electricsheepasia/asia-population-iran-islamic-republic-of-administrative

Iran (Islamic Republic of) administrative levels 0-2 population statistics

Publisher: OCHA Middle East and North Africa (ROMENA) · Source: HDX · License: hdx-other · Updated: 2024-06-13

Abstract

Iran (Islamic Republic of) administrative levels 0 (country), 1 (province, ostān), and 2 (district, baxš) population statistics

Each row in this dataset represents geolocated point observations. Data was last updated on HDX on 2024-06-13. Geographic scope: IRN.

Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).

Dataset Characteristics

Variables

Geographic — population_2011 (range 5263.0–8150000.0), population_2016 (range 7402.0–8737510.0).

Identifier / Metadata — adm0_pcode (IR), adm1_pcode (IR006, IR024, IR015), adm2_pcode (IR001001, IR001002, IR001003), unhcr_pcode (20IRN001001, 20IRN001002, 20IRN001003), esa_source (HDX) and 1 others.

Other — adm0_en (Iran (Islamic Republic of)), adm1_en (Fars, Razavi Khorasan, Khuzestan), adm2_en (Eshtehard, Fardis, Karaj).

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-population-all")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

Schema

Numeric Summary

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. 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 Middle East and North Africa (ROMENA) 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 for the publisher's own methodology notes and caveats.

Citation

@dataset{hdx_asia_population_all,
  title     = {Iran (Islamic Republic of) administrative levels 0-2 population statistics},
  author    = {OCHA Middle East and North Africa (ROMENA)},
  year      = {2024},
  url       = {https://data.humdata.org/dataset/iran-islamic-republic-of-administrative-levels-0-2-population-statistics},
  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.