Datasets:
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- baseline-population
- migration
- caf
pretty_name: CENTRAL AFRICAN REPUBLIC - Population and migration indicators, UNECA
dataset_info:
splits:
- name: train
num_examples: 33
- name: test
num_examples: 8
CENTRAL AFRICAN REPUBLIC - Population and migration indicators, UNECA
Publisher: United Nations Economic Commission for Africa · Source: HDX · License: cc-by-igo · Updated: 2024-09-13
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: CAF.
Curated into ML-ready Parquet format by Electric Sheep Africa.
Dataset Characteristics
| Domain | Demographics and population |
| Unit of observation | Tabular records |
| Rows (total) | 42 |
| Columns | 51 (15 numeric, 36 categorical, 0 datetime) |
| Train split | 33 rows |
| Test split | 8 rows |
| Geographic scope | CAF |
| Publisher | United Nations Economic Commission for Africa |
| HDX last updated | 2024-09-13 |
Variables
Identifier / Metadata — esa_source, esa_processed.
Other — indicator (Average annual population growth rate - Total (%), Net reproduction rate (per woman), Life expectancy at birth - Total (years)), 1970 (range 1.8–930.1), 1971 (range 1.9–948.5), 1972 (range 1.9–966.8), 1973 (range 1.9–985.6) and 44 others.
Quick Start
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-central-african-republic-uneca-population-and-migration")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()
print(train.shape)
train.head()
Schema
| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
indicator |
object | 0.0% | Average annual population growth rate - Total (%), Net reproduction rate (per woman), Life expectancy at birth - Total (years) |
1970 |
float64 | 50.0% | 1.8 – 930.1 (mean 226.7286) |
1971 |
float64 | 50.0% | 1.9 – 948.5 (mean 231.3762) |
1972 |
float64 | 50.0% | 1.9 – 966.8 (mean 235.9476) |
1973 |
float64 | 50.0% | 1.9 – 985.6 (mean 240.5333) |
1974 |
float64 | 52.4% | 2.0 – 970.7 (mean 207.32) |
1975 |
float64 | 52.4% | 2.0 – 991.0 (mean 211.51) |
1976 |
float64 | 54.8% | 2.1 – 863.9 (mean 174.2368) |
1977 |
float64 | 54.8% | 2.1 – 886.5 (mean 178.1105) |
1978 |
float64 | 54.8% | 2.2 – 909.6 (mean 182.2) |
1979 |
float64 | 54.8% | 2.2 – 934.1 (mean 186.5789) |
1980 |
float64 | 54.8% | 2.3 – 960.7 (mean 191.3158) |
1981 |
float64 | 54.8% | 2.3 – 990.7 (mean 196.5684) |
1982 |
object | 47.6% | 3.0, 3.8, 99.0 |
1983 |
object | 47.6% | 3.0, 3.8, 101.4 |
1984 |
object | 47.6% | 2.8, 3.8, 103.6 |
1985 |
object | 47.6% | 2.5, 2.8, 105.7 |
1986 |
object | 47.6% | 2.3, 2.8, 108.5 |
1987 |
object | 47.6% | 49.7, 2.8, 2.2 |
1988 |
object | 47.6% | 2.8, 2.1, 606.7 |
1989 |
object | 47.6% | 2.2, 2.8, 115.5 |
1990 |
float64 | 14.3% | 1.3 – 793.1 (mean 100.3389) |
1991 |
object | 47.6% | 2.5, 2.6, 120.9 |
1992 |
object | 47.6% | |
1993 |
object | 47.6% | |
1994 |
object | 47.6% | |
1995 |
float64 | 14.3% | 2.0 – 911.0 (mean 114.4417) |
1996 |
object | 47.6% | |
1997 |
object | 47.6% | |
1998 |
object | 47.6% | |
1999 |
object | 47.6% | |
2000 |
float64 | 16.7% | 1.9 – 984.5 (mean 101.9486) |
2001 |
object | 45.2% | |
2002 |
object | 45.2% | |
2003 |
object | 45.2% | |
2004 |
object | 45.2% | |
2005 |
object | 0.0% | |
2006 |
object | 45.2% | |
2007 |
object | 45.2% | |
2008 |
object | 45.2% | |
2009 |
object | 45.2% | |
2010 |
object | 0.0% | |
2011 |
object | 45.2% | |
2012 |
object | 45.2% | |
2013 |
object | 47.6% | |
2014 |
object | 47.6% | |
2015 |
object | 4.8% | |
2016 |
object | 50.0% | |
2017 |
object | 31.0% | |
esa_source |
object | 0.0% | |
esa_processed |
object | 0.0% |
Numeric Summary
| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
1970 |
1.8 | 930.1 | 226.7286 | 43.1 |
1971 |
1.9 | 948.5 | 231.3762 | 43.0 |
1972 |
1.9 | 966.8 | 235.9476 | 43.6 |
1973 |
1.9 | 985.6 | 240.5333 | 44.6 |
1974 |
2.0 | 970.7 | 207.32 | 45.25 |
1975 |
2.0 | 991.0 | 211.51 | 46.1 |
1976 |
2.1 | 863.9 | 174.2368 | 46.6 |
1977 |
2.1 | 886.5 | 178.1105 | 47.3 |
1978 |
2.2 | 909.6 | 182.2 | 47.9 |
1979 |
2.2 | 934.1 | 186.5789 | 48.4 |
1980 |
2.3 | 960.7 | 191.3158 | 48.9 |
1981 |
2.3 | 990.7 | 196.5684 | 49.3 |
1990 |
1.3 | 793.1 | 100.3389 | 7.8 |
1995 |
2.0 | 911.0 | 114.4417 | 12.05 |
2000 |
1.9 | 984.5 | 101.9486 | 12.5 |
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. 15 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 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.
Citation
@dataset{hdx_africa_central_african_republic_uneca_population_and_migration,
title = {CENTRAL AFRICAN REPUBLIC - Population and migration indicators, UNECA},
author = {United Nations Economic Commission for Africa},
year = {2024},
url = {https://data.humdata.org/dataset/central-african-republic-uneca-population-and-migration},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.