Add README.md

README.md

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 ---
+annotations_creators:
+- no-annotation
+language_creators:
+- found
+language:
+- en
+license: other
+multilinguality:
+- monolingual
+size_categories:
+- n<1K
+source_datasets:
+- original
+task_categories:
+- tabular-classification
+- tabular-regression
+task_ids: []
+tags:
+- africa
+- humanitarian
+- hdx
+- electric-sheep-africa
+- education
+- gender-and-age-disaggregated-data-gadd
+- ken
+pretty_name: "Kenya - Enrolment in Secondary Schools by Level and Sex, 2009 – 2013"
 dataset_info:
-  features:
-  - name: year
-    dtype: int64
-  - name: gender
-    dtype: string
-  - name: form_1
-    dtype: int64
-  - name: form_2
-    dtype: int64
-  - name: form_3
-    dtype: int64
-  - name: form_4
-    dtype: int64
-  - name: esa_source
-    dtype: string
-  - name: esa_processed
-    dtype: string
   splits:
-  - name: train
-    num_bytes: 556
-    num_examples: 8
-  - name: test
-    num_bytes: 139
-    num_examples: 2
-  download_size: 7199
-  dataset_size: 695
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+    - name: train
+      num_examples: 8
+    - name: test
+      num_examples: 2
 ---
+
+# Kenya - Enrolment in Secondary Schools by Level and Sex, 2009 – 2013
+
+**Publisher:** Kenya National Bureau of Statistics (inactive) · **Source:** [HDX](https://data.humdata.org/dataset/enrolment-in-secondary-schools-by-level-and-sex-2009-2013) · **License:** `other-pd-nr` · **Updated:** 2025-07-22
+
+---
+
+## Abstract
+
+The Dataset shows the Enrolment in Secondary Schools by Level and Sex for the period of 2009 – 2013 as reported by the Kenya National Bureau of statistics in the KNBS Economic Survey 2014
+
+Each row in this dataset represents time-series observations. Data was last updated on HDX on 2025-07-22. Geographic scope: **KEN**.
+
+*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
+
+---
+
+## Dataset Characteristics
+
+| | |
+|---|---|
+| **Domain** | Education |
+| **Unit of observation** | Time-series observations |
+| **Rows (total)** | 10 |
+| **Columns** | 8 (5 numeric, 3 categorical, 0 datetime) |
+| **Train split** | 8 rows |
+| **Test split** | 2 rows |
+| **Geographic scope** | KEN |
+| **Publisher** | Kenya National Bureau of Statistics (inactive) |
+| **HDX last updated** | 2025-07-22 |
+
+---
+
+## Variables
+
+**Geographic** — `year` (range 2009.0–2013.0).
+
+**Demographic** — `gender` (Boys, Girls).
+
+**Identifier / Metadata** — `esa_source` (HDX), `esa_processed` (2026-04-07).
+
+**Other** — `form_1` (range 212467.0–327775.0), `form_2` (range 175098.0–288238.0), `form_3` (range 142579.0–267221.0), `form_4` (range 141999.0–244463.0).
+
+---
+
+## Quick Start
+
+```python
+from datasets import load_dataset
+
+ds    = load_dataset("electricsheepafrica/africa-enrolment-in-secondary-schools-by-level-and-sex-2009-2013")
+train = ds["train"].to_pandas()
+test  = ds["test"].to_pandas()
+
+print(train.shape)
+train.head()
+```
+
+---
+
+## Schema
+
+| Column | Type | Null % | Range / Sample Values |
+|---|---|---|---|
+| `year` | int64 | 0.0% | 2009.0 – 2013.0 (mean 2011.0) |
+| `gender` | object | 0.0% | Boys, Girls |
+| `form_1` | int64 | 0.0% | 212467.0 – 327775.0 (mean 261551.1) |
+| `form_2` | int64 | 0.0% | 175098.0 – 288238.0 (mean 233702.3) |
+| `form_3` | int64 | 0.0% | 142579.0 – 267221.0 (mean 207803.1) |
+| `form_4` | int64 | 0.0% | 141999.0 – 244463.0 (mean 188225.8) |
+| `esa_source` | object | 0.0% | HDX |
+| `esa_processed` | object | 0.0% | 2026-04-07 |
+
+---
+
+## Numeric Summary
+
+| Column | Min | Max | Mean | Median |
+|---|---|---|---|---|
+| `year` | 2009.0 | 2013.0 | 2011.0 | 2011.0 |
+| `form_1` | 212467.0 | 327775.0 | 261551.1 | 258140.0 |
+| `form_2` | 175098.0 | 288238.0 | 233702.3 | 235944.0 |
+| `form_3` | 142579.0 | 267221.0 | 207803.1 | 217532.0 |
+| `form_4` | 141999.0 | 244463.0 | 188225.8 | 185481.0 |
+
+---
+
+## 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`. 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 Kenya National Bureau of Statistics (inactive) and has not been independently validated by ESA.
+- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
+- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/enrolment-in-secondary-schools-by-level-and-sex-2009-2013) for the publisher's own methodology notes and caveats.
+
+---
+
+## Citation
+
+```bibtex
+@dataset{hdx_africa_enrolment_in_secondary_schools_by_level_and_sex_2009_2013,
+  title     = {Kenya - Enrolment in Secondary Schools by Level and Sex, 2009 – 2013},
+  author    = {Kenya National Bureau of Statistics (inactive)},
+  year      = {2025},
+  url       = {https://data.humdata.org/dataset/enrolment-in-secondary-schools-by-level-and-sex-2009-2013},
+  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
+}
+```
+
+---
+
+*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*