# format_glimpse() output test

``````Code
# # Atomic numbers
format_glimpse(1)
Output
[1] "1"
Code
format_glimpse(1:3)
Output
[1] "1" "2" "3"
Code
format_glimpse(NA)
Output
[1] "NA"
Code
format_glimpse(TRUE)
Output
[1] "TRUE"
Code
format_glimpse(logical())
Output
character(0)
Code
# # Strings
format_glimpse("1")
Output
[1] "\"1\""
Code
format_glimpse(letters)
Output
[1] "\"a\"" "\"b\"" "\"c\"" "\"d\"" "\"e\"" "\"f\"" "\"g\"" "\"h\"" "\"i\""
[10] "\"j\"" "\"k\"" "\"l\"" "\"m\"" "\"n\"" "\"o\"" "\"p\"" "\"q\"" "\"r\""
[19] "\"s\"" "\"t\"" "\"u\"" "\"v\"" "\"w\"" "\"x\"" "\"y\"" "\"z\""
Code
format_glimpse(NA_character_)
Output
[1] "NA"
Code
format_glimpse(character())
Output
character(0)
Code
# # Factors
format_glimpse(factor(c("1", "a")))
Output
[1] "1" "a"
Code
format_glimpse(factor(c("foo", "\"bar\"")))
Output
[1] "foo"     "\"bar\""
Code
format_glimpse(factor())
Output
character(0)
Code
# Add quotes around factor levels with comma
# so they don't appear as if they were two observations (#384)
format_glimpse(factor(c("foo, bar", "foo", "\"bar\"")))
Output
[1] "\"foo, bar\""    "\"foo\""         "\"\\\"bar\\\"\""
Code
# # Lists
format_glimpse(list(1:3))
Output
[1] "<1, 2, 3>"
Code
format_glimpse(as.list(1:3))
Output
[1] "1" "2" "3"
Code
format_glimpse(list(1:3, 4))
Output
[1] "<1, 2, 3>" "4"
Code
format_glimpse(list(1:3, 4:5))
Output
[1] "<1, 2, 3>" "<4, 5>"
Code
format_glimpse(list())
Output
[1] "list()"
Code
format_glimpse(list(list()))
Output
[1] "[]"
Code
format_glimpse(list(character()))
Output
[1] "<>"
Code
format_glimpse(list(1:3, list(4)))
Output
[1] "<1, 2, 3>" "[4]"
Code
format_glimpse(list(1:3, list(4:5)))
Output
[1] "<1, 2, 3>" "[<4, 5>]"
``````

# output test for glimpse()

``````Code
glimpse(as_tbl(mtcars), width = 70L)
Output
Rows: 32
Columns: 11
\$ mpg  <dbl> 21.0, 21.0, 22.8, 21.4, 18.7, 18.1, 14.3, 24.4, 22.8, 1~
\$ cyl  <dbl> 6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8, 8, 8, 8, 8, 8, 4, 4~
\$ disp <dbl> 160.0, 160.0, 108.0, 258.0, 360.0, 225.0, 360.0, 146.7,~
\$ hp   <dbl> 110, 110, 93, 110, 175, 105, 245, 62, 95, 123, 123, 180~
\$ drat <dbl> 3.90, 3.90, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3~
\$ wt   <dbl> 2.620, 2.875, 2.320, 3.215, 3.440, 3.460, 3.570, 3.190,~
\$ qsec <dbl> 16.46, 17.02, 18.61, 19.44, 17.02, 20.22, 15.84, 20.00,~
\$ vs   <dbl> 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1~
\$ am   <dbl> 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1~
\$ gear <dbl> 4, 4, 4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4~
\$ carb <dbl> 4, 4, 1, 1, 2, 1, 4, 2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2~
Code
glimpse(as_tbl(iris), width = 70L)
Output
Rows: 150
Columns: 5
\$ Sepal.Length <dbl> 5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4.~
\$ Sepal.Width  <dbl> 3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.~
\$ Petal.Length <dbl> 1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.~
\$ Petal.Width  <dbl> 0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.~
\$ Species      <fct> setosa, setosa, setosa, setosa, setosa, setosa,~
Code
# No columns
glimpse(as_tbl(iris[integer()]), width = 70L)
Output
Rows: 150
Columns: 0
Code
# Non-syntactic names
df <- tibble::tibble(`mean(x)` = 5, `var(x)` = 3)
glimpse(df, width = 28)
Output
Rows: 1
Columns: 2
\$ `mean(x)` <dbl> 5
\$ `var(x)`  <dbl> 3
Code
glimpse(as_tbl(df_all), width = 70L)
Output
Rows: 3
Columns: 9
\$ a <dbl> 1.0, 2.5, NA
\$ b <int> 1, 2, NA
\$ c <lgl> TRUE, FALSE, NA
\$ d <chr> "a", "b", NA
\$ e <fct> a, b, NA
\$ f <date> 2015-12-10, 2015-12-11, NA
\$ g <dttm> 2015-12-09 10:51:35, 2015-12-09 10:51:36, NA
\$ h <list> 1, 2, NA
\$ i <list> [1, <2, 3>], [<4, 5, 6>], [NA]
Code
# options(tibble.width = 50)
withr::with_options(list(tibble.width = 50), glimpse(as_tbl(df_all)))
Output
Rows: 3
Columns: 9
\$ a <dbl> 1.0, 2.5, NA
\$ b <int> 1, 2, NA
\$ c <lgl> TRUE, FALSE, NA
\$ d <chr> "a", "b", NA
\$ e <fct> a, b, NA
\$ f <date> 2015-12-10, 2015-12-11, NA
\$ g <dttm> 2015-12-09 10:51:35, 2015-12-09 10:51:~
\$ h <list> 1, 2, NA
\$ i <list> [1, <2, 3>], [<4, 5, 6>], [NA]
Code
# options(tibble.width = 35)
withr::with_options(list(tibble.width = 35), glimpse(as_tbl(df_all)))
Output
Rows: 3
Columns: 9
\$ a <dbl> 1.0, 2.5, NA
\$ b <int> 1, 2, NA
\$ c <lgl> TRUE, FALSE, NA
\$ d <chr> "a", "b", NA
\$ e <fct> a, b, NA
\$ f <date> 2015-12-10, 2015-12-11,~
\$ g <dttm> 2015-12-09 10:51:35, 20~
\$ h <list> 1, 2, NA
\$ i <list> [1, <2, 3>], [<4, 5, 6>~
Code
# non-tibble
glimpse(5)
Output
num 5
Code
iris2 <- as_unknown_rows(iris)
glimpse(iris2, width = 70L)
Output
Rows: ??
Columns: 5
\$ Sepal.Length <dbl> 5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4.~
\$ Sepal.Width  <dbl> 3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.~
\$ Petal.Length <dbl> 1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.~
\$ Petal.Width  <dbl> 0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.~
\$ Species      <fct> setosa, setosa, setosa, setosa, setosa, setosa,~
Code
species <- unique(iris\$Species)
data <- unname(split(iris, iris\$Species))
nested_iris_df <- tibble::tibble(species, data)
glimpse(nested_iris_df, width = 70L)
Output
Rows: 3
Columns: 2
\$ species <fct> setosa, versicolor, virginica
\$ data    <list> [<data.frame[50 x 5]>], [<data.frame[50 x 5]>], [<da~
Code
data <- map(data, as_tbl)
nested_iris_tbl <- tibble::tibble(species, data)
glimpse(nested_iris_tbl, width = 70L)
Output
Rows: 3
Columns: 2
\$ species <fct> setosa, versicolor, virginica
\$ data    <list> [<tbl[50 x 5]>], [<tbl[50 x 5]>], [<tbl[50 x 5]>]
``````

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pillar documentation built on July 29, 2021, 9:06 a.m.