Hi everyone,
While working through the course, I noticed that after renaming variables during the data cleaning step, I sometimes need to remember to update those names later in my ggplot code.
Do you usually keep the original variable names throughout the analysis, or is it considered good practice to rename them early in the cleaning process?
I’d appreciate any recommendations or workflow tips.
Thanks!
Hey! yeah! A common workflow is to rename variables early in your data cleaning pipeline and then use the new names consistently throughout the rest of the analysis.
There are a few advantages to this approach:
-
More descriptive and consistent variable names make the code easier to read and maintain.
-
You only have to remember the mapping from the raw data once.
-
Downstream code (plots, tables, models) is cleaner and less error-prone.
For example:
clean_data <- raw_data %>%
rename(
onset_date = OnsetDate,
report_date = ReportDate,
district = District
) %>%
mutate(...)
Then, throughout the rest of your script:
ggplot(clean_data, aes(x = onset_date, fill = district)) +
geom_histogram(binwidth = 7)
The main thing is to avoid mixing old and new names in the same analysis. If you rename a variable, update all subsequent code to use the new name.
If you’re working on a larger project, it’s also helpful to keep all renaming in one place (typically at the beginning of your data cleaning script), so there’s a single source of truth for your variable names. This makes your workflow much easier to follow and maintain.
Best,
Luis
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