👀 Views: 0 💬 Answers: 1 📅 Created: 2025-06-16

dplyr dataframe filtering R

I've been banging my head against this for hours. I'm confused about I've been struggling with this for a few days now and could really use some help... I'm having difficulty filtering rows in my data frame using `dplyr` based on multiple conditions. I want to select rows where the `age` is greater than 30 and the `status` is 'active', but I'm not getting the expected results. Here’s the code I’m using: ```r library(dplyr) df <- data.frame( id = 1:10, age = c(25, 35, 40, 22, 29, 45, 32, 28, 50, 36), status = c('inactive', 'active', 'active', 'inactive', 'inactive', 'active', 'active', 'inactive', 'active', 'inactive') ) filtered_df <- df %>% filter(age > 30 & status == 'active') ``` When I run this code, I expect to get a data frame with 4 rows based on my conditions, but I only get 2 rows returned: ``` id age status 1 2 35 active 2 3 40 active ``` I’ve checked the data, and I can see that there are indeed more rows that meet these conditions. To troubleshoot, I printed the unique values for `status` and checked for leading or trailing spaces, but everything seems fine: ```r unique(df$status) ``` Is there something I might be missing in my filtering logic? Also, could there be an scenario with how R is interpreting the data types in the `status` column? Any help would be appreciated! For context: I'm using R on Ubuntu. What am I doing wrong? What would be the recommended way to handle this? I'm working on a mobile app that needs to handle this. Cheers for any assistance!