tidyverse

问题 Just contextualizing, I work with psychometrics/psychological testing. I have a dataset formed of "points","percentile","z_real","z_normal","iq". I would like to have a single ggplot in which I could present the Z_score (from my raw data), the z_score (with an underlying normal distribution), and then have two supplementary x-axes with "raw score" and "iq scores". That's pretty common in statistics, as you can check it below This is the current plot This is the best solution I've got That's

问题 Just contextualizing, I work with psychometrics/psychological testing. I have a dataset formed of "points","percentile","z_real","z_normal","iq". I would like to have a single ggplot in which I could present the Z_score (from my raw data), the z_score (with an underlying normal distribution), and then have two supplementary x-axes with "raw score" and "iq scores". That's pretty common in statistics, as you can check it below This is the current plot This is the best solution I've got That's

问题 Just contextualizing, I work with psychometrics/psychological testing. I have a dataset formed of "points","percentile","z_real","z_normal","iq". I would like to have a single ggplot in which I could present the Z_score (from my raw data), the z_score (with an underlying normal distribution), and then have two supplementary x-axes with "raw score" and "iq scores". That's pretty common in statistics, as you can check it below This is the current plot This is the best solution I've got That's

问题 I have an output that looks like this: test_list <- list(list(x = c(10, 101, 3), y = c(9, 12, 11)), list(x = c(10, 133, 4), y = c(9, 15, 13)), list(x = c(10, 101, 90), y = c(9, 18, 11)), list(x = c(10, 101, 1), y = c(9, 10, 15))) I would like to select and modify specific elements of sublists x and y. For example I would like to replace the last element of x with a number from a vector or generated from a function - i.e; map the vector z <- c(10, 50, 6, 12) over the last element of sublists x

问题 I have an output that looks like this: test_list <- list(list(x = c(10, 101, 3), y = c(9, 12, 11)), list(x = c(10, 133, 4), y = c(9, 15, 13)), list(x = c(10, 101, 90), y = c(9, 18, 11)), list(x = c(10, 101, 1), y = c(9, 10, 15))) I would like to select and modify specific elements of sublists x and y. For example I would like to replace the last element of x with a number from a vector or generated from a function - i.e; map the vector z <- c(10, 50, 6, 12) over the last element of sublists x

问题 I just came across the "embracing operator" {{ }} in section 2.2.3 of the tidyverse style guide. What does the embracing operator {{ }} do in R? 回答1: It's called curly-curly operator (see ?"{{}}" ). It's useful when passing an argument that has to be substituted in place before being evaluated in another context. See this simple example (although a bit awkward as we could simple quote the "cyl" when calling the function here): library(dplyr) # does not work get_var <- function(data, column) {

问题 I just came across the "embracing operator" {{ }} in section 2.2.3 of the tidyverse style guide. What does the embracing operator {{ }} do in R? 回答1: It's called curly-curly operator (see ?"{{}}" ). It's useful when passing an argument that has to be substituted in place before being evaluated in another context. See this simple example (although a bit awkward as we could simple quote the "cyl" when calling the function here): library(dplyr) # does not work get_var <- function(data, column) {

问题 I am developing a tidyverse -based data workflow, and came across a situation where I have a data frame with lots of time intervals. Let's call the data frame my_time_intervals , and it can be reproduced like this: library(tidyverse) library(lubridate) my_time_intervals <- tribble( ~id, ~group, ~start_time, ~end_time, 1L, 1L, ymd_hms("2018-04-12 11:15:03"), ymd_hms("2018-05-14 02:32:10"), 2L, 1L, ymd_hms("2018-07-04 02:53:20"), ymd_hms("2018-07-14 18:09:01"), 3L, 1L, ymd_hms("2018-05-07 13:02

问题 In my plot below, I have two separate sources of data ( dat and dat2 ) used in two different geom_smooth() calls producing the black and the red regression lines ( see pic below ). Is it possible to manually add another legend that shows the black line is called "Between" and red line is called "Within" ? library(tidyverse) dat <- read.csv('https://raw.githubusercontent.com/rnorouzian/e/master/cw2.csv') dat$groups <- factor(dat$groups) dat2 <- dat %>% group_by(groups) %>% summarize(mean_x =

问题 I have the following data: library(dplyr) #> #> Attaching package: 'dplyr' #> The following objects are masked from 'package:stats': #> #> filter, lag #> The following objects are masked from 'package:base': #> #> intersect, setdiff, setequal, union set.seed(1) df <- data_frame( genes = paste("Gene_",letters[0:10],sep=""), X = rnorm(10, 0, 1), Y = rnorm(10, 0, 2), Z = rnorm(10, 0, 4)) df #> # A tibble: 10 × 4 #> genes X Y Z #> <chr> <dbl> <dbl> <dbl> #> 1 Gene_a -0.6264538 3.02356234 3