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A ‘dibble’ (derived from ‘dimensional tibble’) is a data frame consisting of arrays with dimension names, known as data cubes. The columns of the dibbles are classified into dimensions or measures, and the operations on the measures are broadcasted by dimension names.
# the released version from CRAN:
install.packages("dibble")
# the development version from GitHub:
# install.packages("devtools")
devtools::install_github("UchidaMizuki/dibble")library(dibble)
library(dplyr)
library(tidyr)arr1 <- array(1:6, c(2, 3),
list(axis1 = letters[1:2],
axis2 = letters[1:3]))
arr2 <- array(1:2, 2,
list(axis2 = letters[1:2]))
try(arr1 * arr2)
#> Error in arr1 * arr2 : non-conformable arrays
ddf1 <- as_dibble(arr1)
ddf2 <- as_dibble(arr2)
ddf1 * ddf2
#> Warning: Broadcasting,
#> New axes, dim_names = c("axis1", "axis2")
#> New coordinates,
#> $ axis2: chr "c"
#> # A dibble: 6
#> # Dimensions: axis1 [2], axis2 [3]
#> axis1 axis2 .
#> <chr> <chr> <int>
#> 1 a a 1
#> 2 a b 6
#> 3 a c NA
#> 4 b a 2
#> 5 b b 8
#> 6 b c NA# You can use broadcast() to suppress the warnings.
broadcast(ddf1 * ddf2,
dim_names = c("axis1", "axis2"))
#> # A dibble: 6
#> # Dimensions: axis1 [2], axis2 [3]
#> axis1 axis2 .
#> <chr> <chr> <int>
#> 1 a a 1
#> 2 a b 6
#> 3 a c NA
#> 4 b a 2
#> 5 b b 8
#> 6 b c NAdibble provides some dplyr methods as follows,
as_tibble(): From tibble packagefilter()mutate(): Experimentalrename()select() and relocate()slice(): Specify locations (a integer vector) for each
dimensiondf <- expand_grid(axis1 = letters[1:2],
axis2 = letters[1:2]) |>
mutate(value1 = row_number(),
value2 = value1 * 2)
ddf <- df |>
dibble_by(axis1, axis2)
ddf
#> # A dibble: 4 x 2
#> # Dimensions: axis1 [2], axis2 [2]
#> # Measures: value1, value2
#> axis1 axis2 value1 value2
#> <chr> <chr> <int> <dbl>
#> 1 a a 1 2
#> 2 a b 2 4
#> 3 b a 3 6
#> 4 b b 4 8# You can access the measures from the dibble with `$`.
ddf$value1
#> # A dibble: 4
#> # Dimensions: axis1 [2], axis2 [2]
#> axis1 axis2 .
#> <chr> <chr> <int>
#> 1 a a 1
#> 2 a b 2
#> 3 b a 3
#> 4 b b 4
df <- expand_grid(tibble(axis1_key = letters[1:2],
axis1_value = 1:2),
tibble(axis2_key = letters[1:2],
axis2_value = 1:2)) |>
mutate(value1 = row_number(),
value2 = value1 * 2)
# You can `pack` several columns into one dimension (See `tidyr::pack()`).
df |>
dibble_by(axis1 = c("axis1_key", "axis1_value"),
axis2 = c("axis2_key", "axis2_value"),
.names_sep = "_")
#> # A dibble: 4 x 2
#> # Dimensions: axis1 [2], axis2 [2]
#> # Measures: value1, value2
#> axis1$key $value axis2$key $value value1 value2
#> <chr> <int> <chr> <int> <int> <dbl>
#> 1 a 1 a 1 1 2
#> 2 a 1 b 2 2 4
#> 3 b 2 a 1 3 6
#> 4 b 2 b 2 4 8dibble provides some dplyr methods as follows,
# from an array with dimension names
arr <- array(1:4, c(2, 2),
list(axis1 = letters[1:2],
axis2 = letters[1:2]))
ddf1 <- as_dibble(arr)
# from a vector
ddf2 <- broadcast(1:4,
list(axis1 = letters[1:2],
axis2 = letters[1:2]))
arr
#> axis2
#> axis1 a b
#> a 1 3
#> b 2 4ddf1
#> # A dibble: 4
#> # Dimensions: axis1 [2], axis2 [2]
#> axis1 axis2 .
#> <chr> <chr> <int>
#> 1 a a 1
#> 2 a b 3
#> 3 b a 2
#> 4 b b 4ddf2
#> # A dibble: 4
#> # Dimensions: axis1 [2], axis2 [2]
#> axis1 axis2 .
#> <chr> <chr> <int>
#> 1 a a 1
#> 2 a b 3
#> 3 b a 2
#> 4 b b 4These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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