5 Excel chores worth automating with Python (and how to tell which ones aren't)

Description and use

Automating repetitive Excel tasks with Python reduces effort, catches errors, and preserves originals.

Problem

Repetitive manual Excel tasks that take more than 10 minutes weekly are costly and error‑prone.

Outcome

Scripts reduce weekly manual effort, prevent data loss, and catch bugs through row counts.

Workflow

• Count clicks vs rows to decide automation
• Identify four patterns: merge, clean, summarize, rename/sort
• Write Python script using pandas.concat, assign, to_datetime, pivot_table, to_excel
• Create run.bat, in/ and out/ folders, and README
• Print rows in/out/rejected at end for validation
• Keep original files untouched

Evidence

Rule of thumb: if the same manual sequence happens weekly and takes more than 10 minutes, a script pays for itself within a month.

Source

A script that exits without errors can still drop rows. I always print three numbers at the end: rows in, rows out, rows rejected (with a reason column).

Source

Write to a new file, never over the input.

Source