Hi,
My question is how to transpose str(), skim(), glimpse() in order to display variables in columns
not in rows like they do ? Sort of like in displaying tibbles but I do not want to change a table to tibble every time.
when I do:
skimr::skim(wages) %>% t()
it displays nonsens.
thanks
str can only be printed
str does not return anything, for efficiency reasons—help(str)
t(skimr::skim(mtcars))
#> 1 2 3 4
#> skim_type "numeric" "numeric" "numeric" "numeric"
#> skim_variable "mpg" "cyl" "disp" "hp"
#> n_missing "0" "0" "0" "0"
#> complete_rate "1" "1" "1" "1"
#> numeric.mean " 20.090625" " 6.187500" "230.721875" "146.687500"
#> numeric.sd " 6.0269481" " 1.7859216" "123.9386938" " 68.5628685"
#> numeric.p0 "10.400" " 4.000" "71.100" "52.000"
#> numeric.p25 " 15.42500" " 4.00000" "120.82500" " 96.50000"
#> numeric.p50 " 19.200" " 6.000" "196.300" "123.000"
#> numeric.p75 " 22.80" " 8.00" "326.00" "180.00"
#> numeric.p100 " 33.900" " 8.000" "472.000" "335.000"
#> numeric.hist "▃▇▅▁▂" "▆▁▃▁▇" "▇▃▃▃▂" "▇▇▆▃▁"
#> 5 6 7 8
#> skim_type "numeric" "numeric" "numeric" "numeric"
#> skim_variable "drat" "wt" "qsec" "vs"
#> n_missing "0" "0" "0" "0"
#> complete_rate "1" "1" "1" "1"
#> numeric.mean " 3.596563" " 3.217250" " 17.848750" " 0.437500"
#> numeric.sd " 0.5346787" " 0.9784574" " 1.7869432" " 0.5040161"
#> numeric.p0 " 2.760" " 1.513" "14.500" " 0.000"
#> numeric.p25 " 3.08000" " 2.58125" " 16.89250" " 0.00000"
#> numeric.p50 " 3.695" " 3.325" " 17.710" " 0.000"
#> numeric.p75 " 3.92" " 3.61" " 18.90" " 1.00"
#> numeric.p100 " 4.930" " 5.424" " 22.900" " 1.000"
#> numeric.hist "▇▃▇▅▁" "▃▃▇▁▂" "▃▇▇▂▁" "▇▁▁▁▆"
#> 9 10 11
#> skim_type "numeric" "numeric" "numeric"
#> skim_variable "am" "gear" "carb"
#> n_missing "0" "0" "0"
#> complete_rate "1" "1" "1"
#> numeric.mean " 0.406250" " 3.687500" " 2.812500"
#> numeric.sd " 0.4989909" " 0.7378041" " 1.6152000"
#> numeric.p0 " 0.000" " 3.000" " 1.000"
#> numeric.p25 " 0.00000" " 3.00000" " 2.00000"
#> numeric.p50 " 0.000" " 4.000" " 2.000"
#> numeric.p75 " 1.00" " 4.00" " 4.00"
#> numeric.p100 " 1.000" " 5.000" " 8.000"
#> numeric.hist "▇▁▁▁▆" "▇▁▆▁▂" "▇▂▅▁▁"
t(dplyr::glimpse(mtcars))
#> Rows: 32
#> Columns: 11
#> $ mpg <dbl> 21.0, 21.0, 22.8, 21.4, 18.7, 18.1, 14.3, 24.4, 22.8, 19.2, 17.8,…
#> $ cyl <dbl> 6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8, 8, 8, 8, 8, 8, 4, 4, 4, 4, 8,…
#> $ disp <dbl> 160.0, 160.0, 108.0, 258.0, 360.0, 225.0, 360.0, 146.7, 140.8, 16…
#> $ hp <dbl> 110, 110, 93, 110, 175, 105, 245, 62, 95, 123, 123, 180, 180, 180…
#> $ drat <dbl> 3.90, 3.90, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92,…
#> $ wt <dbl> 2.620, 2.875, 2.320, 3.215, 3.440, 3.460, 3.570, 3.190, 3.150, 3.…
#> $ qsec <dbl> 16.46, 17.02, 18.61, 19.44, 17.02, 20.22, 15.84, 20.00, 22.90, 18…
#> $ vs <dbl> 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0,…
#> $ am <dbl> 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0,…
#> $ gear <dbl> 4, 4, 4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3,…
#> $ carb <dbl> 4, 4, 1, 1, 2, 1, 4, 2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2,…
#> Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive Hornet Sportabout
#> mpg 21.00 21.000 22.80 21.400 18.70
#> cyl 6.00 6.000 4.00 6.000 8.00
#> disp 160.00 160.000 108.00 258.000 360.00
#> hp 110.00 110.000 93.00 110.000 175.00
#> drat 3.90 3.900 3.85 3.080 3.15
#> wt 2.62 2.875 2.32 3.215 3.44
#> qsec 16.46 17.020 18.61 19.440 17.02
#> vs 0.00 0.000 1.00 1.000 0.00
#> am 1.00 1.000 1.00 0.000 0.00
#> gear 4.00 4.000 4.00 3.000 3.00
#> carb 4.00 4.000 1.00 1.000 2.00
#> Valiant Duster 360 Merc 240D Merc 230 Merc 280 Merc 280C Merc 450SE
#> mpg 18.10 14.30 24.40 22.80 19.20 17.80 16.40
#> cyl 6.00 8.00 4.00 4.00 6.00 6.00 8.00
#> disp 225.00 360.00 146.70 140.80 167.60 167.60 275.80
#> hp 105.00 245.00 62.00 95.00 123.00 123.00 180.00
#> drat 2.76 3.21 3.69 3.92 3.92 3.92 3.07
#> wt 3.46 3.57 3.19 3.15 3.44 3.44 4.07
#> qsec 20.22 15.84 20.00 22.90 18.30 18.90 17.40
#> vs 1.00 0.00 1.00 1.00 1.00 1.00 0.00
#> am 0.00 0.00 0.00 0.00 0.00 0.00 0.00
#> gear 3.00 3.00 4.00 4.00 4.00 4.00 3.00
#> carb 1.00 4.00 2.00 2.00 4.00 4.00 3.00
#> Merc 450SL Merc 450SLC Cadillac Fleetwood Lincoln Continental
#> mpg 17.30 15.20 10.40 10.400
#> cyl 8.00 8.00 8.00 8.000
#> disp 275.80 275.80 472.00 460.000
#> hp 180.00 180.00 205.00 215.000
#> drat 3.07 3.07 2.93 3.000
#> wt 3.73 3.78 5.25 5.424
#> qsec 17.60 18.00 17.98 17.820
#> vs 0.00 0.00 0.00 0.000
#> am 0.00 0.00 0.00 0.000
#> gear 3.00 3.00 3.00 3.000
#> carb 3.00 3.00 4.00 4.000
#> Chrysler Imperial Fiat 128 Honda Civic Toyota Corolla Toyota Corona
#> mpg 14.700 32.40 30.400 33.900 21.500
#> cyl 8.000 4.00 4.000 4.000 4.000
#> disp 440.000 78.70 75.700 71.100 120.100
#> hp 230.000 66.00 52.000 65.000 97.000
#> drat 3.230 4.08 4.930 4.220 3.700
#> wt 5.345 2.20 1.615 1.835 2.465
#> qsec 17.420 19.47 18.520 19.900 20.010
#> vs 0.000 1.00 1.000 1.000 1.000
#> am 0.000 1.00 1.000 1.000 0.000
#> gear 3.000 4.00 4.000 4.000 3.000
#> carb 4.000 1.00 2.000 1.000 1.000
#> Dodge Challenger AMC Javelin Camaro Z28 Pontiac Firebird Fiat X1-9
#> mpg 15.50 15.200 13.30 19.200 27.300
#> cyl 8.00 8.000 8.00 8.000 4.000
#> disp 318.00 304.000 350.00 400.000 79.000
#> hp 150.00 150.000 245.00 175.000 66.000
#> drat 2.76 3.150 3.73 3.080 4.080
#> wt 3.52 3.435 3.84 3.845 1.935
#> qsec 16.87 17.300 15.41 17.050 18.900
#> vs 0.00 0.000 0.00 0.000 1.000
#> am 0.00 0.000 0.00 0.000 1.000
#> gear 3.00 3.000 3.00 3.000 4.000
#> carb 2.00 2.000 4.00 2.000 1.000
#> Porsche 914-2 Lotus Europa Ford Pantera L Ferrari Dino Maserati Bora
#> mpg 26.00 30.400 15.80 19.70 15.00
#> cyl 4.00 4.000 8.00 6.00 8.00
#> disp 120.30 95.100 351.00 145.00 301.00
#> hp 91.00 113.000 264.00 175.00 335.00
#> drat 4.43 3.770 4.22 3.62 3.54
#> wt 2.14 1.513 3.17 2.77 3.57
#> qsec 16.70 16.900 14.50 15.50 14.60
#> vs 0.00 1.000 0.00 0.00 0.00
#> am 1.00 1.000 1.00 1.00 1.00
#> gear 5.00 5.000 5.00 5.00 5.00
#> carb 2.00 2.000 4.00 6.00 8.00
#> Volvo 142E
#> mpg 21.40
#> cyl 4.00
#> disp 121.00
#> hp 109.00
#> drat 4.11
#> wt 2.78
#> qsec 18.60
#> vs 1.00
#> am 1.00
#> gear 4.00
#> carb 2.00
Thank you Technocrat, this is it.
Additionally there is a new package;
install.packages("paint", repos = c(mm = "https://milesmcbain.r-universe.dev", c(getOption("repos"))))
and I did it that way as well:
paint::paint(mtcars) %>% pivot_wider()
thanks again
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