analytics

Window functions perform calculations across rows related to the current row. I use them for running totals, rankings, and moving averages. Django's Window expression with functions like RowNumber, Rank, DenseRank provide SQL window function support.

Window functions perform calculations across row sets without grouping. ROWNUMBER assigns unique sequential numbers. RANK/DENSERANK handle ties differently. I use PARTITION BY to reset calculations per group. ORDER BY determines calculation order with

Static plots are fine for papers, but product and business reviews often benefit from interactive filtering and hover details. I use Plotly when I need fast exploratory dashboards without spinning up a full app. It is especially useful for cohort anal

A surprising amount of feature engineering is best done in SQL before Python ever runs. ROW_NUMBER, LAG, rolling windows, and partitioned aggregates are ideal for deriving customer behavior signals close to the source. I use SQL here when it reduces m

I reach for groupby when I need trustworthy aggregates that can power dashboards or analytical reports. Clear aggregation naming matters because these outputs frequently get joined back into feature tables or exported to BI systems. pivot_table is use

Location data becomes useful when spatial joins and distance-based features are handled correctly. GeoPandas is enough for many routing, service coverage, and market analysis tasks before you need heavier GIS infrastructure. I care about coordinate sy

For leaderboards, let the database do ranking. Window functions are fast and expressive. Use them to compute daily top N without Ruby loops.

LATERAL joins enable correlated subqueries in FROM clause. Each row can reference previous table columns. I use LATERAL for top-N-per-group queries. CROSS JOIN LATERAL iterates for each row. LEFT JOIN LATERAL includes rows without matches. Understandi

Advanced aggregations extract insights from data. ROLLUP creates hierarchical subtotals. CUBE generates all possible grouping combinations. GROUPING SETS specifies exact grouping combinations. FILTER clause conditions aggregations. String aggregation