Add README.md

README.md

@@ -9,12 +9,11 @@ license: other
 multilinguality:
 - monolingual
 size_categories:
-- 1K<n<10K
+- n<1K
 source_datasets:
 - original
 task_categories:
 - tabular-classification
-- other
 task_ids: []
 tags:
 - africa
@@ -24,98 +23,28 @@ tags:
 - demographics
 - health
 - zmb
-pretty_name: Zambia - Subnational Demographic and Health Data
+pretty_name: "Zambia - 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
-  - name: esa_source
-    dtype: string
-  - name: esa_processed
-    dtype: string
   splits:
-  - name: train
-    num_bytes: 48430
-    num_examples: 164
-  - name: test
-    num_bytes: 12592
-    num_examples: 42
-  download_size: 33292
-  dataset_size: 61022
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+    - name: train
+      num_examples: 164
+    - name: test
+      num_examples: 41
 ---
 
-# Zambia - Subnational Demographic and Health Data
+# Zambia - National Demographic and Health Data
 
-**Publisher:** The DHS Program · **Source:** [HDX](https://data.humdata.org/dataset/dhs-subnational-data-for-zambia) · **License:** `hdx-other` · **Updated:** 2026-04-20
+**Publisher:** The DHS Program · **Source:** [HDX](https://data.humdata.org/dataset/dhs-data-for-zambia) · **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 [Zambia - National Demographic and Health Data](https://data.humdata.org/dataset/dhs-data-for-zambia) on HDX.
+Contains data from the [DHS data portal](https://api.dhsprogram.com/). There is also a dataset containing [Zambia - Subnational Demographic and Health Data](https://data.humdata.org/dataset/dhs-subnational-data-for-zambia) on HDX.
 
 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.
 
-Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-04-20. Geographic scope: **ZMB**.
+Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-04-20. Geographic scope: **ZMB**.
 
 *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
 
@@ -126,11 +55,11 @@ Each row in this dataset represents first-level administrative unit observations
 | | |
 |---|---|
 | **Domain** | Public health |
-| **Unit of observation** | First-level administrative unit observations |
-| **Rows (total)** | 1,743 |
-| **Columns** | 30 (14 numeric, 16 categorical, 0 datetime) |
-| **Train split** | 1,394 rows |
-| **Test split** | 348 rows |
+| **Unit of observation** | Country-level aggregates |
+| **Rows (total)** | 206 |
+| **Columns** | 29 (14 numeric, 15 categorical, 0 datetime) |
+| **Train split** | 164 rows |
+| **Test split** | 41 rows |
 | **Geographic scope** | ZMB |
 | **Publisher** | The DHS Program |
 | **HDX last updated** | 2026-04-20 |
@@ -139,13 +68,13 @@ Each row in this dataset represents first-level administrative unit observations
 
 ## Variables
 
-**Geographic** — `iso3` (ZMB), `location` (Central, Copperbelt, Luapula), `dhs_countrycode` (ZM), `countryname` (Zambia), `surveyyear` (range 1992.0–2024.0) and 8 others.
+**Geographic** — `iso3` (ZMB), `dhs_countrycode` (ZM), `countryname` (Zambia), `surveyyear` (range 1992.0–2024.0), `surveyid` (ZM2018DHS, ZM2024DHS, ZM2007DHS) and 6 others.
 
-**Outcome / Measurement** — `value` (range 0.0–254.0), `istotal` (range 0.0–0.0).
+**Outcome / Measurement** — `value` (range 0.4–729.0), `istotal` (range 1.0–1.0).
 
-**Identifier / Metadata** — `dataid` (range 584.0–7980700.0), `indicatorid` (RH_DELP_C_DHF, CH_DIAT_C_ORT, FE_FRTR_W_TFR), `characteristicid` (range 456001.0–456012.0), `characteristiclabel` (Central, Copperbelt, Luapula), `ispreferred` (range 0.0–1.0) and 3 others.
+**Identifier / Metadata** — `dataid` (range 41515.0–834693.0), `indicatorid` (RH_DELP_C_DHF, CH_DIAT_C_ORT, 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, Treatment of diarrhea: Either ORS or RHF, Total fertility rate 15-49), `precision` (range 0.0–1.0), `indicatororder` (range 11763080.0–260321010.0), `characteristicorder` (range 1456001.0–1456012.0), `denominatorweighted` (range 24.0–5683.0) and 2 others.
+**Other** — `indicator` (Place of delivery: Health facility, Treatment of diarrhea: Either ORS or RHF, Infant mortality rate), `precision` (range 0.0–1.0), `indicatororder` (range 11763080.0–260321010.0), `characteristicorder` (range 0.0–10000.0), `denominatorweighted` (range 745.0–27859.0) and 3 others.
 
 ---
 
@@ -169,33 +98,32 @@ train.head()
 | Column | Type | Null % | Range / Sample Values |
 |---|---|---|---|
 | `iso3` | object | 0.0% | ZMB |
-| `location` | object | 0.0% | Central, Copperbelt, Luapula |
-| `dataid` | int64 | 0.0% | 584.0 – 7980700.0 (mean 4302204.7522) |
-| `indicator` | object | 0.0% | Place of delivery: Health facility, Treatment of diarrhea: Either ORS or RHF, Total fertility rate 15-49 |
-| `value` | float64 | 0.0% | 0.0 – 254.0 (mean 39.2798) |
-| `precision` | int64 | 0.0% | 0.0 – 1.0 (mean 0.9243) |
+| `dataid` | int64 | 0.0% | 41515.0 – 834693.0 (mean 483738.1456) |
+| `indicator` | object | 0.0% | Place of delivery: Health facility, Treatment of diarrhea: Either ORS or RHF, Infant mortality rate |
+| `value` | float64 | 0.0% | 0.4 – 729.0 (mean 58.3112) |
+| `precision` | int64 | 0.0% | 0.0 – 1.0 (mean 0.8252) |
 | `dhs_countrycode` | object | 0.0% | ZM |
 | `countryname` | object | 0.0% | Zambia |
-| `surveyyear` | int64 | 0.0% | 1992.0 – 2024.0 (mean 2009.1664) |
-| `surveyid` | object | 0.0% | ZM2013DHS, ZM2018DHS, ZM2024DHS |
-| `indicatorid` | object | 0.0% | RH_DELP_C_DHF, CH_DIAT_C_ORT, FE_FRTR_W_TFR |
-| `indicatororder` | int64 | 0.0% | 11763080.0 – 260321010.0 (mean 100486077.8026) |
+| `surveyyear` | int64 | 0.0% | 1992.0 – 2024.0 (mean 2008.7573) |
+| `surveyid` | object | 0.0% | ZM2018DHS, ZM2024DHS, ZM2007DHS |
+| `indicatorid` | object | 0.0% | RH_DELP_C_DHF, CH_DIAT_C_ORT, CM_ECMR_C_IMR |
+| `indicatororder` | int64 | 0.0% | 11763080.0 – 260321010.0 (mean 96782154.7087) |
 | `indicatortype` | object | 0.0% | I |
-| `characteristicid` | int64 | 0.0% | 456001.0 – 456012.0 (mean 456005.9484) |
-| `characteristicorder` | int64 | 0.0% | 1456001.0 – 1456012.0 (mean 1456006.572) |
-| `characteristiccategory` | object | 0.0% | Region |
-| `characteristiclabel` | object | 0.0% | Central, Copperbelt, Luapula |
-| `byvariableid` | int64 | 0.0% | 0.0 – 631002.0 (mean 21369.8847) |
-| `byvariablelabel` | object | 71.3% |  |
-| `istotal` | int64 | 0.0% | 0.0 – 0.0 (mean 0.0) |
-| `ispreferred` | int64 | 0.0% | 0.0 – 1.0 (mean 0.8698) |
+| `characteristicid` | int64 | 0.0% | 1000.0 – 10000.0 (mean 2747.5728) |
+| `characteristicorder` | int64 | 0.0% | 0.0 – 10000.0 (mean 1941.7476) |
+| `characteristiccategory` | object | 0.0% | Total, Total 15-49 |
+| `characteristiclabel` | object | 0.0% | Total, Total 15-49 |
+| `byvariableid` | int64 | 0.0% | 0.0 – 631002.0 (mean 19529.5583) |
+| `byvariablelabel` | object | 67.5% | 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 0.8155) |
 | `sdrid` | object | 0.0% |  |
-| `regionid` | object | 0.0% |  |
-| `surveyyearlabel` | float64 | 30.1% | 1992.0 – 2024.0 (mean 2009.63) |
+| `surveyyearlabel` | object | 0.0% |  |
 | `surveytype` | object | 0.0% |  |
-| `denominatorweighted` | float64 | 22.7% | 24.0 – 5683.0 (mean 738.317) |
-| `denominatorunweighted` | float64 | 22.7% | 51.0 – 3620.0 (mean 741.9569) |
-| `levelrank` | float64 | 16.6% | 1.0 – 1.0 (mean 1.0) |
+| `denominatorweighted` | float64 | 31.1% | 745.0 – 27859.0 (mean 7003.7183) |
+| `denominatorunweighted` | float64 | 31.1% | 750.0 – 27883.0 (mean 7038.1408) |
+| `cilow` | float64 | 75.2% | 5.3 – 586.0 (mean 100.5471) |
+| `cihigh` | float64 | 75.2% | 6.6 – 872.0 (mean 141.9471) |
 | `esa_source` | object | 0.0% |  |
 | `esa_processed` | object | 0.0% |  |
 
@@ -205,26 +133,26 @@ train.head()
 
 | Column | Min | Max | Mean | Median |
 |---|---|---|---|---|
-| `dataid` | 584.0 | 7980700.0 | 4302204.7522 | 4315680.0 |
-| `value` | 0.0 | 254.0 | 39.2798 | 32.6 |
-| `precision` | 0.0 | 1.0 | 0.9243 | 1.0 |
-| `surveyyear` | 1992.0 | 2024.0 | 2009.1664 | 2007.0 |
-| `indicatororder` | 11763080.0 | 260321010.0 | 100486077.8026 | 94096040.0 |
-| `characteristicid` | 456001.0 | 456012.0 | 456005.9484 | 456006.0 |
-| `characteristicorder` | 1456001.0 | 1456012.0 | 1456006.572 | 1456006.0 |
-| `byvariableid` | 0.0 | 631002.0 | 21369.8847 | 0.0 |
-| `istotal` | 0.0 | 0.0 | 0.0 | 0.0 |
-| `ispreferred` | 0.0 | 1.0 | 0.8698 | 1.0 |
-| `surveyyearlabel` | 1992.0 | 2024.0 | 2009.63 | 2007.0 |
-| `denominatorweighted` | 24.0 | 5683.0 | 738.317 | 615.0 |
-| `denominatorunweighted` | 51.0 | 3620.0 | 741.9569 | 641.0 |
-| `levelrank` | 1.0 | 1.0 | 1.0 | 1.0 |
+| `dataid` | 41515.0 | 834693.0 | 483738.1456 | 546494.0 |
+| `value` | 0.4 | 729.0 | 58.3112 | 42.0 |
+| `precision` | 0.0 | 1.0 | 0.8252 | 1.0 |
+| `surveyyear` | 1992.0 | 2024.0 | 2008.7573 | 2007.0 |
+| `indicatororder` | 11763080.0 | 260321010.0 | 96782154.7087 | 83566070.0 |
+| `characteristicid` | 1000.0 | 10000.0 | 2747.5728 | 1000.0 |
+| `characteristicorder` | 0.0 | 10000.0 | 1941.7476 | 0.0 |
+| `byvariableid` | 0.0 | 631002.0 | 19529.5583 | 0.0 |
+| `istotal` | 1.0 | 1.0 | 1.0 | 1.0 |
+| `ispreferred` | 0.0 | 1.0 | 0.8155 | 1.0 |
+| `denominatorweighted` | 745.0 | 27859.0 | 7003.7183 | 5771.0 |
+| `denominatorunweighted` | 750.0 | 27883.0 | 7038.1408 | 5894.0 |
+| `cilow` | 5.3 | 586.0 | 100.5471 | 63.0 |
+| `cihigh` | 6.6 | 872.0 | 141.9471 | 78.0 |
 
 ---
 
 ## 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: `cilow`, `cihigh`. 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.
+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`. The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.
 
 ---
 
@@ -232,8 +160,8 @@ Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Colu
 
 - 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`, `surveyyearlabel`, `denominatorweighted`, `denominatorunweighted`.
-- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/dhs-subnational-data-for-zambia) for the publisher's own methodology notes and caveats.
+- 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-zambia) for the publisher's own methodology notes and caveats.
 
 ---
 
@@ -241,10 +169,10 @@ Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Colu
 
 ```bibtex
 @dataset{hdx_africa_demographics_zambia,
-  title     = {Zambia - Subnational Demographic and Health Data},
+  title     = {Zambia - National Demographic and Health Data},
   author    = {The DHS Program},
   year      = {2026},
-  url       = {https://data.humdata.org/dataset/dhs-subnational-data-for-zambia},
+  url       = {https://data.humdata.org/dataset/dhs-data-for-zambia},
   note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
 }
 ```