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# load libraries as needed:
library(tidyverse)
## -- Attaching packages --------------------------------------------- tidyverse 1.3.0 --
## v ggplot2 3.3.0 v purrr 0.3.3
## v tibble 2.1.3 v dplyr 0.8.4
## v tidyr 1.0.2 v stringr 1.4.0
## v readr 1.3.1 v forcats 0.4.0
## Warning: package 'ggplot2' was built under R version 3.6.3
## -- Conflicts ------------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
library(janitor)
##
## Attaching package: 'janitor'
head(mtcars)
## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
dt <- mtcars[1:5, 1:4]
print(dt)
## mpg cyl disp hp
## Mazda RX4 21.0 6 160 110
## Mazda RX4 Wag 21.0 6 160 110
## Datsun 710 22.8 4 108 93
## Hornet 4 Drive 21.4 6 258 110
## Hornet Sportabout 18.7 8 360 175
mtcars %>%
tabyl(gear, cyl, show_NA = TRUE)
## gear 4 6 8
## 3 1 2 12
## 4 8 4 0
## 5 2 1 2
mtcars %>%
tabyl(gear, cyl, show_NA = TRUE) %>%
adorn_totals(where="row")
## gear 4 6 8
## 3 1 2 12
## 4 8 4 0
## 5 2 1 2
## Total 11 7 14
mtcars %>%
tabyl(gear, cyl, show_NA = TRUE) %>%
adorn_totals(where=c("row","col"))
## gear 4 6 8 Total
## 3 1 2 12 15
## 4 8 4 0 12
## 5 2 1 2 5
## Total 11 7 14 32
mtcars %>%
tabyl(gear, cyl, show_NA = TRUE) %>%
adorn_totals(where=c("row","col")) %>%
adorn_percentages(denominator = "col") %>%
adorn_pct_formatting(digits = 0)
## gear 4 6 8 Total
## 3 9% 29% 86% 47%
## 4 73% 57% 0% 38%
## 5 18% 14% 14% 16%
## Total 100% 100% 100% 100%
mtcars %>%
tabyl(gear, cyl, show_NA = TRUE) %>%
adorn_totals(where=c("row","col")) %>%
adorn_percentages(denominator = "col") %>%
adorn_pct_formatting(digits = 0) %>%
adorn_ns(position = "front")
## gear 4 6 8 Total
## 3 1 (9%) 2 (29%) 12 (86%) 15 (47%)
## 4 8 (73%) 4 (57%) 0 (0%) 12 (38%)
## 5 2 (18%) 1 (14%) 2 (14%) 5 (16%)
## Total 11 (100%) 7 (100%) 14 (100%) 32 (100%)
dt %>%
kable()
dt %>%
kable() %>%
kable_styling()
dt %>%
kable() %>%
kable_styling(bootstrap_options =
c("striped", "hover", "condensed", "responsive",
full_width = F, position = "center")
)
…
Analyzing Automobile Data with R
Analyzing Automobile Data with R

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Analyzing Automobile Data with R

  • 1.
  • 2. # load libraries as needed: library(tidyverse) ## -- Attaching packages --------------------------------------------- tidyverse 1.3.0 -- ## v ggplot2 3.3.0 v purrr 0.3.3 ## v tibble 2.1.3 v dplyr 0.8.4 ## v tidyr 1.0.2 v stringr 1.4.0 ## v readr 1.3.1 v forcats 0.4.0 ## Warning: package 'ggplot2' was built under R version 3.6.3 ## -- Conflicts ------------------------------------------------ tidyverse_conflicts() -- ## x dplyr::filter() masks stats::filter() ## x dplyr::lag() masks stats::lag() library(janitor) ## ## Attaching package: 'janitor'
  • 3. head(mtcars) ## mpg cyl disp hp drat wt qsec vs am gear carb ## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 ## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 ## Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 ## Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1 ## Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2 ## Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
  • 4. dt <- mtcars[1:5, 1:4] print(dt) ## mpg cyl disp hp ## Mazda RX4 21.0 6 160 110 ## Mazda RX4 Wag 21.0 6 160 110 ## Datsun 710 22.8 4 108 93 ## Hornet 4 Drive 21.4 6 258 110 ## Hornet Sportabout 18.7 8 360 175
  • 5.
  • 6. mtcars %>% tabyl(gear, cyl, show_NA = TRUE) ## gear 4 6 8 ## 3 1 2 12 ## 4 8 4 0 ## 5 2 1 2
  • 7. mtcars %>% tabyl(gear, cyl, show_NA = TRUE) %>% adorn_totals(where="row") ## gear 4 6 8 ## 3 1 2 12 ## 4 8 4 0 ## 5 2 1 2 ## Total 11 7 14
  • 8. mtcars %>% tabyl(gear, cyl, show_NA = TRUE) %>% adorn_totals(where=c("row","col")) ## gear 4 6 8 Total ## 3 1 2 12 15 ## 4 8 4 0 12 ## 5 2 1 2 5 ## Total 11 7 14 32
  • 9. mtcars %>% tabyl(gear, cyl, show_NA = TRUE) %>% adorn_totals(where=c("row","col")) %>% adorn_percentages(denominator = "col") %>% adorn_pct_formatting(digits = 0) ## gear 4 6 8 Total ## 3 9% 29% 86% 47% ## 4 73% 57% 0% 38% ## 5 18% 14% 14% 16% ## Total 100% 100% 100% 100%
  • 10. mtcars %>% tabyl(gear, cyl, show_NA = TRUE) %>% adorn_totals(where=c("row","col")) %>% adorn_percentages(denominator = "col") %>% adorn_pct_formatting(digits = 0) %>% adorn_ns(position = "front") ## gear 4 6 8 Total ## 3 1 (9%) 2 (29%) 12 (86%) 15 (47%) ## 4 8 (73%) 4 (57%) 0 (0%) 12 (38%) ## 5 2 (18%) 1 (14%) 2 (14%) 5 (16%) ## Total 11 (100%) 7 (100%) 14 (100%) 32 (100%)
  • 13.
  • 14. dt %>% kable() %>% kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive", full_width = F, position = "center") )
  • 15.