183 articles tagged #Debugging
COUNTIFS applies AND logic by default, so combining OR conditions inside one formula silently undercounts your data. Here's exactly why it breaks and four reliable patterns to fix it.
Your INSERT ... ON CONFLICT DO UPDATE is firing on every row, stamping updated_at even when nothing changed. Here's why that happens and exactly how to fix it with a conditional DO UPDATE clause.
XLOOKUP silently returns wrong values when your search array contains merged cells — not an error, just the wrong answer. Here's exactly why it happens and how to fix it for good.
Your INDEX MATCH formula works fine on a single column but throws #VALUE! the moment you extend it across multiple columns. Here's exactly why that happens and the precise fixes to make it work.
VLOOKUP always returns the first match it finds — so when your lookup table has duplicate keys, you get the wrong value with no error to warn you. Here's how to diagnose the problem and fix it for good.
Object destructuring makes JavaScript code cleaner and more readable, but destructuring nested objects can unexpectedly produce undefined values or even runtime errors when properties don't exist. Learn why this happens, how destructuring actually works, and the safest patterns for working with deep
SSO-enabled teams often never see invitation emails, and your app silently drops them with no error. Here's how to diagnose the exact failure points and build an invitation flow that actually works for enterprise accounts.
AVERAGEIFS throws #DIV/0! and your named range looks perfectly fine — so what's going wrong? The culprit is usually a size mismatch or scope conflict that Excel silently fails on. Here's how to diagnose and fix it.
Your PostgreSQL rank is returning unexpected numbers when multiple rows share the same value in a partition. Here's exactly why RANK(), DENSE_RANK(), and ROW_NUMBER() behave differently on ties — and how to pick the right one.
Python's csv.DictReader may appear to skip rows, produce malformed records, or fail unexpectedly when a CSV file is opened with the wrong text encoding. Learn how character encodings affect CSV parsing, how to diagnose encoding-related issues, and how to build reliable CSV import pipelines.
Your SUMIF looks right, your criteria is correct, but the total is off — and the only thing that changed was filtering or hiding some rows. Here's exactly why SUMIF ignores your hidden-row expectations and how to fix it.
Running pd.merge() and getting way more rows than expected? When join keys aren't unique on both sides, Pandas does a cartesian product on matches — and the result can silently balloon your DataFrame. Here's how to diagnose and fix it.