I am using the pivot
function from the lessR package, to create an Excel-like pivot table with two categorical variables that make up the vertical and horizontal categories, and a mean in each cell. (Hope this makes sense).
I followed the code that the documentation (https://cran.r-project.org/web/packages/lessR/vignettes/pivot.html) gives. Let's follow their example:
d <- Read("Employee")
a <- pivot(d, mean, Salary, Dept, Gender)
The data d
is like this:
Years Gender Dept Salary JobSat Plan Pre Post
Ritchie, Darnell 7 M ADMN 53788.26 med 1 82 92
Wu, James NA M SALE 94494.58 low 1 62 74
Hoang, Binh 15 M SALE 111074.86 low 3 96 97
Jones, Alissa 5 F <NA> 53772.58 <NA> 1 65 62
Downs, Deborah 7 F FINC 57139.90 high 2 90 86
Afshari, Anbar 6 F ADMN 69441.93 high 2 100 100
Knox, Michael 18 M MKTG 99062.66 med 3 81 84
Campagna, Justin 8 M SALE 72321.36 low 1 76 84
Kimball, Claire 8 F MKTG 61356.69 high 2 93 92
The pivottable a
is a nice table, exactly as I want it to look in terms of cell contents, etc. It appears to be a knitr_kable.
Gender F M
Dept
------- --------- ---------
ACCT 63237.16 59626.20
ADMN 81434.00 80963.35
FINC 57139.90 72967.60
MKTG 64496.02 99062.66
SALE 64188.25 86150.97
Next, I would like to make a dataframe out of this, for easier manipulation in my code and for copying it to the clipboard. However, I don't know how to convert a knitr_kable to a dataframe. Here is my code and the error it results in:
as.data.frame(a)
Error in as.data.frame.default(a) :
cannot coerce class ‘"knitr_kable"’ to a data.frame
The knitr-documentation does not say anything about this conversion - it is only about converting a dataframe to a knitr_kable
, which is the opposite of what I want.
I have also tried pivottabler
, but this has similar issues: the resulting class cannot be coerced to a dataframe either.
CodePudding user response:
Here are two potential answers:
Most direct: Wrangle the data yourself
If you're open to a tidyverse-style approach, it only takes a few lines to do the wrangling and summarising yourself. That will give you a datatable output that you can work with right away.
# load packages
library(lessR)
library(dplyr)
library(tidyr)
# load data
d <- Read("Employee")
# use tidyverse-style code to pivot and summarise the data yourself
d %>%
group_by(Gender, Dept) %>%
summarise(Salary_mean = mean(Salary)) %>%
pivot_wider(names_from= "Gender", values_from = "Salary_mean")
Read the knitr::kable() markdown output into a data frame
If you prefer to work backwards from a knitr::kable()
output to a dataframe, this is addressed in this SO question: Markdown table to data frame in R