👀 Views: 27 💬 Answers: 1 📅 Created: 2025-08-25

r tidyverse data-wrangling R

I'm trying to figure out I've been struggling with this for a few days now and could really use some help. I am trying to reshape my data frame from wide to long format using the `pivot_longer()` function from the `tidyr` package (version 1.1.3), but I am running into issues with how it handles NA values. My original data frame looks like this: ```r library(tidyr) data <- data.frame( id = 1:5, measurement_1 = c(2, NA, 5, 6, NA), measurement_2 = c(3, 4, NA, NA, 8) ) ``` When I apply `pivot_longer()`, I expect to get a long format where each measurement is in its own row, but I'm not sure how to properly handle the NA values. Here’s what I have tried so far: ```r long_data <- data %>% pivot_longer(cols = starts_with("measurement"), names_to = "measurement", values_to = "value") ``` However, this is resulting in the following output: ``` id measurement value 1 1 measurement_1 2 2 1 measurement_2 3 3 2 measurement_1 NA 4 2 measurement_2 4 5 3 measurement_1 5 6 3 measurement_2 NA 7 4 measurement_1 6 8 4 measurement_2 NA 9 5 measurement_1 NA 10 5 measurement_2 8 ``` What I really want is to remove any rows where the value is NA after reshaping, to clean up the output. I’ve attempted to use `drop_na()` right after `pivot_longer()`, but it doesn’t seem to work as expected: ```r long_data <- data %>% pivot_longer(cols = starts_with("measurement"), names_to = "measurement", values_to = "value") %>% drop_na(value) ``` When I do this, I still see the NA values in my resulting data frame. The resulting data frame looks like this: ``` id measurement value 1 1 measurement_1 2 2 1 measurement_2 3 3 2 measurement_1 NA 4 2 measurement_2 4 5 3 measurement_1 5 6 3 measurement_2 NA 7 4 measurement_1 6 8 4 measurement_2 NA 9 5 measurement_1 NA 10 5 measurement_2 8 ``` I would appreciate any guidance on how to correctly remove these NA values after reshaping the data. Is there a specific parameter in `pivot_longer()` that I might be overlooking, or do I need to implement a different approach to achieve a clean long format? My development environment is Windows. Any help would be greatly appreciated! This is for a microservice running on Ubuntu 20.04. Any pointers in the right direction?