mutate(employee_id_key = str_trim(gsub("employee_id_", "", employee_id_key)),
hours_key = str_trim(gsub("hours_", "", hours_key))) %>%
filter(employee_id_key == hours_key) %>%
select(-employee_id_key, -hours_key)I am thankful for Google Colab and the ability to use R with it. I had a challenging dataset that required conversion from wide to long format. The difficulty arose because the transformation resulted in extra rows due to multiple columns needing to be pivoted.
After experimenting with different approaches, ChatGPT suggested creating keys from the column output and filtering based on those conditions. The initial code recommendation didn’t work, so I sought clarification. Ultimately, after cleaning up a NA value and identifying extra spaces in one of the columns, the following code proved to be the solution.