Add README.md

README.md

@@ -1,43 +1,161 @@
 ---
+annotations_creators:
+- no-annotation
+language_creators:
+- found
+language:
+- en
+license: cc-by-4.0
+multilinguality:
+- monolingual
+size_categories:
+- n<1K
+source_datasets:
+- original
+task_categories:
+- tabular-classification
+- tabular-regression
+task_ids: []
+tags:
+- africa
+- humanitarian
+- hdx
+- electric-sheep-africa
+- covid-19
+- funding
+- humanitarian-financial-tracking-service-fts
+- lby
+pretty_name: "Libya - Requirements and Funding Data"
 dataset_info:
-  features:
-  - name: countrycode
-    dtype: string
-  - name: id
-    dtype: float64
-  - name: name
-    dtype: string
-  - name: code
-    dtype: string
-  - name: typeid
-    dtype: float64
-  - name: typename
-    dtype: string
-  - name: startdate
-    dtype: timestamp[ns]
-  - name: enddate
-    dtype: timestamp[ns]
-  - name: year
-    dtype: int64
-  - name: requirements
-    dtype: float64
-  - name: funding
-    dtype: int64
-  - name: percentfunded
-    dtype: float64
-  - name: esa_source
-    dtype: string
-  - name: esa_processed
-    dtype: string
   splits:
-  - name: train
-    num_bytes: 4159
-    num_examples: 28
-  download_size: 7231
-  dataset_size: 4159
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+    - name: train
+      num_examples: 28
+    - name: test
+      num_examples: 7
 ---
+
+# Libya - Requirements and Funding Data
+
+**Publisher:** OCHA Financial Tracking System (FTS) · **Source:** [HDX](https://data.humdata.org/dataset/lby-requirements-and-funding-data) · **License:** `cc-by-igo` · **Updated:** 2026-04-03
+
+---
+
+## Abstract
+
+FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's [Financial Tracking Service](https://fts.unocha.org/) and is encoded as utf-8.
+
+Each row in this dataset represents country-level aggregates. Temporal coverage is indicated by the `startdate`, `enddate` column(s). Geographic scope: **LBY**.
+
+*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
+
+---
+
+## Dataset Characteristics
+
+| | |
+|---|---|
+| **Domain** | Humanitarian and development data |
+| **Unit of observation** | Country-level aggregates |
+| **Rows (total)** | 35 |
+| **Columns** | 14 (6 numeric, 6 categorical, 2 datetime) |
+| **Train split** | 28 rows |
+| **Test split** | 7 rows |
+| **Geographic scope** | LBY |
+| **Publisher** | OCHA Financial Tracking System (FTS) |
+| **HDX last updated** | 2026-04-03 |
+
+---
+
+## Variables
+
+**Geographic** — `countrycode` (LBY), `typeid` (range 4.0–111.0), `typename` (Humanitarian response plan, Regional response plan, Flash appeal), `year` (range 2005.0–2027.0).
+
+**Temporal** — `startdate`, `enddate`.
+
+**Outcome / Measurement** — `percentfunded` (range 5.0–128.0).
+
+**Identifier / Metadata** — `id` (range 365.0–1523.0), `name` (Not specified, Sudan Emergency: Regional Refugee Response Plan 2026, Sudan Emergency: Regional Refugee Response Plan 2025), `code` (RREG26a, RRSDN25, FLBY24), `esa_source` (HDX), `esa_processed` (2026-04-04).
+
+**Other** — `requirements` (range 10676371.0–312740102.0), `funding` (range 60976.0–150268390.0).
+
+---
+
+## Quick Start
+
+```python
+from datasets import load_dataset
+
+ds    = load_dataset("electricsheepafrica/africa-lby-requirements-and-funding-data")
+train = ds["train"].to_pandas()
+test  = ds["test"].to_pandas()
+
+print(train.shape)
+train.head()
+```
+
+---
+
+## Schema
+
+| Column | Type | Null % | Range / Sample Values |
+|---|---|---|---|
+| `countrycode` | object | 0.0% | LBY |
+| `id` | float64 | 57.1% | 365.0 – 1523.0 (mean 867.8667) |
+| `name` | object | 0.0% | Not specified, Sudan Emergency: Regional Refugee Response Plan 2026, Sudan Emergency: Regional Refugee Response Plan 2025 |
+| `code` | object | 57.1% | RREG26a, RRSDN25, FLBY24 |
+| `typeid` | float64 | 57.1% | 4.0 – 111.0 (mean 32.8) |
+| `typename` | object | 57.1% | Humanitarian response plan, Regional response plan, Flash appeal |
+| `startdate` | datetime64[ns] | 57.1% |  |
+| `enddate` | datetime64[ns] | 57.1% |  |
+| `year` | int64 | 0.0% | 2005.0 – 2027.0 (mean 2018.3429) |
+| `requirements` | float64 | 60.0% | 10676371.0 – 312740102.0 (mean 114052953.4286) |
+| `funding` | int64 | 0.0% | 60976.0 – 150268390.0 (mean 44350035.7714) |
+| `percentfunded` | float64 | 60.0% | 5.0 – 128.0 (mean 62.6429) |
+| `esa_source` | object | 0.0% | HDX |
+| `esa_processed` | object | 0.0% | 2026-04-04 |
+
+---
+
+## Numeric Summary
+
+| Column | Min | Max | Mean | Median |
+|---|---|---|---|---|
+| `id` | 365.0 | 1523.0 | 867.8667 | 931.0 |
+| `typeid` | 4.0 | 111.0 | 32.8 | 5.0 |
+| `year` | 2005.0 | 2027.0 | 2018.3429 | 2019.0 |
+| `requirements` | 10676371.0 | 312740102.0 | 114052953.4286 | 110215636.5 |
+| `funding` | 60976.0 | 150268390.0 | 44350035.7714 | 39729359.0 |
+| `percentfunded` | 5.0 | 128.0 | 62.6429 | 61.5 |
+
+---
+
+## 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) 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 OCHA Financial Tracking System (FTS) 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: `id`, `code`, `typeid`, `typename`, `startdate`, `enddate`, `requirements`, `percentfunded`.
+- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/lby-requirements-and-funding-data) for the publisher's own methodology notes and caveats.
+
+---
+
+## Citation
+
+```bibtex
+@dataset{hdx_africa_lby_requirements_and_funding_data,
+  title     = {Libya - Requirements and Funding Data},
+  author    = {OCHA Financial Tracking System (FTS)},
+  year      = {2026},
+  url       = {https://data.humdata.org/dataset/lby-requirements-and-funding-data},
+  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.*