👀 Views: 1982 💬 Answers: 1 📅 Created: 2025-06-12

data.table filtering R

I'm working through a tutorial and I'm getting frustrated with I'm working on a personal project and I'm sure I'm missing something obvious here, but I'm working with a scenario while trying to filter rows in a `data.table` based on multiple conditions. I'm using R version 4.3 and the `data.table` package for data manipulation. My goal is to keep only the rows where column `A` is greater than 5 and column `B` is equal to 'yes'. However, I noticed that the filtered result is not what I expect, as it seems to return fewer rows than anticipated. Here's the code I used: ```r library(data.table) dt <- data.table(A = c(1, 6, 7, 4, 5, 8), B = c('no', 'yes', 'yes', 'no', 'yes', 'yes')) filtered_dt <- dt[A > 5 & B == 'yes'] print(filtered_dt) ``` When I run this code, the output is: ``` A B 1: 6 yes 2: 7 yes 3: 8 yes ``` However, I expected to see more rows since I thought that the filter should include any rows with `A` greater than 5 and `B` equals 'yes'. I also tried using the following alternative syntax: ```r filtered_dt <- dt[.(A > 5, B == 'yes')] ``` But I got the same result. Additionally, I checked for any whitespace in column `B` and confirmed that there are no leading or trailing spaces. I even attempted to simplify my condition by filtering one column at a time, but that didn’t help either. Is there something I'm missing here, or is there a better way to implement this type of filtering? Any insights would be greatly appreciated! What am I doing wrong? This is part of a larger application I'm building. Is there a better approach? I'm working on a application that needs to handle this. I'm developing on Debian with R. I'm open to any suggestions.