electricsheepasia/asia-displacement-number-of-tdps

Number of TDPs

Publisher: OCHA Pakistan · Source: HDX · License: other-pd-nr · Updated: 2023-03-03

Abstract

Number of Temporarily Displaced People (TDPs) from FATA region registered by UNHCR verified through National Database & Registration Authority (NADRA)

Each row in this dataset represents tabular records. Temporal coverage is indicated by the unnamed_4, unnamed_6 column(s). Geographic scope: PAK.

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

Dataset Characteristics

Variables

Geographic — by_host_areas (KP, FATA, Province).

Identifier / Metadata — unnamed_1 (Kurram, District, Hangu), unnamed_2 (range 376.0–277811.0), unnamed_3 (UNHCR,FDMA, WFP, TDP Families in Camps, 1154), unnamed_4, unnamed_5 (UNHCR,FDMA, WFP, UNHCR registration data verified through National Database & Registration Authority (NADRA), Source (who is providing you with this information)) and 4 others.

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-displacement-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. 3 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 OCHA Pakistan 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: unnamed_2, unnamed_3, unnamed_4, unnamed_6, unnamed_7.
• —Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

Citation

@dataset{hdx_asia_displacement_all,
  title     = {Number of TDPs},
  author    = {OCHA Pakistan},
  year      = {2023},
  url       = {https://data.humdata.org/dataset/number-of-tdps},
  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.