Add README.md

README.md

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 ---
+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-classification
+- tabular-regression
+task_ids: []
+tags:
+- africa
+- humanitarian
+- hdx
+- electric-sheep-africa
+- food-security
+- indicators
+- nutrition
+- tza
+pretty_name: "United Republic of Tanzania - Food Security and Nutrition Indicators"
 dataset_info:
-  features:
-  - name: iso3
-    dtype: string
-  - name: startdate
-    dtype: timestamp[ns]
-  - name: enddate
-    dtype: timestamp[ns]
-  - name: area_code
-    dtype: int64
-  - name: area_code_m49
-    dtype: string
-  - name: area
-    dtype: string
-  - name: item_code
-    dtype: string
-  - name: item
-    dtype: string
-  - name: element_code
-    dtype: int64
-  - name: element
-    dtype: string
-  - name: year_code
-    dtype: int64
-  - name: year
-    dtype: int64
-  - name: unit
-    dtype: string
-  - name: value
-    dtype: float64
-  - name: flag
-    dtype: string
-  - name: note
-    dtype: string
-  - name: esa_source
-    dtype: string
-  - name: esa_processed
-    dtype: string
   splits:
-  - name: train
-    num_bytes: 228785
-    num_examples: 893
-  - name: test
-    num_bytes: 57939
-    num_examples: 224
-  download_size: 31444
-  dataset_size: 286724
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+    - name: train
+      num_examples: 893
+    - name: test
+      num_examples: 223
 ---
+
+# United Republic of Tanzania - Food Security and Nutrition Indicators
+
+**Publisher:** Food and Agriculture Organization (FAO) of the United Nations · **Source:** [HDX](https://data.humdata.org/dataset/faostat-food-security-indicators-for-united-republic-of-tanzania) · **License:** `cc-by-igo` · **Updated:** 2026-04-06
+
+---
+
+## Abstract
+
+Food Security and Nutrition Indicators for United Republic of Tanzania.
+
+Contains data from the FAOSTAT [bulk data service](https://fenixservices.fao.org/faostat/static/bulkdownloads/datasets_E.json).
+
+Each row in this dataset represents country-level aggregates. Temporal coverage is indicated by the `startdate`, `enddate` column(s). Geographic scope: **TZA**.
+
+*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)** | 1,117 |
+| **Columns** | 18 (5 numeric, 11 categorical, 2 datetime) |
+| **Train split** | 893 rows |
+| **Test split** | 223 rows |
+| **Geographic scope** | TZA |
+| **Publisher** | Food and Agriculture Organization (FAO) of the United Nations |
+| **HDX last updated** | 2026-04-06 |
+
+---
+
+## Variables
+
+**Geographic** — `iso3` (TZA), `year_code` (range 2000.0–20222024.0), `year` (range 2000.0–2024.0).
+
+**Temporal** — `startdate`, `enddate`.
+
+**Outcome / Measurement** — `value` (range -0.9–3713.0).
+
+**Identifier / Metadata** — `area_code` (range 215.0–215.0), `area_code_m49` ('834), `item_code` (210071M, 210091F, 210081F), `element_code` (range 6121.0–61322.0), `esa_source` (HDX) and 1 others.
+
+**Other** — `area` (United Republic of Tanzania), `item` (Number of severely food insecure male adults (million) (3-year average), Prevalence of moderate or severe food insecurity in the female adult population (percent) (3-year average), Number of moderately or severely food insecure female adults (million) (3-year average)), `element` (Value, Confidence interval: Lower bound, Confidence interval: Upper bound), `unit` (%, million No, kcal/cap/d), `flag` (E, X) and 1 others.
+
+---
+
+## Quick Start
+
+```python
+from datasets import load_dataset
+
+ds    = load_dataset("electricsheepafrica/africa-faostat-food-security-indicators-for-united-republic-of-tanzania")
+train = ds["train"].to_pandas()
+test  = ds["test"].to_pandas()
+
+print(train.shape)
+train.head()
+```
+
+---
+
+## Schema
+
+| Column | Type | Null % | Range / Sample Values |
+|---|---|---|---|
+| `iso3` | object | 0.0% | TZA |
+| `startdate` | datetime64[ns] | 0.0% |  |
+| `enddate` | datetime64[ns] | 0.0% |  |
+| `area_code` | int64 | 0.0% | 215.0 – 215.0 (mean 215.0) |
+| `area_code_m49` | object | 0.0% | '834 |
+| `area` | object | 0.0% | United Republic of Tanzania |
+| `item_code` | object | 0.0% | 210071M, 210091F, 210081F |
+| `item` | object | 0.0% | Number of severely food insecure male adults (million) (3-year average), Prevalence of moderate or severe food insecurity in the female adult population (percent) (3-year average), Number of moderately or severely food insecure female adults (million) (3-year average) |
+| `element_code` | int64 | 0.0% | 6121.0 – 61322.0 (mean 16788.9221) |
+| `element` | object | 0.0% | Value, Confidence interval: Lower bound, Confidence interval: Upper bound |
+| `year_code` | int64 | 0.0% | 2000.0 – 20222024.0 (mean 10211298.0045) |
+| `year` | int64 | 0.0% | 2000.0 – 2024.0 (mean 2014.2086) |
+| `unit` | object | 2.0% | %, million No, kcal/cap/d |
+| `value` | float64 | 0.0% | -0.9 – 3713.0 (mean 262.0155) |
+| `flag` | object | 0.0% | E, X |
+| `note` | object | 71.0% | Official estimate integrated with FAO data |
+| `esa_source` | object | 0.0% | HDX |
+| `esa_processed` | object | 0.0% |  |
+
+---
+
+## Numeric Summary
+
+| Column | Min | Max | Mean | Median |
+|---|---|---|---|---|
+| `area_code` | 215.0 | 215.0 | 215.0 | 215.0 |
+| `element_code` | 6121.0 | 61322.0 | 16788.9221 | 6128.0 |
+| `year_code` | 2000.0 | 20222024.0 | 10211298.0045 | 20002002.0 |
+| `year` | 2000.0 | 2024.0 | 2014.2086 | 2016.0 |
+| `value` | -0.9 | 3713.0 | 262.0155 | 16.8 |
+
+---
+
+## 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 Food and Agriculture Organization (FAO) of the United Nations 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: `note`.
+- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/faostat-food-security-indicators-for-united-republic-of-tanzania) for the publisher's own methodology notes and caveats.
+
+---
+
+## Citation
+
+```bibtex
+@dataset{hdx_africa_faostat_food_security_indicators_for_united_republic_of_tanzania,
+  title     = {United Republic of Tanzania - Food Security and Nutrition Indicators},
+  author    = {Food and Agriculture Organization (FAO) of the United Nations},
+  year      = {2026},
+  url       = {https://data.humdata.org/dataset/faostat-food-security-indicators-for-united-republic-of-tanzania},
+  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.*