calling environment, use
!!or.env, e.g.!!.dataor.env$.datafor the special case of an objectnamed.data.- .rows
The number of rows, useful to create a 0-column tibble orjust as an additional check.
- .name_repair
Treatment of problematic column names:
"minimal": No name repair or checks, beyond basic existence,"unique": Make sure names are unique and not empty,"check_unique": (default value), no name repair, but check they areunique,"universal": Make the namesuniqueand syntactica function: apply custom name repair (e.g.,
.name_repair = make.namesfor names in the style of base R).A purrr-style anonymous function, see
rlang::as_function()
This argument is passed on as
repairtovctrs::vec_as_names().See there for more details on these terms and the strategies usedto enforce them.
Value
A tibble, which is a colloquial term for an object of classtbl_df. A tbl_df object is also a dataframe, i.e. it has class data.frame.
See also
Use as_tibble() to turn an existing object into a tibble. Useenframe() to convert a named vector into a tibble. Name repair isdetailed in vctrs::vec_as_names().See quasiquotation for more details on tidy dots semantics,i.e. exactly how the ... argument is processed.
Examples
# Unnamed arguments are named with their expression:a <- 1:5tibble(a, a * 2)#> # A tibble: 5 × 2#> a `a * 2`#> <int> <dbl>#> 1 1 2#> 2 2 4#> 3 3 6#> 4 4 8#> 5 5 10# Scalars (vectors of length one) are recycled:tibble(a, b = a * 2, c = 1)#> # A tibble: 5 × 3#> a b c#> <int> <dbl> <dbl>#> 1 1 2 1#> 2 2 4 1#> 3 3 6 1#> 4 4 8 1#> 5 5 10 1# Columns are available in subsequent expressions:tibble(x = runif(10), y = x * 2)#> # A tibble: 10 × 2#> x y#> <dbl> <dbl>#> 1 0.900 1.80 #> 2 0.617 1.23 #> 3 0.704 1.41 #> 4 0.546 1.09 #> 5 0.807 1.61 #> 6 0.184 0.368#> 7 0.725 1.45 #> 8 0.623 1.25 #> 9 0.0574 0.115#> 10 0.636 1.27 # tibble() never coerces its inputs,str(tibble(letters))#> tibble [26 × 1] (S3: tbl_df/tbl/data.frame)#> $ letters: chr [1:26] "a" "b" "c" "d" ...str(tibble(x = list(diag(1), diag(2))))#> tibble [2 × 1] (S3: tbl_df/tbl/data.frame)#> $ x:List of 2#> ..$ : num [1, 1] 1#> ..$ : num [1:2, 1:2] 1 0 0 1# or munges column names (unless requested),tibble(`a + b` = 1:5)#> # A tibble: 5 × 1#> `a + b`#> <int>#> 1 1#> 2 2#> 3 3#> 4 4#> 5 5# but it forces you to take charge of names, if they need repair:try(tibble(x = 1, x = 2))#> Error in tibble(x = 1, x = 2) : #> Column name `x` must not be duplicated.#> Use `.name_repair` to specify repair.#> Caused by error in `repaired_names()` at tibble/R/names.R:14:2:#> ! Names must be unique.#> ✖ These names are duplicated:#> * "x" at locations 1 and 2.tibble(x = 1, x = 2, .name_repair = "unique")#> New names:#> • `x` -> `x...1`#> • `x` -> `x...2`#> # A tibble: 1 × 2#> x...1 x...2#> <dbl> <dbl>#> 1 1 2tibble(x = 1, x = 2, .name_repair = "minimal")#> # A tibble: 1 × 2#> x x#> <dbl> <dbl>#> 1 1 2## By default, non-syntactic names are allowed,df <- tibble(`a 1` = 1, `a 2` = 2)## because you can still index by name:df[["a 1"]]#> [1] 1df$`a 1`#> [1] 1with(df, `a 1`)#> [1] 1## Syntactic names are easier to work with, though, and you can request them:df <- tibble(`a 1` = 1, `a 2` = 2, .name_repair = "universal")#> New names:#> • `a 1` -> `a.1`#> • `a 2` -> `a.2`df$a.1#> [1] 1## You can specify your own name repair function:tibble(x = 1, x = 2, .name_repair = make.unique)#> # A tibble: 1 × 2#> x x.1#> <dbl> <dbl>#> 1 1 2fix_names <- function(x) gsub("\\s+", "_", x)tibble(`year 1` = 1, `year 2` = 2, .name_repair = fix_names)#> # A tibble: 1 × 2#> year_1 year_2#> <dbl> <dbl>#> 1 1 2## purrr-style anonymous functions and constants## are also supportedtibble(x = 1, x = 2, .name_repair = ~ make.names(., unique = TRUE))#> # A tibble: 1 × 2#> x x.1#> <dbl> <dbl>#> 1 1 2tibble(x = 1, x = 2, .name_repair = ~ c("a", "b"))#> # A tibble: 1 × 2#> a b#> <dbl> <dbl>#> 1 1 2# Tibbles can contain columns that are tibbles or matrices# if the number of rows is compatible. Unnamed tibbled are# spliced, i.e. the inner columns are inserted into the# tibble under construction.tibble( a = 1:3, tibble( b = 4:6, c = 7:9 ), d = tibble( e = tibble( f = b ) ))#> # A tibble: 3 × 4#> a b c d$e$f#> <int> <int> <int> <int>#> 1 1 4 7 4#> 2 2 5 8 5#> 3 3 6 9 6tibble( a = 1:3, b = diag(3), c = cor(trees), d = Titanic[1:3, , , ])#> # A tibble: 3 × 4#> a b[,1] [,2] [,3] c[,"Girth"] [,"Height"] [,"Volume"] d#> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <table[,2,2>#> 1 1 1 0 0 1 0.519 0.967 0 …#> 2 2 0 1 0 0.519 1 0.598 0 …#> 3 3 0 0 1 0.967 0.598 1 35 …# Data can not contain tibbles or matrices with incompatible number of rows:try(tibble(a = 1:3, b = tibble(c = 4:7)))#> Error in tibble(a = 1:3, b = tibble(c = 4:7)) : #> Tibble columns must have compatible sizes.#> • Size 3: Existing data.#> • Size 4: Column `b`.#> ℹ Only values of size one are recycled.# Use := to create columns with names that start with a dot:tibble(.dotted := 3)#> # A tibble: 1 × 1#> .dotted#> <dbl>#> 1 3# This also works, but might break in the future:tibble(.dotted = 3)#> # A tibble: 1 × 1#> .dotted#> <dbl>#> 1 3# You can unquote an expression:x <- 3tibble(x = 1, y = x)#> # A tibble: 1 × 2#> x y#> <dbl> <dbl>#> 1 1 1tibble(x = 1, y = !!x)#> # A tibble: 1 × 2#> x y#> <dbl> <dbl>#> 1 1 3# You can splice-unquote a list of quosures and expressions:tibble(!!!list(x = rlang::quo(1:10), y = quote(x * 2)))#> # A tibble: 10 × 2#> x y#> <int> <dbl>#> 1 1 2#> 2 2 4#> 3 3 6#> 4 4 8#> 5 5 10#> 6 6 12#> 7 7 14#> 8 8 16#> 9 9 18#> 10 10 20# Use .data, .env and !! to refer explicitly to columns or outside objectsa <- 1tibble(a = 2, b = a)#> # A tibble: 1 × 2#> a b#> <dbl> <dbl>#> 1 2 2tibble(a = 2, b = .data$a)#> # A tibble: 1 × 2#> a b#> <dbl> <dbl>#> 1 2 2tibble(a = 2, b = .env$a)#> # A tibble: 1 × 2#> a b#> <dbl> <dbl>#> 1 2 1tibble(a = 2, b = !!a)#> # A tibble: 1 × 2#> a b#> <dbl> <dbl>#> 1 2 1try(tibble(a = 2, b = .env$bogus))#> Error in eval_bare(sym(nm), x) : object 'bogus' not foundtry(tibble(a = 2, b = !!bogus))#> Error in quos(...) : object 'bogus' not found# Use tibble_row() to construct a one-row tibble:tibble_row(a = 1, lm = lm(Height ~ Girth + Volume, data = trees))#> # A tibble: 1 × 2#> a lm #> <dbl> <list>#> 1 1 <lm>