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The Affected Lots table shifts the perspective from issue types to individual production lots. For the selected week and lines, it lists every lot that experienced at least one issue, showing how many issues were logged and which types were involved. This makes it easy to identify high-impact lots that need follow-up and to correlate problems with specific lot codes across reporting periods.

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Columns

ColumnDescription
week_labelISO week label for the selected week (e.g. 2026-W03)
line_nameName of the production line on which the lot ran
lot_codeUnique lot identifier (e.g. LOT-1001)
issue_countTotal number of issues recorded for this lot in the selected scope
issue_typesComma-separated, alphabetically sorted list of distinct issue type names logged against the lot

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Ordering

Rows are sorted by issue_count DESC so the most-affected lots appear at the top. Within the same issue count, rows are further ordered by lot_code ascending (alphabetical). This ordering comes directly from the SQL query: 
ORDER BY issue_count DESC, l.lot_code

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Example output

week_label | line_name | lot_code  | issue_count | issue_types
2026-W03   | Line 1    | LOT-1001  | 1           | tool_wear
2026-W03   | Line 1    | LOT-1002  | 1           | material_shortage
2026-W03   | Line 4    | LOT-3001  | 1           | sensor_fault

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Lot codes in seed data

The following lot codes appear in the default seed dataset:
Lot codeLines it appears on
LOT-1001Line 1
LOT-1002Line 1
LOT-2001Line 2
LOT-2002Line 2
LOT-3001Line 4
A lot may appear in multiple weeks — for example, LOT-1001 appears in both 2026-W03 (with a tool_wear issue) and 2026-W04 (with a changeover_delay issue). Within any single week-and-line scope, however, a lot appears at most once in this table, with its issues aggregated into the issue_count and issue_types columns.
The production_issues table enforces a UNIQUE constraint on production_run_id, meaning each production run can have at most one primary issue record. As a result, issue_count for a lot is equivalent to the number of production runs for that lot that have an issue recorded — it does not represent multiple issues on a single run.

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Dataframe display options

Like the Issue Summary table, the Affected Lots table is rendered with: 
st.dataframe(rows, hide_index=True, use_container_width=True)
If no affected lots are found for the current filter scope, the table is replaced with st.info("No affected lots found for the selected scope."). For details on the underlying fact tables that back this query, see the fact tables data model.

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