
Reconciling a Bank Statement CSV With Your Ledger in SQL
Match a bank statement CSV against a ledger in SQL with a date tolerance, pair duplicate amounts correctly, and explain the difference in totals row by row.
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Match a bank statement CSV against a ledger in SQL with a date tolerance, pair duplicate amounts correctly, and explain the difference in totals row by row.

Make quick charts from a large CSV: aggregate in DuckDB, plot with matplotlib or draw text bars in the terminal, and keep the charts honest.

Test whether a CSV column follows a normal distribution using skew, kurtosis, percentiles and Shapiro-Wilk, and why a huge file always fails the test.

Sample a large CSV for a quick first look: why the top rows mislead, random and reproducible sampling in DuckDB, and how the error shrinks with sample size.

Rank customers by revenue in a CSV with SQL, compute cumulative share and the top 10 percent, handle ties and refunds, and read the concentration curve.

Compare this month with last month from a CSV in SQL without being fooled by day counts, open periods or weekday mix, using 2 million real rows.

Find weekly and monthly rhythms in daily sales from a CSV: a weekday index, autocorrelation at lag 7, what a flat result looks like and how to adjust for it.

Build a cross tab of two CSV columns with DuckDB PIVOT, add row totals and percentages, and test with chi-square whether the two columns are really related.

Nine analysis moves for a CSV in SQL: cross tabs, period comparisons, concentration, seasonality, distribution shape, sampling, charts and reconciliation.

A tested guide to analytics on JSON event data: envelope versus properties, funnels and retention, typed columns, indexes, type drift and backfills.

Compare Excel PERCENTILE.INC, PERCENTILE.EXC and MEDIAN with PostgreSQL percentile_cont and percentile_disc, with worked numbers.

Split delimited text into columns or rows in Excel with TEXTSPLIT and Text to Columns and in PostgreSQL with split_part, string_to_array and unnest.
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