Hello @Apurvaugale! Your question about removing columns from R DataFrames without disrupting structure is a common challenge, especially when dealing with messy datasets!
I’ve personally dealt with this a few times, and I find the **subset()** function in base R surprisingly handy for this task.
Here’s a quick example:
df <- subset(df, select = -c(column1, column2))
I prefer this method because it’s remarkably concise, easy to read, and it means you don’t require dplyr or other external dependencies if you’re sticking to base R. It works very well when I’m quickly testing things in RStudio or writing rapid scripts. Just a small heads-up: make sure your column names don’t have special characters, otherwise, subset() might throw a fit.
Hope this base R tip helps streamline your data cleaning!