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africa-faostat-food-security-indicators-for-united-republic-of-tanzania

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metadata 
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:
  splits:
    - 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 · 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.

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.

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 

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 for the publisher's own methodology notes and caveats.

Citation 

@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 — Africa's ML dataset infrastructure. Lagos, Nigeria.