Nothing
format_fixed
worksCode
x = c(1, 1.2, 12.78749, pi, 1.2e-07)
format_fixed(x, digits = 3)
Output
[1] "1.000e+00" "1.200e+00" "1.279e+01" "3.142e+00" "1.200e-07"
Code
format_fixed(x, digits = 3, zero_digits = 2)
Output
[1] "1.000e+00" "1.200e+00" "1.279e+01" "3.142e+00" "1.200e-07"
Code
format_fixed(x, digits = 3, zero_digits = NULL)
Output
[1] "1.000e+00" "1.200e+00" "1.279e+01" "3.142e+00" "1.200e-07"
Code
x_sd = sd(iris$Sepal.Length / 10000, na.rm = TRUE)
format_fixed(x_sd, dig = 6)
Output
[1] "8.280661e-05"
Code
format_fixed(x_sd, dig = 3, zero_digits = 2)
Output
[1] "8.281e-05"
Code
format_fixed(x_sd, dig = 3, zero_digits = 2, only_round = TRUE)
Output
[1] "8.281e-05"
Code
options(crosstable_only_round = TRUE)
format_fixed(x_sd, dig = 3, zero_digits = 2)
Output
[1] "8.281e-05"
Code
options(crosstable_only_round = NULL)
x2 = c(0.01, 0.1001, 0.500005, 1.2e-07)
format_fixed(x2, scientific = 0, dig = 1)
Output
[1] "1.0e-02" "1.0e-01" "5.0e-01" "1.2e-07"
Code
format_fixed(x2, scientific = FALSE, dig = 6)
Output
[1] "0.010000" "0.100100" "0.500005" "1e-07"
Code
format_fixed(x2, scientific = FALSE, dig = 6, zero_digits = NA)
Output
[1] "0.010000" "0.100100" "0.500005" "0.000000"
Code
format_fixed(x2, scientific = FALSE, dig = 7)
Output
[1] "0.0100000" "0.1001000" "0.5000050" "0.0000001"
Code
format_fixed(x2, scientific = FALSE, percent = TRUE, dig = 0)
Output
[1] "1%" "10%" "50%" "1e-05%"
Code
format_fixed(x2, scientific = FALSE, eps = 0.05)
Output
[1] "<0.05" "0.1" "0.5" "<0.05"
Code
x_date = as.Date("1960-01-01") + c(0, 32, 400)
format_fixed(x_date)
Output
[1] "1960-01-01" "1960-02-02" "1961-02-04"
Code
format_fixed(x_date, date_format = "%Y/%m/%d")
Output
[1] "1960/01/01" "1960/02/02" "1961/02/04"
Code
x_posix = as.POSIXct("1960-01-01 00:00:01") + c(1, 5, 10) * 1e+06
format_fixed(x_posix)
Output
[1] "1960-01-12 13:46:41" "1960-02-27 20:53:21" "1960-04-25 17:46:41"
Code
format_fixed(x_posix, date_format = "%Y/%m/%d")
Output
[1] "1960/01/12" "1960/02/27" "1960/04/25"
Code
withr::with_package("lubridate", format_fixed(lubridate::days(1:5)))
Output
[1] "1d 0H 0M 0S" "2d 0H 0M 0S" "3d 0H 0M 0S" "4d 0H 0M 0S" "5d 0H 0M 0S"
Code
withr::with_package("lubridate", format_fixed(lubridate::weeks(1:5)))
Output
[1] "7d 0H 0M 0S" "14d 0H 0M 0S" "21d 0H 0M 0S" "28d 0H 0M 0S" "35d 0H 0M 0S"
Code
x
Output
.id label variable straight vshaped
1 disp Displacement (cu.in.) meansd 111.856 (58.044) 302.193 (115.524)
2 disp Displacement (cu.in.) quantile 25% 78.700 217.900
3 disp Displacement (cu.in.) quantile 75% 120.100 375.500
4 hp Gross horsepower meansd 85.667 (23.452) 187.667 (64.556)
5 hp Gross horsepower quantile 25% 66.000 150.000
6 hp Gross horsepower quantile 75% 109.000 222.500
7 am Transmission auto 2 (18.18%) 9 (81.82%)
8 am Transmission manual 7 (53.85%) 6 (46.15%)
9 am Transmission NA 0 0
10 am Transmission Total 9 (37.50%) 15 (62.50%)
NA Total
1 230.438 (91.499) 230.722 (123.939)
2 162.375 120.825
3 296.850 326.000
4 138.500 (58.241) 146.688 (68.563)
5 102.500 96.500
6 176.250 180.000
7 8 19 (59.38%)
8 0 13 (40.62%)
9 0 0
10 8 32 (100.00%)
Code
ft
Output
a flextable object.
col_keys: `label`, `variable`, `straight`, `vshaped`, `NA`, `Total`
header has 2 row(s)
body has 10 row(s)
original dataset sample:
.id label variable straight vshaped
1 disp Displacement (cu.in.) meansd 111.856 (58.044) 302.193 (115.524)
2 disp Displacement (cu.in.) quantile 25% 78.700 217.900
3 disp Displacement (cu.in.) quantile 75% 120.100 375.500
4 hp Gross horsepower meansd 85.667 (23.452) 187.667 (64.556)
5 hp Gross horsepower quantile 25% 66.000 150.000
NA Total
1 230.438 (91.499) 230.722 (123.939)
2 162.375 120.825
3 296.850 326.000
4 138.500 (58.241) 146.688 (68.563)
5 102.500 96.500
Code
crosstable(iris2, c(Sepal.Length), funs = "mean")
Output
# A tibble: 1 x 4
.id label variable value
<chr> <chr> <chr> <chr>
1 Sepal.Length Length of Sepal "\"mean\"" 5.8
Code
crosstable(iris2, c(Sepal.Length), funs = mean)
Output
# A tibble: 1 x 4
.id label variable value
<chr> <chr> <chr> <chr>
1 Sepal.Length Length of Sepal mean 5.8
Code
crosstable(iris2, c(Sepal.Length), funs = cross_summary)
Output
# A tibble: 4 x 4
.id label variable value
<chr> <chr> <chr> <chr>
1 Sepal.Length Length of Sepal cross_summary Min / Max 4.3 / 7.9
2 Sepal.Length Length of Sepal cross_summary Med [IQR] 5.8 [5.1;6.4]
3 Sepal.Length Length of Sepal cross_summary Mean (std) 5.8 (0.8)
4 Sepal.Length Length of Sepal cross_summary N (NA) 150 (0)
Code
crosstable(iris2, c(Sepal.Length), funs = function(xx) xx[1])
Condition
Warning:
Anonymous functions should be named.
i Instead of: `funs=function(xx){}`
i Write: `funs=c("Some calculation"=function(xx){}`
Output
# A tibble: 1 x 4
.id label variable value
<chr> <chr> <chr> <chr>
1 Sepal.Length Length of Sepal function(xx){} 5.1
Code
crosstable(iris2, c(Sepal.Length), funs = function(xx) {
y = 4
xx[1]
})
Condition
Warning:
Anonymous functions should be named.
i Instead of: `funs=function(xx){}`
i Write: `funs=c("Some calculation"=function(xx){}`
Output
# A tibble: 1 x 4
.id label variable value
<chr> <chr> <chr> <chr>
1 Sepal.Length Length of Sepal function(xx){} 5.1
Code
crosstable(iris2, c(Sepal.Length), funs = ~ mean(.x, na.rm = TRUE))
Condition
Warning:
Anonymous lambda-functions should be named.
i Instead of: `funs=~mean(.x, na.rm = TRUE)`
i Write: `funs=c("Some calculation"=~mean(.x, na.rm = TRUE)`
Output
# A tibble: 1 x 4
.id label variable value
<chr> <chr> <chr> <chr>
1 Sepal.Length Length of Sepal ~mean(.x, na.rm = TRUE) 5.8
Code
crosstable(iris2, c(Sepal.Length), funs = c(~ mean(.x, na.rm = TRUE), ~ sd(.x,
na.rm = TRUE)))
Condition
Warning:
Anonymous lambda-functions should be named.
i Instead of: `funs=~mean(.x, na.rm = TRUE)`
i Write: `funs=c("Some calculation"=~mean(.x, na.rm = TRUE)`
Warning:
Anonymous lambda-functions should be named.
i Instead of: `funs=~sd(.x, na.rm = TRUE)`
i Write: `funs=c("Some calculation"=~sd(.x, na.rm = TRUE)`
Output
# A tibble: 2 x 4
.id label variable value
<chr> <chr> <chr> <chr>
1 Sepal.Length Length of Sepal ~mean(.x, na.rm = TRUE) 5.8
2 Sepal.Length Length of Sepal ~sd(.x, na.rm = TRUE) 0.8
Code
crosstable(iris2, c(Sepal.Length), funs = c(`My mean` = mean))
Output
# A tibble: 1 x 4
.id label variable value
<chr> <chr> <chr> <chr>
1 Sepal.Length Length of Sepal My mean 5.8
Code
crosstable(iris2, c(Sepal.Length), funs = c(` ` = cross_summary))
Output
# A tibble: 4 x 4
.id label variable value
<chr> <chr> <chr> <chr>
1 Sepal.Length Length of Sepal Min / Max 4.3 / 7.9
2 Sepal.Length Length of Sepal Med [IQR] 5.8 [5.1;6.4]
3 Sepal.Length Length of Sepal Mean (std) 5.8 (0.8)
4 Sepal.Length Length of Sepal N (NA) 150 (0)
Code
crosstable(iris2, c(Sepal.Length), funs = list(` ` = cross_summary))
Output
# A tibble: 4 x 4
.id label variable value
<chr> <chr> <chr> <chr>
1 Sepal.Length Length of Sepal Min / Max 4.3 / 7.9
2 Sepal.Length Length of Sepal Med [IQR] 5.8 [5.1;6.4]
3 Sepal.Length Length of Sepal Mean (std) 5.8 (0.8)
4 Sepal.Length Length of Sepal N (NA) 150 (0)
Code
crosstable(iris2, c(Sepal.Length), funs = c(first = ~ .x[1]))
Output
# A tibble: 1 x 4
.id label variable value
<chr> <chr> <chr> <chr>
1 Sepal.Length Length of Sepal first 5.1
Code
crosstable(iris2, c(Sepal.Length), funs = c(first = function(xx) xx[1]))
Output
# A tibble: 1 x 4
.id label variable value
<chr> <chr> <chr> <chr>
1 Sepal.Length Length of Sepal first 5.1
Code
crosstable(iris2, c(Sepal.Length), funs = c(first = function(xx) {
y = 4
xx[1]
}))
Output
# A tibble: 1 x 4
.id label variable value
<chr> <chr> <chr> <chr>
1 Sepal.Length Length of Sepal first 5.1
Code
crosstable(iris2, c(Sepal.Length), funs = c(mean = ~ mean(.x, na.rm = TRUE)))
Output
# A tibble: 1 x 4
.id label variable value
<chr> <chr> <chr> <chr>
1 Sepal.Length Length of Sepal mean 5.8
Code
crosstable(iris2, c(Sepal.Length), funs = c(mean = ~ mean(.x, na.rm = TRUE),
std = ~ sd(.x, na.rm = TRUE)))
Output
# A tibble: 2 x 4
.id label variable value
<chr> <chr> <chr> <chr>
1 Sepal.Length Length of Sepal mean 5.8
2 Sepal.Length Length of Sepal std 0.8
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