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Query aggregated analytics data from DHIS2. Use for calculated/aggregated values, indicator values, or cross-dimensional analysis. ALWAYS use with dhis2-query-optimization skill. Routed via dhis2 skill for general DHIS2 requests.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Guide for creating OpenHEXA data pipelines. Use when users ask to create a pipeline, build a data pipeline, automate data processing, or schedule data workflows.
Work with DHIS2 health information systems - extract data, query metadata, run validations, manage users, or check system info. Use this skill for ANY DHIS2-related request. It routes to specialized sub-skills and provides centralized client setup and API patterns.
Extract data elements and data element groups from DHIS2. Use for data element metadata, groups, or category option combos. Routed via dhis2 skill for general DHIS2 requests.
Extract raw data values from DHIS2 using the dataValueSets API. Use for actual submitted data values, not aggregated analytics. ALWAYS use with dhis2-query-optimization skill. Routed via dhis2 skill for general DHIS2 requests.
Extract datasets metadata from DHIS2. Use for dataset definitions, data entry forms, or reporting frequencies. Routed via dhis2 skill for general DHIS2 requests.
Extract indicators and indicator groups from DHIS2. Use for indicator definitions, formulas, or indicator groups. Routed via dhis2 skill for general DHIS2 requests.
| name | dhis2-analytics |
| description | Query aggregated analytics data from DHIS2. Use for calculated/aggregated values, indicator values, or cross-dimensional analysis. ALWAYS use with dhis2-query-optimization skill. Routed via dhis2 skill for general DHIS2 requests. |
Prerequisites: Client setup from dhis2 skill + dhis2-query-optimization for large queries
from openhexa.toolbox.dhis2 import dataframe
| Parameter | Type | Required | Notes |
|---|---|---|---|
| dhis2 | DHIS2 | Yes | |
| periods | list[str] | Yes | e.g., ["2021", "202401"] |
| data_elements | list[str] | None | No | Cannot mix with indicators |
| data_element_groups | list[str] | None | No | Cannot mix with indicators |
| indicators | list[str] | None | No | Cannot mix with data_elements |
| indicator_groups | list[str] | None | No | Cannot mix with data_elements |
| org_units | list[str] | None | No | At least one spatial dim required |
| org_unit_groups | list[str] | None | No | At least one spatial dim required |
| org_unit_levels | list[int] | None | No | At least one spatial dim required |
Returns pl.DataFrame:
For data elements:
| Column | Type |
|---|---|
| data_element_id | str |
| category_option_combo_id | str |
| organisation_unit_id | str |
| period | str |
| value | str |
For indicators (no category_option_combo_id):
| Column | Type |
|---|---|
| indicator_id | str |
| organisation_unit_id | str |
| period | str |
| value | str |
# Data elements
data = dhis.analytics.get(
data_elements=["uid"],
org_units=["uid"],
periods=["202401"]
) # Returns list[dict]
# Indicators - ALWAYS use include_cocs=False
data = dhis.analytics.get(
indicators=["uid"],
org_units=["uid"],
periods=["2024"],
include_cocs=False # MANDATORY for indicators
)