Data Analyst

Learn when pandas utc=True converts an instant and when it assumes UTC. Test New York and London exports with explicit localization and source zones.

Understand SQL LAST_VALUE with a tested window-frame example. Compare the final value with MAX, preserve final NULLs, and avoid future-data leakage.

See how pandas groupby().first() can combine fields from different records. Preserve real rows with explicit sorting and head(1), with tested examples.

SQL LAG returns the previous row, not necessarily the previous month. Test missing periods, zero denominators, and monthly revenue comparisons.

Learn why pandas astype(bool) turns the string False into True. Parse CSV flags explicitly, preserve missing values, and verify conversion denominators.

Fix conditional SQL counts with a tested US/UK example. Compare COUNT and SUM, report unknown outcomes, and choose the right success-rate denominator.

Test why SUM(DISTINCT amount) undercounts equal-value orders. Fix join grain, compare EXISTS and reconcile a runnable US/UK revenue example.

Use pandas transform to add market totals without losing order rows. Test index alignment, zero denominators and repeated-total double counting.

Test SQL running totals with tied timestamps. Compare the default peer frame, explicit ROWS ordering, and daily aggregation using a reproducible USD example.

Pandas pivot_table defaults to mean. Use a tested US/UK order example to choose sum, reconcile revenue, and distinguish absent cells from confirmed zero sales.