wrapr
supplies a few tools for creating example data.frame
s. An important use case is: building the control table for cdata::rowrecs_to_blocks()
and cdata::blocks_to_rowrecs()
(example here).
Lets see how to create an example data frame. The idea is similar to that found in tibble::tribble()
: for small tables a row oriented constructor can be quite legible, and avoids the cognitive load of taking a transpose.
For example we can create a typical data.frame
as follows:
d <- data.frame(
names = c("a", "b", "c", "d"),
x = c(1, 2, 3, 4 ),
y = c(1, 4, 9, 16 ),
stringsAsFactors = FALSE)
print(d)
## names x y
## 1 a 1 1
## 2 b 2 4
## 3 c 3 9
## 4 d 4 16
Notice how the table is specified by columns (which is close to how data.frame
s are implemented), but printed by rows. utils::str()
and tibble::glimpse()
both print by columns.
str(d)
## 'data.frame': 4 obs. of 3 variables:
## $ names: chr "a" "b" "c" "d"
## $ x : num 1 2 3 4
## $ y : num 1 4 9 16
wrapr
supplies the method draw_frame
which at first glance appears to be a mere pretty-printer:
cat(draw_frame(d))
d <- wrapr::build_frame(
"names" , "x", "y" |
"a" , 1 , 1 |
"b" , 2 , 4 |
"c" , 3 , 9 |
"d" , 4 , 16 )
However, the above rendering is actually executable R
code. If we run it, we re-create the original data.frame()
.
d2 <- build_frame(
"names", "x", "y" |
"a" , 1 , 1 |
"b" , 2 , 4 |
"c" , 3 , 9 |
"d" , 4 , 16 )
print(d2)
## names x y
## 1 a 1 1
## 2 b 2 4
## 3 c 3 9
## 4 d 4 16
The merit is: the above input is how it looks when printed.
The technique is intended for typing small examples (or cdata
control tables) and only builds data.frame
s with atomic types (characters, numerics, and logicals; no times, factors or list columns). The specification rule is the first appearance of an infix 2-argument function call (in this case the infix “or symbol” “|
”) is taken to mean the earlier arguments are part of the header or column names and later arguments are values. The other appearances of “/
” are ignored. This means we could also write the frame as follows:
build_frame(
"names", "x", "y" |
"a" , 1 , 1 ,
"b" , 2 , 4 ,
"c" , 3 , 9 ,
"d" , 4 , 16 )
## names x y
## 1 a 1 1
## 2 b 2 4
## 3 c 3 9
## 4 d 4 16
This is more limited than base::dump()
, but also more legible.
d <-
structure(list(names = c("a", "b", "c", "d"), x = c(1, 2, 3,
4), y = c(1, 4, 9, 16)), class = "data.frame", row.names = c(NA,
-4L))
d
One can use the combination of build_frame()
and draw_frame()
to neaten up by-hand examples for later use (via copy and paste):
cat(draw_frame(build_frame(
"names", "x", "y" |
"a", 1, 1,
"b", 2, 4,
"c", 3, 9,
"d", 4, 16)))
wrapr::build_frame(
"names" , "x", "y" |
"a" , 1 , 1 |
"b" , 2 , 4 |
"c" , 3 , 9 |
"d" , 4 , 16 )
build_frame()
allows for simple substitutions of values. In contrast the method qchar_frame()
builds data.frame
s containing only character
types and doesn’t require quoting (though it does allow it).
qchar_frame(
col_1, col_2, col_3 |
a , b , c |
d , e , "f g" )
## col_1 col_2 col_3
## 1 a b c
## 2 d e f g
build_frame()
is intended to capture typed-in examples, and is only compatible with very limited in-place calculation and substitution, and that must be in parenthesis:
build_frame(
"names", "x" , "y" |
"a" , 1 , 1 |
"b" , cos(2) , 4 |
"c" , (3+2) , 9 |
"d" , 4 , 16 )
## names x y
## 1 a 1.0000000 1
## 2 b -0.4161468 4
## 3 c 5.0000000 9
## 4 d 4.0000000 16
Expressions not in parenthesis (such as “3 + 2
”) will confuse the language transform build_frame()
uses to detect cell boundaries.