3. Coding Walkthrough: pivot_longer Dataset: Pulse Data (SAS format). Problem: The BDI (depression) score is spread across four columns: bdi_score_bl, bdi_score_01m, bdi_score_06m, bdi_score_12m. The Process: Import: Used haven::read_sas. Clean Names: Used janitor::clean_names. Pivot: Targeted columns: bdi_score_bl to bdi_score_12m. names_to = "visit": Moves column headers to a new variable called "visit". values_to = "bdi": Moves the numbers to a new variable called "bdi". names_prefix = "bdi_score_": Strips the redundant prefix. Refinement: Used mutate and recode to change "bl" to "00m" for consistency. 4. Coding Walkthrough: pivot_wider Dataset: Synthetic analysis result. Context: Sometimes you have a long, tidy dataset (e.g., Mean scores for Treatment/Placebo at Pre/Post times) that you want to display in a paper. The Process: Used pivot_wider. names_from = "time": Turns "pre" and "post" rows into column headers. values_from = "mean": Fills the cells with the mean values. Result: A table that is easier for humans to read but harder for the computer to analyze further