Datasets:
indicator stringlengths 30 121 | 2010 float64 0.9 110 ⌀ | 2011 float64 0.5 110 ⌀ | 2012 float64 0.5 108 ⌀ | esa_source stringclasses 1
value | esa_processed stringdate 2026-04-16 00:00:00 2026-04-16 00:00:00 |
|---|---|---|---|---|---|
Pupil-teacher ratio, primary education - Total (rate) | 49.2 | 47.1 | 44.4 | HDX | 2026-04-16 |
Participation rate in organized learning (one year before the official primary entry age) - Male (%) | 29.3 | null | 22.1 | HDX | 2026-04-16 |
Gender parity index of teachers in pre-primary education who are trained (ratio) | 1.1 | null | 0.9 | HDX | 2026-04-16 |
Gross enrolment ratio in teritiary - Female (%) | null | 6.7 | 7.7 | HDX | 2026-04-16 |
Gender parity index for participation rate in organized learning (one year before the official primary entry age) (ratio) | 1 | null | 1.1 | HDX | 2026-04-16 |
Gender parity index for achievement in mathematics in grades 2/3 (ratio) | null | null | null | HDX | 2026-04-16 |
Rural to urban parity index for achievement in mathematics by the end of primary (ratio) | null | null | null | HDX | 2026-04-16 |
Net enrolment rate in primary education - Total (%) | 89.3 | null | 85.8 | HDX | 2026-04-16 |
School life Expectancy in Secondary - Female (years) | null | null | 3.4 | HDX | 2026-04-16 |
School life Expectancy in Primary - Total (years) | 6.9 | 6.8 | 6.4 | HDX | 2026-04-16 |
School life Expectancy in Tertiary - Total (years) | null | 0.5 | 0.5 | HDX | 2026-04-16 |
Gross enrolment ratio in secondary - Male (%) | null | null | 55.9 | HDX | 2026-04-16 |
Gender parity index of teachers in primary education who are trained (ratio) | 1.1 | 1.2 | 1.2 | HDX | 2026-04-16 |
Gross enrolment ratio in secondary - Total (%) | null | null | 52.1 | HDX | 2026-04-16 |
Mean years of schooling - Total (years) | 6.1 | 6.1 | 6.1 | HDX | 2026-04-16 |
Proportion of children at the end of primary achieving at least a minimum proficiency level in mathematics (%) | 77.3 | null | null | HDX | 2026-04-16 |
Survival Rate to the last grade in Primary - Female (%) | null | null | null | HDX | 2026-04-16 |
School life Expectancy in Secondary - Male (years) | null | null | 3.9 | HDX | 2026-04-16 |
Net enrolment rate in primary education - Female (%) | 87.8 | null | 89.4 | HDX | 2026-04-16 |
Gross enrolment ratio in primary - Female (%) | 109.9 | 110 | 107.8 | HDX | 2026-04-16 |
Proportion of children at the end of primary achieving at least a minimum proficiency level in mathematics - Female (%) | null | null | null | HDX | 2026-04-16 |
School life Expectancy in Secondary - Total (years) | null | null | 3.7 | HDX | 2026-04-16 |
Ratio of girls to boys in primary education (ratio) | 0.9 | 0.9 | 1.1 | HDX | 2026-04-16 |
Participation rate in organized learning (one year before the official primary entry age) - Female (%) | 30.5 | null | 24.6 | HDX | 2026-04-16 |
Ratio of school attendance rate of orphans to school attendance rate of non orphans (%) | null | null | 1 | HDX | 2026-04-16 |
Adult literacy rate - Male (%) | null | 86.4 | null | HDX | 2026-04-16 |
Gross graduation Ratio from Primary education - Male (%) | 46.9 | null | 49 | HDX | 2026-04-16 |
Adult literacy rate - Total (%) | null | 79.3 | null | HDX | 2026-04-16 |
Rural to urban parity index for achievement in reading by the end of primary (ratio) | null | null | null | HDX | 2026-04-16 |
Ratio of girls to boys in tertiary education (ratio) | null | 0.6 | 0.6 | HDX | 2026-04-16 |
Pupil-teacher ratio, secondary education - Total (rate) | null | null | 18.7 | HDX | 2026-04-16 |
Literacy rates of 15-24 years old - Total (%) | null | 80.9 | null | HDX | 2026-04-16 |
School life Expectancy in Primary - Male (years) | 7.1 | 7 | 6.2 | HDX | 2026-04-16 |
Gender parity index of teachers in upper secondary education who are trained (ratio) | null | null | 1.1 | HDX | 2026-04-16 |
Gross graduation Ratio from Primary education - Total (%) | 44.6 | null | 45 | HDX | 2026-04-16 |
Gross enrolment ratio in teritiary - Male (%) | null | 11.5 | 12.3 | HDX | 2026-04-16 |
Survival Rate to the last grade in Primary - Total (%) | null | null | null | HDX | 2026-04-16 |
Gross graduation Ratio from Primary education - Female (%) | 42.3 | null | 46.2 | HDX | 2026-04-16 |
Gender parity index of teachers in lower secondary education who are trained (ratio) | null | null | 2.2 | HDX | 2026-04-16 |
Rural to urban parity index for achievement in mathematics in grades 2/3 (ratio) | null | null | null | HDX | 2026-04-16 |
Gross enrolment ratio in secondary - Female (%) | null | null | 48.4 | HDX | 2026-04-16 |
Participation rate in organized learning (one year before the official primary entry age) (%) | 29.9 | null | 23.3 | HDX | 2026-04-16 |
School life Expectancy in Tertiary - Male (years) | null | 0.6 | 0.6 | HDX | 2026-04-16 |
Ratio of girls to boys in secondary education (ratio) | null | null | 0.9 | HDX | 2026-04-16 |
CONGO - Education 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 in education such as as Net enrolment rate in primary education, Ratio of girls to boys in primary education, etc. The whole list and their description can be find in this link https://bit.ly/2NWP6Z1
Each row in this dataset represents tabular records. Data was last updated on HDX on 2024-09-13. Geographic scope: COG.
Curated into ML-ready Parquet format by Electric Sheep Africa.
Dataset Characteristics
| Domain | Education |
| Unit of observation | Tabular records |
| Rows (total) | 56 |
| Columns | 6 (3 numeric, 3 categorical, 0 datetime) |
| Train split | 44 rows |
| Test split | 11 rows |
| Geographic scope | COG |
| Publisher | United Nations Economic Commission for Africa |
| HDX last updated | 2024-09-13 |
Variables
Identifier / Metadata — esa_source (HDX), esa_processed (2026-04-16).
Other — indicator (Adult literacy rate - Female (%), Adult literacy rate - Male (%), Participation rate in organized learning (one year before the official primary entry age) - Male (%)), 2010 (range 0.9–116.3), 2011 (range 0.3–116.6), 2012 (range 0.4–107.8).
Quick Start
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-congo-uneca-education")
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% | Adult literacy rate - Female (%), Adult literacy rate - Male (%), Participation rate in organized learning (one year before the official primary entry age) - Male (%) |
2010 |
float64 | 62.5% | 0.9 – 116.3 (mean 42.7286) |
2011 |
float64 | 60.7% | 0.3 – 116.6 (mean 34.9773) |
2012 |
float64 | 28.6% | 0.4 – 107.8 (mean 27.24) |
esa_source |
object | 0.0% | HDX |
esa_processed |
object | 0.0% | 2026-04-16 |
Numeric Summary
| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
2010 |
0.9 | 116.3 | 42.7286 | 30.5 |
2011 |
0.3 | 116.6 | 34.9773 | 8.05 |
2012 |
0.4 | 107.8 | 27.24 | 8.85 |
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. 7 column(s) with >80% missing values were removed: 2013, 2014, 2015, 2016, 2017, 2018.... 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:
2010,2011,2012. - Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.
Citation
@dataset{hdx_africa_congo_uneca_education,
title = {CONGO - Education indicators, UNECA},
author = {United Nations Economic Commission for Africa},
year = {2024},
url = {https://data.humdata.org/dataset/congo-uneca-education},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.
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