Let’s hope this works:
rixpress::rxp_read("/nix/store/f02j8p8mrs8h1bxv2zin1p0fixh5b8gc-mtcars_head")
mpg cyl disp hp drat wt qsec vs am gear carb
1 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
2 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
3 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
4 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
5 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
6 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
rixpress::rxp_read("/nix/store/gasjw02rj4m7jn3vk10gfcd79bb0676s-mtcars_tail")
mpg cyl disp hp drat wt qsec vs am gear carb
2 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
3 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
4 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
5 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
6 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
rixpress::rxp_read("/nix/store/25igxlfndgssha61wxpgdyhmdfj747sa-mtcars_mpg")
mpg
2 30.4
3 33.9
4 27.3
5 26.0
6 30.4
This is code from the file content.qmd
.
library("chronicler")
data("avia")
head(avia)
# A tibble: 6 x 238
`unit,tra_meas,airp_pr\\time` `2018Q1` `2018M03` `2018M02` `2018M01` `2017Q4`
<chr> <chr> <chr> <chr> <chr> <chr>
1 FLIGHT,CAF_PAS,LU_ELLX_AT_LOWW 511 172 161 178 502
2 FLIGHT,CAF_PAS,LU_ELLX_BE_EBBR : : : : :
3 FLIGHT,CAF_PAS,LU_ELLX_CH_LSGG : : : : 399
4 FLIGHT,CAF_PAS,LU_ELLX_CH_LSZH 485 167 151 167 493
5 FLIGHT,CAF_PAS,LU_ELLX_DE_EDDF 834 293 267 274 790
6 FLIGHT,CAF_PAS,LU_ELLX_DE_EDDI : : : : :
# i 232 more variables: `2017Q3` <chr>, `2017Q2` <chr>, `2017Q1` <chr>,
# `2017M12` <chr>, `2017M11` <chr>, `2017M10` <chr>, `2017M09` <chr>,
# `2017M08` <chr>, `2017M07` <chr>, `2017M06` <chr>, `2017M05` <chr>,
# `2017M04` <chr>, `2017M03` <chr>, `2017M02` <chr>, `2017M01` <chr>,
# `2017` <chr>, `2016Q4` <chr>, `2016Q3` <chr>, `2016Q2` <chr>,
# `2016Q1` <chr>, `2016M12` <chr>, `2016M11` <chr>, `2016M10` <chr>,
# `2016M09` <chr>, `2016M08` <chr>, `2016M07` <chr>, `2016M06` <chr>, ...
rixpress::rxp_read("/nix/store/xckfrc0fx6wi384qvz11daj3mzaqr562-mtcars_tail_py")
mpg cyl disp hp drat wt qsec vs am gear carb
2 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
3 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
4 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
5 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
6 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2