Add README.md

README.md

@@ -1,54 +1,162 @@
 ---
+annotations_creators:
+- no-annotation
+language_creators:
+- found
+language:
+- en
+license: cc-by-4.0
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- tabular-regression
+- other
+task_ids: []
+tags:
+- africa
+- humanitarian
+- hdx
+- electric-sheep-africa
+- eastern-africa
+- economics
+- food-security
+- indicators
+- markets
+- dji
+pretty_name: "Djibouti Weekly FEWS NET Staple Food Price Data"
 dataset_info:
-  features:
-  - name: country
-    dtype: string
-  - name: fnid
-    dtype: string
-  - name: market
-    dtype: string
-  - name: longitude
-    dtype: float64
-  - name: latitude
-    dtype: float64
-  - name: cpcv2
-    dtype: string
-  - name: product
-    dtype: string
-  - name: source_document
-    dtype: string
-  - name: period_date
-    dtype: timestamp[ns]
-  - name: price_type
-    dtype: string
-  - name: product_source
-    dtype: string
-  - name: unit
-    dtype: string
-  - name: unit_type
-    dtype: string
-  - name: currency
-    dtype: string
-  - name: value
-    dtype: float64
-  - name: esa_source
-    dtype: string
-  - name: esa_processed
-    dtype: string
   splits:
-  - name: train
-    num_bytes: 199183
-    num_examples: 852
-  - name: test
-    num_bytes: 49804
-    num_examples: 213
-  download_size: 21773
-  dataset_size: 248987
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+    - name: train
+      num_examples: 852
+    - name: test
+      num_examples: 213
 ---
+
+# Djibouti Weekly FEWS NET Staple Food Price Data
+
+**Publisher:** FEWS NET · **Source:** [HDX](https://data.humdata.org/dataset/fewsnet_staple_food_price_data_for_djibouti_weekly_269) · **License:** `cc-by` · **Updated:** 2026-04-01
+
+---
+
+## Abstract
+
+Djibouti Weekly staple food price data collected by FEWS NET since 2004.
+
+Each row in this dataset represents country-level aggregates. Temporal coverage is indicated by the `period_date` 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** | Country-level aggregates |
+| **Rows (total)** | 1,065 |
+| **Columns** | 17 (3 numeric, 13 categorical, 1 datetime) |
+| **Train split** | 852 rows |
+| **Test split** | 213 rows |
+| **Geographic scope** | DJI |
+| **Publisher** | FEWS NET |
+| **HDX last updated** | 2026-04-01 |
+
+---
+
+## Variables
+
+**Geographic** — `country` (Djibouti), `longitude` (range 43.1485–43.1485), `latitude` (range 11.59–11.59), `price_type` (Retail), `unit_type` (Weight, Volume) and 1 others.
+
+**Temporal** — `period_date`.
+
+**Outcome / Measurement** — `value` (range 80.0–405.0).
+
+**Identifier / Metadata** — `fnid` (DJ0000M005), `source_document` (Famine Early Warning Systems Network (FEWS NET), Djibouti, Price), `product_source` (Local, Import), `esa_source`, `esa_processed`.
+
+**Other** — `market` (Djibouti City), `cpcv2` (P33341AA, P23161AA, P23110AA), `product` (Kerosene, Rice (Milled), Wheat Flour), `unit` (kg, L).
+
+---
+
+## Quick Start
+
+```python
+from datasets import load_dataset
+
+ds    = load_dataset("electricsheepafrica/africa-fewsnet-staple-food-price-data-for-djibouti-weekly-269")
+train = ds["train"].to_pandas()
+test  = ds["test"].to_pandas()
+
+print(train.shape)
+train.head()
+```
+
+---
+
+## Schema
+
+| Column | Type | Null % | Range / Sample Values |
+|---|---|---|---|
+| `country` | object | 0.0% | Djibouti |
+| `fnid` | object | 0.0% | DJ0000M005 |
+| `market` | object | 0.0% | Djibouti City |
+| `longitude` | float64 | 0.0% | 43.1485 – 43.1485 (mean 43.1485) |
+| `latitude` | float64 | 0.0% | 11.59 – 11.59 (mean 11.59) |
+| `cpcv2` | object | 0.0% | P33341AA, P23161AA, P23110AA |
+| `product` | object | 0.0% | Kerosene, Rice (Milled), Wheat Flour |
+| `source_document` | object | 0.0% | Famine Early Warning Systems Network (FEWS NET), Djibouti, Price |
+| `period_date` | datetime64[ns] | 0.0% |  |
+| `price_type` | object | 0.0% | Retail |
+| `product_source` | object | 0.0% | Local, Import |
+| `unit` | object | 0.0% | kg, L |
+| `unit_type` | object | 0.0% | Weight, Volume |
+| `currency` | object | 0.0% |  |
+| `value` | float64 | 5.2% | 80.0 – 405.0 (mean 148.407) |
+| `esa_source` | object | 0.0% |  |
+| `esa_processed` | object | 0.0% |  |
+
+---
+
+## Numeric Summary
+
+| Column | Min | Max | Mean | Median |
+|---|---|---|---|---|
+| `longitude` | 43.1485 | 43.1485 | 43.1485 | 43.1485 |
+| `latitude` | 11.59 | 11.59 | 11.59 | 11.59 |
+| `value` | 80.0 | 405.0 | 148.407 | 140.0 |
+
+---
+
+## 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`. 1 column(s) with >80% missing values were removed: `admin_1`. 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 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/fewsnet_staple_food_price_data_for_djibouti_weekly_269) for the publisher's own methodology notes and caveats.
+
+---
+
+## Citation
+
+```bibtex
+@dataset{hdx_africa_fewsnet_staple_food_price_data_for_djibouti_weekly_269,
+  title     = {Djibouti Weekly FEWS NET Staple Food Price Data},
+  author    = {FEWS NET},
+  year      = {2026},
+  url       = {https://data.humdata.org/dataset/fewsnet_staple_food_price_data_for_djibouti_weekly_269},
+  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.*