No. EDD's reports stay where merchants like them, with their period selector and headline graphs. The Charts view is an additional dashboard surface for cross-cutting questions the reports tab doesn't compose, like a refund-rate donut next to a revenue area chart on the same screen with the same filter.

Primarily edd_orders for revenue, order count, status, and gateway. Joins to edd_order_items for product-level aggregations and to edd_customers for customer-level LTV charts. Indexed columns (id, date_created, status, gateway) are used as groupBy keys so aggregations stay fast on stores with high order volume.

Yes. Charts and Table are two view types over the same dataset. A filter set on the Table view, like 'last 30 days, status = complete, gateway = stripe', applies to the Charts view automatically when you switch tabs. Switch back, the matching rows are still selected.

All chart aggregations run inside wp-admin against the EDD relational tables, paginated and indexed. Storefront pages and checkout are untouched. The Charts dashboard typically renders in under a second on stores with tens of thousands of orders because the groupBy columns are indexed.

Yes. Recurring Payments data in edd_subscriptions can power its own subscription charts (active vs cancelled, renewal trends, failed-payment rates). Software Licensing data in edd_licenses can power license-status pies or activation-trend area charts. Each add-on's tables become a chart-ready dataset.

Yes. Build a stacked area chart grouping by date_created with status as the series column. The refund slice grows when refund rate climbs, which is hard to miss visually compared to scrolling through the orders list. Pair with a horizontal bar of refund counts by product to find the source.

Yes. edd_ordermeta keys present in your data appear in the column picker, scoped to keys actually written. Useful for custom-checkout fields (referral source, campaign code) where you want a chart of revenue by attribution channel that EDD's own reports don't include.

The underlying dataset of any card exports as CSV. For the visual itself, screenshot or browser-print to PDF works fine for monthly reviews. The CSV path is more common since stakeholders typically want the numbers behind the chart for their own modeling.