Add README.md

README.md

@@ -1,100 +1,187 @@
 ---
+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
+- food-security
+- dji
+pretty_name: "Djibouti Current Situation FEWS NET Acute Food Insecurity Classifications Data"
 dataset_info:
-  features:
-  - name: source_organization
-    dtype: string
-  - name: source_document
-    dtype: string
-  - name: country
-    dtype: string
-  - name: country_code
-    dtype: string
-  - name: geographic_group
-    dtype: string
-  - name: fewsnet_region
-    dtype: string
-  - name: geographic_unit_full_name
-    dtype: string
-  - name: geographic_unit_name
-    dtype: string
-  - name: unit_type
-    dtype: string
-  - name: fnid
-    dtype: string
-  - name: classification_scale
-    dtype: string
-  - name: scenario_name
-    dtype: string
-  - name: preference_rating
-    dtype: int64
-  - name: is_allowing_for_assistance
-    dtype: bool
-  - name: projection_start
-    dtype: timestamp[ns]
-  - name: projection_end
-    dtype: timestamp[ns]
-  - name: status
-    dtype: string
-  - name: value
-    dtype: float64
-  - name: description
-    dtype: string
-  - name: id
-    dtype: int64
-  - name: datacollectionperiod
-    dtype: int64
-  - name: datacollection
-    dtype: int64
-  - name: scenario
-    dtype: string
-  - name: geographic_unit
-    dtype: int64
-  - name: datasourceorganization
-    dtype: int64
-  - name: datasourcedocument
-    dtype: int64
-  - name: dataseries
-    dtype: int64
-  - name: dataseries_name
-    dtype: string
-  - name: specialization_type
-    dtype: string
-  - name: dataseries_specialization_type
-    dtype: string
-  - name: data_usage_policy
-    dtype: string
-  - name: created
-    dtype: timestamp[ns]
-  - name: modified
-    dtype: timestamp[ns]
-  - name: status_changed
-    dtype: timestamp[ns]
-  - name: collection_status
-    dtype: string
-  - name: collection_status_changed
-    dtype: timestamp[ns]
-  - name: collection_schedule
-    dtype: string
-  - name: reporting_date
-    dtype: timestamp[ns]
-  - name: esa_source
-    dtype: string
-  - name: esa_processed
-    dtype: string
   splits:
-  - name: train
-    num_bytes: 199647
-    num_examples: 320
-  - name: test
-    num_bytes: 50586
-    num_examples: 81
-  download_size: 49406
-  dataset_size: 250233
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+    - name: train
+      num_examples: 320
+    - name: test
+      num_examples: 80
 ---
+
+# Djibouti Current Situation FEWS NET Acute Food Insecurity Classifications Data
+
+**Publisher:** FEWS NET · **Source:** [HDX](https://data.humdata.org/dataset/djibouti_current_situation_fewsnet_ipc_classification) · **License:** `cc-by` · **Updated:** 2026-04-01
+
+---
+
+## Abstract
+
+Djibouti Current Situation FEWS NET Acute Food Insecurity Classifications Data from 2011
+
+Each row in this dataset represents first-level administrative unit observations. Temporal coverage is indicated by the `projection_start`, `projection_end` column(s). Geographic scope: **DJI**.
+
+*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
+
+---
+
+## Dataset Characteristics
+
+| | |
+|---|---|
+| **Domain** | Food security and nutrition |
+| **Unit of observation** | First-level administrative unit observations |
+| **Rows (total)** | 401 |
+| **Columns** | 40 (9 numeric, 23 categorical, 7 datetime) |
+| **Train split** | 320 rows |
+| **Test split** | 80 rows |
+| **Geographic scope** | DJI |
+| **Publisher** | FEWS NET |
+| **HDX last updated** | 2026-04-01 |
+
+---
+
+## Variables
+
+**Geographic** — `country` (Djibouti), `country_code` (DJ), `fewsnet_region` (East Africa), `unit_type` (fsc_admin_lhz, fsc_lhz), `specialization_type` and 2 others.
+
+**Temporal** — `datacollectionperiod` (range 159830.0–159881.0), `reporting_date`.
+
+**Outcome / Measurement** — `value` (range 1.0–3.0).
+
+**Identifier / Metadata** — `source_organization` (FEWS NET), `source_document` (Food Security Outlook, Djibouti), `geographic_unit_full_name` (Central Pastoral - Highland, Balha, Tadjourah, Djibouti, Southeast Pastoral - Border, Ali Sabieh, Ali Sabieh, Djibouti, Market Gardening, Dikhil, Dikhil, Djibouti), `geographic_unit_name` (Central Pastoral - Lowland, Market Gardening, Southeast Pastoral - Roadside), `fnid` (DJ2012C305012B, DJ2012C301013B, DJ2012C3020204) and 8 others.
+
+**Other** — `geographic_group` (Eastern Africa), `classification_scale`, `is_allowing_for_assistance`, `projection_start`, `projection_end` and 12 others.
+
+---
+
+## Quick Start
+
+```python
+from datasets import load_dataset
+
+ds    = load_dataset("electricsheepafrica/africa-djibouti-current-situation-fewsnet-ipc-classification")
+train = ds["train"].to_pandas()
+test  = ds["test"].to_pandas()
+
+print(train.shape)
+train.head()
+```
+
+---
+
+## Schema
+
+| Column | Type | Null % | Range / Sample Values |
+|---|---|---|---|
+| `source_organization` | object | 0.0% | FEWS NET |
+| `source_document` | object | 0.0% | Food Security Outlook, Djibouti |
+| `country` | object | 0.0% | Djibouti |
+| `country_code` | object | 0.0% | DJ |
+| `geographic_group` | object | 0.0% | Eastern Africa |
+| `fewsnet_region` | object | 0.0% | East Africa |
+| `geographic_unit_full_name` | object | 0.0% | Central Pastoral - Highland, Balha, Tadjourah, Djibouti, Southeast Pastoral - Border, Ali Sabieh, Ali Sabieh, Djibouti, Market Gardening, Dikhil, Dikhil, Djibouti |
+| `geographic_unit_name` | object | 0.0% | Central Pastoral - Lowland, Market Gardening, Southeast Pastoral - Roadside |
+| `unit_type` | object | 0.0% | fsc_admin_lhz, fsc_lhz |
+| `fnid` | object | 0.0% | DJ2012C305012B, DJ2012C301013B, DJ2012C3020204 |
+| `classification_scale` | object | 0.0% |  |
+| `scenario_name` | object | 0.0% |  |
+| `preference_rating` | int64 | 0.0% | 90.0 – 90.0 (mean 90.0) |
+| `is_allowing_for_assistance` | bool | 0.0% |  |
+| `projection_start` | datetime64[ns] | 0.0% |  |
+| `projection_end` | datetime64[ns] | 0.0% |  |
+| `status` | object | 0.0% |  |
+| `value` | float64 | 11.5% | 1.0 – 3.0 (mean 2.0592) |
+| `description` | object | 11.5% |  |
+| `id` | int64 | 0.0% | 24538359.0 – 24539559.0 (mean 24538959.0) |
+| `datacollectionperiod` | int64 | 0.0% | 159830.0 – 159881.0 (mean 159862.7007) |
+| `datacollection` | int64 | 0.0% | 168806.0 – 168823.0 (mean 168816.9002) |
+| `scenario` | object | 0.0% |  |
+| `geographic_unit` | int64 | 0.0% | 20943.0 – 20981.0 (mean 20963.1172) |
+| `datasourceorganization` | int64 | 0.0% | 1.0 – 1.0 (mean 1.0) |
+| `datasourcedocument` | int64 | 0.0% | 6621.0 – 6621.0 (mean 6621.0) |
+| `dataseries` | int64 | 0.0% | 6516268.0 – 6516529.0 (mean 6516395.8953) |
+| `dataseries_name` | object | 0.0% |  |
+| `specialization_type` | object | 0.0% |  |
+| `dataseries_specialization_type` | object | 0.0% |  |
+| `data_usage_policy` | object | 0.0% |  |
+| `created` | datetime64[ns] | 0.0% |  |
+| `modified` | datetime64[ns] | 0.0% |  |
+| `status_changed` | datetime64[ns] | 0.0% |  |
+| `collection_status` | object | 0.0% |  |
+| `collection_status_changed` | datetime64[ns] | 0.0% |  |
+| `collection_schedule` | object | 0.0% |  |
+| `reporting_date` | datetime64[ns] | 0.0% |  |
+| `esa_source` | object | 0.0% |  |
+| `esa_processed` | object | 0.0% |  |
+
+---
+
+## Numeric Summary
+
+| Column | Min | Max | Mean | Median |
+|---|---|---|---|---|
+| `preference_rating` | 90.0 | 90.0 | 90.0 | 90.0 |
+| `value` | 1.0 | 3.0 | 2.0592 | 2.0 |
+| `id` | 24538359.0 | 24539559.0 | 24538959.0 | 24538959.0 |
+| `datacollectionperiod` | 159830.0 | 159881.0 | 159862.7007 | 159863.0 |
+| `datacollection` | 168806.0 | 168823.0 | 168816.9002 | 168817.0 |
+| `geographic_unit` | 20943.0 | 20981.0 | 20963.1172 | 20963.0 |
+| `datasourceorganization` | 1.0 | 1.0 | 1.0 | 1.0 |
+| `datasourcedocument` | 6621.0 | 6621.0 | 6621.0 | 6621.0 |
+| `dataseries` | 6516268.0 | 6516529.0 | 6516395.8953 | 6516396.0 |
+
+---
+
+## 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`. 3 column(s) with >80% missing values were removed: `pct_phase3`, `pct_phase4`, `pct_phase5`. 7 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 FEWS NET 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/djibouti_current_situation_fewsnet_ipc_classification) for the publisher's own methodology notes and caveats.
+
+---
+
+## Citation
+
+```bibtex
+@dataset{hdx_africa_djibouti_current_situation_fewsnet_ipc_classification,
+  title     = {Djibouti Current Situation FEWS NET Acute Food Insecurity Classifications Data},
+  author    = {FEWS NET},
+  year      = {2026},
+  url       = {https://data.humdata.org/dataset/djibouti_current_situation_fewsnet_ipc_classification},
+  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.*