About & known issues

What this dashboard is built from, and what to watch out for.

report tables

5,366

cells

figures

146

districts

265

checks passed

need review

Source

Everything here comes from Uganda Aquaculture Census 2025 (approved final report). The reference period is July 2024 – June 2025; the edition is published as 2025.

No microdata was available, so the dashboard is built from the report's published tables rather than from farm records. That sets a hard limit on what can be shown: there is no disaggregation beyond what the report itself published, and no level below district. Each of the 53 tables is stored cell for cell as printed, so every figure on this site can be traced back to its table in Report Tables.

How the figures are disaggregated

The report uses one set of breakdowns throughout:

National: Uganda as a whole.
Location: Rural and Urban.
Sub-region: The 17 UBOS statistical sub-regions.
ZARDI: The 10 Zonal Agricultural Research and Development Institute zones. These appear only in the annex tables and have no official UBOS geography codes, so they are treated as a labelled grouping rather than as geography.
District: All 146 districts, in the annex tables only.

Known issues in the source report

The dashboard reproduces the report and does not correct it. These problems were found while extracting it and have been raised for follow-up. Where a figure is affected, the printed value is what you see.

Figures that do not reconcile

Components published in the report do not add to the totals published alongside them. The printed values are shown unchanged.

main 3.7 col5 sub_region

Components do not add to the stated total: sub_region sums to 160 vs national 164 (2.4% off)

main 3.8 col7 sub_region

Components do not add to the stated total: sub_region sums to 609 vs national 667 (8.7% off)

main 3.9 col7 sub_region

Components do not add to the stated total: sub_region sums to 395 vs national 467 (15.4% off)

Chart defects

Problems in the embedded chart objects.

chart34

Series names come through as '#REF!' — broken Excel link in the source document.

Table and heading numbering

Numbering problems in the printed report. We carry the report’s own numbering so citations match the print.

3.2

Two headings are both numbered 3.2 ('Reason for Unstocked Production Methods' and 'Aquaculture Farms by Production Culture').

4.5

'Table 4. 5' is used twice: the 4.5a/b/c harvest series and 'Grow-out Farms Production in Metric Tonnes'.

5.4.1

Two headings are both numbered 5.4.1 (extension services and credit/membership).

5.8–5.12

Chapter 5 jumps from Table 5.7 to Table 5.13; 5.8–5.12 do not exist.

Smaller discrepancies

Gaps under about 2%, and columns where it could not be determined automatically whether a value is a count or a share.

main 4.12 col5

could not tell whether 'Fish escape' is a count or a share

main 5.3 col9

could not tell whether 'Insect larvae (Black Soldier Fly)' is a count or a share

main 6.4 col3

could not tell whether 'Seed Production (million) — Actual' is a count or a share

annex 5.1 Buganda col1

repeated as 55,753 inside the district block but 55,704 in the sub_region block

annex 5.1 Buganda col2

repeated as 85.2 inside the district block but 85.1 in the sub_region block

annex 5.1 Buganda col3

repeated as 47,393 inside the district block but 47,383 in the sub_region block

annex 5.1 Buganda col5

repeated as 8,294 inside the district block but 8,254 in the sub_region block

annex 5.1 Buganda col6

repeated as 73.1 inside the district block but 72.7 in the sub_region block

annex 5.1 col7 district

district sums to 113 vs national 111 (1.8% off — rounding?)

annex 5.1 col7 sub_region

sub_region sums to 112 vs national 111 (0.9% off — rounding?)

annex 5.1 col7 zardi

zardi sums to 112 vs national 111 (0.9% off — rounding?)

main 4.10 col1 urban_rural

urban_rural sums to 3,716 vs national 3,772 (1.5% off — rounding?)

main 4.11 col1 urban_rural

urban_rural sums to 2,476 vs national 2,508 (1.3% off — rounding?)

main 4.12 col1 urban_rural

urban_rural sums to 160 vs national 161 (0.6% off — rounding?)

main 6.3 col3 urban_rural

urban_rural sums to 18 vs national 18 (0.5% off — rounding?)

How it was built

A Python pipeline reads the approved document, stores all 53 tables verbatim, extracts the 37 figures from their embedded chart data (four of them carry values that appear in no table at all), and then derives the indicators used by the rest of the dashboard from those stored tables.

Every additive column is reconciled against its parts — Rural + Urban, the 17 sub-regions, the 10 ZARDIs and the 146 districts, each checked against the national row. 265 checks pass; the rest are listed above and were traced to the printed report rather than to the extraction.