I have some NA values in my data that I would like to fill in according to the filename column. In order words, every observation with the same filename should have the same values in the discipline, nativeness, year, and gender columns. structure(list(TA = c("future_perfect", "future_progressive", "future_simple", "past_perfect", "past_perfect_progressive", "past_progressive", "past_simple", "present_perfect", "present_perfect_progressive", "present_progressive", "present_simple",… Read More How to fill in NA values according to a categorial variable in R

Below is a reprex of my confusion. I expect when I cross a 1-row tibble with a 2-row tibble, I get a 2-row tibble. This does work with atomic column types. However, if the 2-row tibble is a list of dataframes, I don’t get a 2-row table, like expected, but a 1-row table. This does… Read More `tidyr::crossing()` with a list of tibbles unexpectedly reduces rows

I have a list of 15 tibbles. The tibbles are in either one of 3 formats with different numbers of columns. What I am trying to do is to create a loop over all of the tibbles that will change each tibble depending on its structure. Essentially, I have the names of each tibble in… Read More How to use case_when and for loop to reorganize my tibbles in a list?

I am working with imaging data in a format similar to this: name side modality <chr> <chr> <chr> 1 alex right xray 2 alex left xray 3 brad right xray 4 brad left xray 5 alex right ct 6 alex left ct 7 brad right ct 8 alex right mri 9 brad right mri 10… Read More How to create tibble summarising missing imaging data in R

Let’s say we have the following tibble ( rank = c(1, 2, 3), race_A = c("John", "Nick", "George"), race_B = c("Jay", "Nick", "John"), race_C = c("Jay", "Jack", "Robbie") ) which generates this tibble # A tibble: 3 × 4 rank race_A race_B race_C <dbl> <chr> <chr> <chr> 1 1 John Jay Jay 2 2 Nick… Read More R dplyr pivot (rankings table) – new column with unique row values from multiple columns, then assign row values from another column

I have multiple (~40) excel files with identical column names and want to bring them all into 1 df and bind_rows but getting error due to data type mismatch. How/when do I convert all to character so that I can bind rows into 1 df? library(readxl) library(tidyverse) file.list <- list.files(pattern=’*.xlsx’, recursive = TRUE) df.list <-… Read More R how to change data types in list.file to prevent bind_rows error

I have created a tibble consisting of 6 columns containing 6 different variables that will be input for a user defined function. I am new to r, and I don’t know how to connect the tibble with user defined function. Please help. I have replaced the complex user defined function with simple user_defined_function for the… Read More How to use multiple variable from tibble in an user-defined function?

I have this list of lists: regions <- list(c("AO", "BI", "BW", "DJ", "DZ", "ET", "GH", "GM", "KE", "LS", "MA", "MR", "MW", "MZ", "NG", "SL", "SZ", "TN", "TZ", "UG", "ZA", "ZM", "ZR", "ZW"), c("BD", "CN", "HK", "ID", "IN", "KR", "MU", "MY", "PH", "PK", "SG", "TH", "TW", "VN", "AU", "NZ"), c("AT", "BA", "BE", "BL", "CH", "CI", "CT",… Read More From a list of list to tibble in long format

I have a list of tibbles (too many to do it manually) which are made up of data I need to tabulate. I want to get the p-values, but let say I want to get multiple columns and multiple rows from sthg like this: sample$ppara # A tibble: 9 × 8 effect group term estimate… Read More Get coefficents from a list of tibble

So I’m running some code on a dataset that is 9992 rows and 10 columns. Specifically, I’m checking if the dataset’s glimpse is a tibble, i.e., data %>% glimpse() %>% is_tibble(). It is outputting TRUE. But on other datasets, like the cars dataset, I’m getting FALSE. Why might this be the case? I ran data… Read More Why is the result of glimpse() a tibble for some but not all data?