tibble

I have code which I use to web scrape past air atmosphere data repeatedly by wrapping the httr in the function.The original code works well on looping task. You may find the original code here https://stackoverflow.com/a/52545775/7356308 . I modified it a bit to web-scrap different part in the website. Unfortunately it didn't return right format especially the observation time. #' @param region one of "`naconf`", "`samer`", "`pac`", "`nz`", "`ant`", "`np`", #' "`europe`", "`africa`", "`seasia`", "`mideast`" (which matches the #' values of the drop-down menu on the site) #' @param date an ISO

Brief Dataset description: I have survey data generated from Qualtrics, which I've imported into R as a tibble. Each column corresponds to a survey question, and I've preserved the original column order (to correspond with the order of the questions in the survey). Problem in plain language: Due to normal participant attrition, not all participants completed all of the questions in the survey. I want to know how far each participant got in the survey, and the last question they each answered before stopping. Problem statement in R: I want to generate (using tidyverse): 1) A new column ( lastq

I am working with data that has significant digits (i.e. digits after the "."). These digits appear when viewing my data both as a variable in base R, and also when the data is stored in a dataframe. However, they do not appear when I view the data in a tibble. I need to view these significant digits for my work. Is there a way to make them appear when using tibbles? Here is a reproducible example: x has 5 significant digits, and 3 are displayed when using base R: x = 1234.56789 x [1] 1234.568 Within a data.frame, 3 significant digits are also displayed: df = data.frame(x=x) df x 1 1234.568

I have ten datasets that have been read from Excel files, using the xlsx library, and stored in tibbles. I want to merge them. Here are example datasets. The number of variables differ between datasets, and some variables are only in one dataset. The value of the person variable will never overlap. data1 <- tibble(person = c("A","B","C"), test1 = as.factor(c(1,4,5)), test2 = c(14,25,10), test3 = c(12.5,16.0,4), test4 = c(16,23,21), test5 = as.factor(c(49,36,52))) data2 <- tibble(person = c("D","E","F"), test1 = c(8,7,2), test3 = c(6.5,12.0,19.5), test4 = as.factor(c(15,21,29)), test5 = as