electricsheepafrica/africa-chad-uneca-population-and-migration

CHAD - Population and migration indicators, UNECA

Publisher: United Nations Economic Commission for Africa · Source: HDX · License: cc-by-igo · Updated: 2024-09-13

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Abstract

This dataset contains many indicators related to population and migration such as Average annual population growth rate, Population 15-19 , Annual rate of change of the migrant stock, International migrant stock at mid-year, etc. The whole list and their description can be find in this link https://bit.ly/2ODhFQh

Each row in this dataset represents tabular records. Data was last updated on HDX on 2024-09-13. Geographic scope: TCD.

Curated into ML-ready Parquet format by Electric Sheep Africa.

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Dataset Characteristics

Domain	Demographics and population
Unit of observation	Tabular records
Rows (total)	45
Columns	51 (0 numeric, 51 categorical, 0 datetime)
Train split	36 rows
Test split	9 rows
Geographic scope	TCD
Publisher	United Nations Economic Commission for Africa
HDX last updated	2024-09-13

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Variables

Identifier / Metadata — esa_source, esa_processed.

Other — indicator (Average annual population growth rate - Total (%), Life expectancy at birth - Total (years), Mid-year population - Female (thousands)), 1970 (2.2, 8.2, 135.0), 1971 (2.3, 8.2, 138.4), 1972 (2.4, 8.2, 141.4), 1973 (2.4, 8.2, 144.1) and 44 others.

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-chad-uneca-population-and-migration")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

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Schema

Column	Type	Null %	Range / Sample Values
indicator	object	0.0%	Average annual population growth rate - Total (%), Life expectancy at birth - Total (years), Mid-year population - Female (thousands)
1970	object	51.1%	2.2, 8.2, 135.0
1971	object	51.1%	2.3, 8.2, 138.4
1972	object	51.1%	2.4, 8.2, 141.4
1973	object	51.1%	2.4, 8.2, 144.1
1974	object	51.1%	2.3, 8.2, 146.3
1975	object	51.1%	2.1, 5.7, 148.0
1976	object	51.1%	2.0, 5.7, 150.9
1977	object	51.1%	1.9, 5.7, 153.3
1978	object	51.1%	1.9, 5.7, 155.2
1979	object	51.1%
1980	object	51.1%
1981	object	51.1%
1982	object	51.1%
1983	object	51.1%
1984	object	51.1%
1985	object	51.1%
1986	object	51.1%
1987	object	51.1%
1988	object	51.1%
1989	object	51.1%
1990	object	11.1%
1991	object	51.1%
1992	object	51.1%
1993	object	51.1%
1994	object	51.1%
1995	object	11.1%
1996	object	51.1%
1997	object	51.1%
1998	object	51.1%
1999	object	51.1%
2000	object	2.2%
2001	object	42.2%
2002	object	42.2%
2003	object	42.2%
2004	object	42.2%
2005	object	0.0%
2006	object	42.2%
2007	object	42.2%
2008	object	42.2%
2009	object	42.2%
2010	object	0.0%
2011	object	42.2%
2012	object	42.2%
2013	object	44.4%
2014	object	44.4%
2015	object	4.4%
2016	object	46.7%
2017	object	28.9%
esa_source	object	0.0%
esa_processed	object	0.0%

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Numeric Summary

Column	Min	Max	Mean	Median
No numeric columns.

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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.

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Limitations

• Data originates from United Nations Economic Commission for Africa 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: 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977....
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_africa_chad_uneca_population_and_migration,
  title     = {CHAD - Population and migration indicators, UNECA},
  author    = {United Nations Economic Commission for Africa},
  year      = {2024},
  url       = {https://data.humdata.org/dataset/chad-uneca-population-and-migration},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

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Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.