Posts about Data Cleaning.
Joining a column of names or tags into one comma-separated string used to need TEXTJOIN or a helper column. REDUCE does it in one formula, and lets you transform each item before it gets concatenated.
MAP takes your LAMBDA and runs it on every element in an array. No helper columns, no dragging formulas, no VBA loops. It's the Excel equivalent of a functional programming pattern, and once you've used it, going back to column-by-column formulas feels like a step backwards.
In a small team, you're the analyst, the engineer, the dashboard designer, and the person who explains what a p-value is at the all-hands.
The Keep Rows filter in the Power Query UI handles 80% of row filtering tasks without you ever opening the Advanced Editor. Most people skip past it and go straight to writing M. Five clicks and you're done, and the M it generates is clean enough to modify later.
VLOOKUP and XLOOKUP, but for files that don't fit in memory, joins on multiple keys, and many-to-many matches that VLOOKUP simply can't do.
You can't build every dashboard that gets requested. But 'no' lands differently depending on how you say it — and most data people either say yes to everything and resent it, or say no in ways that…
SUMIFS and COUNTIFS are great — until your data has 500,000 rows and Excel is grinding. Part 2 shows how to do everything your SUMIFS does, but with pandas groupby — faster, more flexible, and on d…
This isn't 'what is a variable' Python. This is: you have a CSV that's too big for Excel, you need it filtered by date and category, and you need the result saved as a clean file. Part 1 covers exa…