b-rodrigues / modern_r Goto Github PK

Hi,

According to the book:

map_at(numbers, c(1, 3), sqrt)

will generate the following output.

## [[1]]
## [1] 2.645751
## 
## [[2]]
## [1] 8
## 
## [[3]]
## [1] 4.358899
## 
## [[4]]
## [1] 64

However, the numbers vector takes values numbers <- c(0, 5, 8, 3, 2, 1)
and the output I get is:

## [[1]]
## [1] 0
## 
## [[2]]
## [1] 5
## 
## [[3]]
## [1] 2.828427
## 
## [[4]]
## [1] 3
## 
## [[5]]
## [1] 2
## 
## [[6]]
## [1] 1

This does make sense since the square root of 0 is 0 and the square root of 8 is 2.828427.

Looking forward to your response.
Thanks,
Leyla

@b-rodrigues Just to let you know the link for ggplot2 extensions here links to an adult website.
Other than that, brilliant website thank you.

In the preface section, there's a command to install packages

install.packages(c("tidyverse", "rsample", "recipes", "blogdown" ,"yardstick", "parsnip", "plm", "pwt9", "checkpoint", "Ecdat", "ggthemes", "ggfortify", "margins", "janitor", "rio", "colourpicker", "glmnet", "lhs", "mrlMBO", "mlbench", "ranger"))

Did you mean "mlrMBO"? As I couldn't find the package "mrlMBO".

Thanks

everything() documentation seems thin on the ground. It perhaps means everything_else()? But there are dark allusions to non-intuitive behaviour in the presence of minus-excluded column references??

Windows 10 RStudio seems to work just fine with UNIX-style forward slashes (/////) in file and setwd() references. It SEEMS to interpret \ as the UNIX-style escape character.

gitbash yields a terminal window for Windows 10 that understands UNIX commands ls, ln, vi, cd, mv, cp, mkdir... With / as understood in UNIX.

everything() documentation seems thin on the ground. It perhaps means everything_else()? But there are dark allusions to non-intuitive behaviour in the presence of minus-excluded column references??

For Newbies: briefly, around here somewhere: how group_by and filter are row oriented.

Hi:

In dplyr 0.8.5, starwars dataset uses "male" for "gender" column instead "masculine". That causes examples to fail.

So far, great book, easy to read and follow. Thank you very much. Regards.

A delight of R is this propensity for inscrutable-to-newbies error messages. A gentle suggestion as to which arguments' lengths are causing the trouble here seems in order.

Perhaps an example such as your here-present "toy" data.frame/tibble/tribble would play well in section 2.8, where you mention data.frames for the first time. Maybe give a newbie a chance to interact with the data.frame construct.

This "toy" example has few rows or columns, so, whatever you do to/with it will entirely fit on a screen as you write about group_by(), and its dplyr associates. The larger mtcars, starwars, iris, etc, can come later after some confidence is built.