Upload README.md with huggingface_hub

README.md

@@ -1,249 +1,50 @@
 ---
-annotations_creators:
-- no-annotation
-language_creators:
-- found
-language:
-- en
 license: other
-multilinguality:
-- monolingual
-size_categories:
-- n<1K
-source_datasets:
-- original
-task_categories:
-- tabular-classification
-task_ids: []
 tags:
-- africa
-- humanitarian
 - hdx
-- electric-sheep-africa
-- demographics
-- health
-- jor
-pretty_name: Jordan - National Demographic and Health Data
-dataset_info:
-  features:
-  - name: ISO3
-    dtype: string
-  - name: DataId
-    dtype: int64
-  - name: Indicator
-    dtype: string
-  - name: Value
-    dtype: float64
-  - name: Precision
-    dtype: int64
-  - name: DHS_CountryCode
-    dtype: string
-  - name: CountryName
-    dtype: string
-  - name: SurveyYear
-    dtype: int64
-  - name: SurveyId
-    dtype: string
-  - name: IndicatorId
-    dtype: string
-  - name: IndicatorOrder
-    dtype: int64
-  - name: IndicatorType
-    dtype: string
-  - name: CharacteristicId
-    dtype: int64
-  - name: CharacteristicOrder
-    dtype: int64
-  - name: CharacteristicCategory
-    dtype: string
-  - name: CharacteristicLabel
-    dtype: string
-  - name: ByVariableId
-    dtype: int64
-  - name: ByVariableLabel
-    dtype: string
-  - name: IsTotal
-    dtype: int64
-  - name: IsPreferred
-    dtype: int64
-  - name: SDRID
-    dtype: string
-  - name: SurveyYearLabel
-    dtype: string
-  - name: SurveyType
-    dtype: string
-  - name: DenominatorWeighted
-    dtype: float64
-  - name: DenominatorUnweighted
-    dtype: float64
-  - name: CILow
-    dtype: float64
-  - name: CIHigh
-    dtype: float64
-  splits:
-  - name: train
-    num_bytes: 35364
-    num_examples: 129
-  - name: test
-    num_bytes: 9175
-    num_examples: 33
-  download_size: 30131
-  dataset_size: 44539
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+- humanitarian
+- asia
+- demographics-health
 ---
 
 # Jordan - National Demographic and Health Data
 
-**Publisher:** The DHS Program · **Source:** [HDX](https://data.humdata.org/dataset/dhs-data-for-jordan) · **License:** `hdx-other` · **Updated:** 2026-04-20
-
----
-
-## Abstract
+Contains data from the [DHS data portal](https://api.dhsprogram.com/). There is also a dataset containing [Jordan - Subnational Demographic and Health Data](https://data.humdata.org/dataset/dhs-subnational-data-for-jordan) on HDX.  The DHS Program Application Programming Interface (API) provides sof
 
-Contains data from the [DHS data portal](https://api.dhsprogram.com/). There is also a dataset containing [Jordan - Subnational Demographic and Health Data](https://data.humdata.org/dataset/dhs-subnational-data-for-jordan) on HDX.
+## Resources
 
-The DHS Program Application Programming Interface (API) provides software developers access to aggregated indicator data from The Demographic and Health Surveys (DHS) Program. The API can be used to create various applications to help analyze, visualize, explore and disseminate data on population, health, HIV, and nutrition from more than 90 countries.
+- **Resource Count**: 42
+- **Formats**: csv
+- **Last Updated**: 2026-04-20
 
-Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-04-20. Geographic scope: **JOR**.
+## Coverage
 
-*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
+jor
 
----
-
-## Dataset Characteristics
-
-| | |
-|---|---|
-| **Domain** | Public health |
-| **Unit of observation** | Country-level aggregates |
-| **Rows (total)** | 162 |
-| **Columns** | 29 (15 numeric, 14 categorical, 0 datetime) |
-| **Train split** | 129 rows |
-| **Test split** | 32 rows |
-| **Geographic scope** | JOR |
-| **Publisher** | The DHS Program |
-| **HDX last updated** | 2026-04-20 |
-
----
+## Tags
 
-## Variables
+`demographics`, `health`
 
-**Geographic** — `iso3` (JOR), `dhs_countrycode` (JO), `countryname` (Jordan), `surveyyear` (range 1990.0–2023.0), `surveyid` (JO1997DHS, JO2012DHS, JO2023DHS) and 6 others.
+## License
 
-**Outcome / Measurement** — `value` (range 0.5–99.5), `istotal` (range 1.0–1.0).
+**License ID**: hdx-other
 
-**Identifier / Metadata** — `dataid` (range 46593.0–834563.0), `indicatorid` (RH_DELP_C_DHF, CM_ECMR_C_U5M, CM_ECMR_C_IMR), `characteristicid` (range 1000.0–10000.0), `characteristiclabel` (Total, Total 15-49), `ispreferred` (range 0.0–1.0) and 3 others.
-
-**Other** — `indicator` (Place of delivery: Health facility, Under-five mortality rate, Infant mortality rate), `precision` (range 0.0–1.0), `indicatororder` (range 11763080.0–260321010.0), `characteristicorder` (range 0.0–10000.0), `denominatorweighted` (range 586.0–15190.0) and 3 others.
-
----
-
-## Quick Start
-
-```python
-from datasets import load_dataset
-
-ds    = load_dataset("electricsheepafrica/asia-demographics-dhs-data-for-jordan")
-train = ds["train"].to_pandas()
-test  = ds["test"].to_pandas()
+## Citation
 
-print(train.shape)
-train.head()
+```
+@dataset{{{slug}},
+  title = {{{title}}},
+  author = {{{org}}},
+  year = {{{last_updated[:4] if updated else 'unknown'}}},
+  URL = {{{hdx_url}}}
+}
 ```
 
----
-
-## Schema
-
-| Column | Type | Null % | Range / Sample Values |
-|---|---|---|---|
-| `iso3` | object | 0.0% | JOR |
-| `dataid` | int64 | 0.0% | 46593.0 – 834563.0 (mean 449228.2531) |
-| `indicator` | object | 0.0% | Place of delivery: Health facility, Under-five mortality rate, Infant mortality rate |
-| `value` | float64 | 0.0% | 0.5 – 99.5 (mean 40.4253) |
-| `precision` | int64 | 0.0% | 0.0 – 1.0 (mean 0.7963) |
-| `dhs_countrycode` | object | 0.0% | JO |
-| `countryname` | object | 0.0% | Jordan |
-| `surveyyear` | int64 | 0.0% | 1990.0 – 2023.0 (mean 2007.3457) |
-| `surveyid` | object | 0.0% | JO1997DHS, JO2012DHS, JO2023DHS |
-| `indicatorid` | object | 0.0% | RH_DELP_C_DHF, CM_ECMR_C_U5M, CM_ECMR_C_IMR |
-| `indicatororder` | int64 | 0.0% | 11763080.0 – 260321010.0 (mean 84493710.0) |
-| `indicatortype` | object | 0.0% | I |
-| `characteristicid` | int64 | 0.0% | 1000.0 – 10000.0 (mean 1722.2222) |
-| `characteristicorder` | int64 | 0.0% | 0.0 – 10000.0 (mean 802.4691) |
-| `characteristiccategory` | object | 0.0% | Total, Total 15-49 |
-| `characteristiclabel` | object | 0.0% | Total, Total 15-49 |
-| `byvariableid` | int64 | 0.0% | 0.0 – 631001.0 (mean 21284.537) |
-| `byvariablelabel` | object | 56.8% | Five years preceding the survey, Ten years preceding the survey, Three years preceding the survey |
-| `istotal` | int64 | 0.0% | 1.0 – 1.0 (mean 1.0) |
-| `ispreferred` | int64 | 0.0% | 0.0 – 1.0 (mean 0.7531) |
-| `sdrid` | object | 0.0% |  |
-| `surveyyearlabel` | float64 | 12.3% | 1990.0 – 2023.0 (mean 2005.9859) |
-| `surveytype` | object | 0.0% |  |
-| `denominatorweighted` | float64 | 34.6% | 586.0 – 15190.0 (mean 6206.8774) |
-| `denominatorunweighted` | float64 | 34.6% | 586.0 – 15190.0 (mean 6311.3019) |
-| `cilow` | float64 | 79.6% | 8.0 – 38.0 (mean 19.303) |
-| `cihigh` | float64 | 79.6% | 18.0 – 64.0 (mean 29.7879) |
-| `esa_source` | object | 0.0% |  |
-| `esa_processed` | object | 0.0% |  |
-
----
-
-## Numeric Summary
-
-| Column | Min | Max | Mean | Median |
-|---|---|---|---|---|
-| `dataid` | 46593.0 | 834563.0 | 449228.2531 | 431842.5 |
-| `value` | 0.5 | 99.5 | 40.4253 | 27.95 |
-| `precision` | 0.0 | 1.0 | 0.7963 | 1.0 |
-| `surveyyear` | 1990.0 | 2023.0 | 2007.3457 | 2007.0 |
-| `indicatororder` | 11763080.0 | 260321010.0 | 84493710.0 | 80299545.0 |
-| `characteristicid` | 1000.0 | 10000.0 | 1722.2222 | 1000.0 |
-| `characteristicorder` | 0.0 | 10000.0 | 802.4691 | 0.0 |
-| `byvariableid` | 0.0 | 631001.0 | 21284.537 | 0.0 |
-| `istotal` | 1.0 | 1.0 | 1.0 | 1.0 |
-| `ispreferred` | 0.0 | 1.0 | 0.7531 | 1.0 |
-| `surveyyearlabel` | 1990.0 | 2023.0 | 2005.9859 | 2007.0 |
-| `denominatorweighted` | 586.0 | 15190.0 | 6206.8774 | 5613.5 |
-| `denominatorunweighted` | 586.0 | 15190.0 | 6311.3019 | 5667.5 |
-| `cilow` | 8.0 | 38.0 | 19.303 | 17.0 |
-| `cihigh` | 18.0 | 64.0 | 29.7879 | 27.0 |
-
----
-
-## Curation
-
-Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`) were unified to `NaN`. 2 column(s) with >80% missing values were removed: `regionid`, `levelrank`. 1 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.
-
----
-
-## Limitations
 
-- Data originates from The DHS Program and has not been independently validated by ESA.
-- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
-- The following columns have >20% missing values and should be treated with caution in modelling: `byvariablelabel`, `denominatorweighted`, `denominatorunweighted`, `cilow`, `cihigh`.
-- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/dhs-data-for-jordan) for the publisher's own methodology notes and caveats.
+--- 
 
----
-
-## Citation
+*Curated into ML-ready Parquet format by [Electric Sheep Asia](https://huggingface.co/electricsheepasia).*
 
-```bibtex
-@dataset{hdx_asia_demographics_dhs_data_for_jordan,
-  title     = {Jordan - National Demographic and Health Data},
-  author    = {The DHS Program},
-  year      = {2026},
-  url       = {https://data.humdata.org/dataset/dhs-data-for-jordan},
-  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
-}
-```
-
----
+*Source: [dhs-data-for-jordan](https://data.humdata.org/dataset/dhs-data-for-jordan) via HDX (Humanitarian Data Exchange)*
 
-*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*
+*Last updated: 2026-04-20*