Use this panel to build pivot tables and charts from your project data with a simple drag‑and‑drop interface. Three subtabs: Pivot table, Summary (one-dimensional heatmaps for categorical vars with <10 categories, mean/median for continuous), and All-by-all checks (pairwise significance tests).

Example bookmark:

• Comparing groups (gender) — heatmap pivot table

Quick start#

This panel is powered by PivotTable.js, which generates most of the UI dynamically. These are the actual widgets you can see/use:

1. 👉🏼 (Links / Factors / Sources) (Dropdown): Which table to analyse? — chooses which dataset to pivot.
2. 👉🏼 (After pipeline / Before pipeline) (Radio buttons): Which stage to analyse? — chooses post‑pipeline (matches other panels) vs raw data for the chosen dataset.
3. 👉🏼 (Refresh) (Button): reloads + re-renders the pivot with latest data.
4. 👉🏼 (Sig level) (Dropdown): significance threshold for 2-way table tests (0.10, 0.05, 0.01, 0.001).
5. 👉🏼 (Copy to Clipboard) (Button): copies the current pivot table/chart as an image.
6. 👉🏼 (Copy as Table) (Button): copies the pivot as tab-separated text — paste into Excel/Sheets to get a properly aligned table (Table renderer only).
7. 👉🏼 (Download XLSX) (Button): downloads the current pivot as .xlsx (Table renderer only). Merged cells (rowspan/colspan) are expanded so columns align correctly.
8. 👉🏼 (Help) (Button): opens help for the Statistics panel.
9. 👉🏼 Drag-and-drop fields (field chip list): shows available fields (columns). Drag a field chip into Rows, Cols, or Vals.
10. 👉🏼 (Rows / Cols / Vals) (Drag-and-drop drop zones): defines how the pivot is laid out and what values are summarised.
11. 👉🏼 (Aggregator) (Dropdown): chooses the aggregation function (e.g. Count, Sum, Average).
12. 👉🏼 (Vals) (Dropdown): chooses the numeric field to aggregate (only appears for aggregators that need it).
13. 👉🏼 (Renderer) (Dropdown): chooses the output type (table, heatmaps, Plotly charts).
14. 👉🏼 (Row Order / Col Order) (Dropdowns): chooses how row/column keys are sorted.
15. 👉🏼 (Filter popup on each field chip) (Popup): include/exclude values for that field.
16. 👉🏼 (Search) (Text field): searches within the field’s value list.
17. 👉🏼 (Checkbox list): ticks/unticks specific values.
18. 👉🏼 (× on a field chip) (Button): removes that field from Rows/Cols/Vals.

Arrange fields (drag and drop)#

• 👉🏼 Drag-and-drop list: the “pool” of fields you can use.
• 👉🏼 (Rows) (Drop zone): fields listed down the left side of the output.
• 👉🏼 (Cols) (Drop zone): fields listed across the top of the output.
• 👉🏼 (Vals) (Drop zone): numeric field(s) to summarise (when needed by the chosen aggregator).
• 👉🏼 (Drag within a zone): reorders fields.
• 👉🏼 (×) (Button): removes a field from a zone.

Choose the calculation ("Aggregator")#

• 👉🏼 (Aggregator) (Dropdown): chooses how each cell is calculated. Optional — you can leave this at the default Count (no additional variable needed).
• 👉🏼 (Count): how many rows fall into each cell.
• 👉🏼 (Sum / Average / Min / Max): summarises a numeric field.
• 👉🏼 (Unique Count): counts distinct values of a field.
• 👉🏼 (Vals) (Dropdown): choose which numeric field to summarise (optional, only shown when needed).

Filter or exclude values#

• 👉🏼 (Filter popup on a field chip) (Popup): include/exclude values for that field.
• 👉🏼 (Search) (Text field): narrows the value list.
• 👉🏼 (Checkbox list): include/exclude specific values (includes a “select all” control).

Sorting#

• 👉🏼 (Row Order) (Dropdown): sorts row keys (e.g. by key or by value, depending on the option).
• 👉🏼 (Col Order) (Dropdown): sorts column keys.

Heatmaps and charts#

• 👉🏼 (Renderer) (Dropdown): switches between:
• 👉🏼 Heatmaps (e.g. Heatmap, Row Heatmap, Col Heatmap)
• 👉🏼 Plotly charts (e.g. Bar, Line, Scatter, Stacked Bar, Area, Multiple Pie)

Export and sharing#

• 👉🏼 (Copy to Clipboard) (Button): copies the current pivot output as an image.
• 👉🏼 (Copy as Table) (Button): copies the pivot as TSV — pastes as a correctly aligned table in Excel or Google Sheets (Table renderer only).
• 👉🏼 (Download XLSX) (Button): exports the pivot table to .xlsx with merged cells expanded so columns align (Table renderer only).
• 👉🏼 (URL state): the pivot configuration is saved to the URL automatically, so you can bookmark/share it.

Significance testing#

When you build a 2-way count table (one field in Rows, one in Cols, Count aggregator), the app runs a statistical test and shows the result below the table.

• Sig level (dropdown): choose your significance threshold (0.10, 0.05, 0.01, or 0.001). The test result shows whether the association is significant at that level.
• Which test? The app picks the right test for your data:
• Chi-squared when both variables are nominal (e.g. categories with no natural order).
• Mantel (linear-by-linear) when one or both variables are ordinal (e.g. Likert scales, age bands). This test is more sensitive to ordered trends.
• All-by-all checks: below the pivot, tick Run all-by-all checks and click Run. The app tests every pair of categorical variables with 2–10 values, lists them by p-value, and shows heatmap tables for the significant ones. Useful for exploratory analysis when you have several group or rating variables.

Notes on the datasets#

• Links: every causal link plus metadata; includes AI fields (e.g. confidence) and reserved columns like original_cause, original_effect.
• Factors: unique factors with frequency, source count, citations, and original_label (ALL underlying original labels for the displayed factor, concatenated with line breaks, derived from the current stage's links like original_cause/effect).
• Sources: document metadata and flattened custom fields (custom_*).

💡Tip: For results that match other panels, use After Analysis Pipeline.