Datasets:
country_name stringlengths 4 28 | country_iso3 stringlengths 3 3 | year int64 2k 2.02k | Share of workers in informal employment in the agricultural sector float64 35 99.9 | Share of workers in informal employment in the non-agricultural sector float64 14.1 98.2 | World region according to OWID stringclasses 1
value |
|---|---|---|---|---|---|
Angola | AGO | 2,004 | 98.47 | 68.22 | Africa |
Angola | AGO | 2,011 | 99.76 | 68.1 | Africa |
Angola | AGO | 2,019 | 99.47 | 75.94 | Africa |
Angola | AGO | 2,021 | 99.84 | 78.13 | Africa |
Angola | AGO | 2,022 | 99.75 | 84.12 | Africa |
Benin | BEN | 2,011 | 99.78 | 94.54 | Africa |
Benin | BEN | 2,022 | 99.83 | 93.75 | Africa |
Botswana | BWA | 2,019 | 96.08 | 66.61 | Africa |
Botswana | BWA | 2,020 | 98.53 | 67.92 | Africa |
Botswana | BWA | 2,021 | 97.84 | 65.67 | Africa |
Botswana | BWA | 2,022 | 98.61 | 69.27 | Africa |
Botswana | BWA | 2,023 | 99.17 | 71.1 | Africa |
Burkina Faso | BFA | 2,018 | 99.44 | 94.26 | Africa |
Burkina Faso | BFA | 2,022 | 99.67 | 93.32 | Africa |
Burkina Faso | BFA | 2,023 | 99.64 | 93.11 | Africa |
Burundi | BDI | 2,014 | 99.73 | 89.44 | Africa |
Cameroon | CMR | 2,007 | 99.26 | 79.21 | Africa |
Cameroon | CMR | 2,014 | 98.46 | 76.8 | Africa |
Cape Verde | CPV | 2,015 | 95.96 | 57.81 | Africa |
Chad | TCD | 2,018 | 99.79 | 90.12 | Africa |
Comoros | COM | 2,014 | 96.91 | 93.36 | Africa |
Comoros | COM | 2,021 | 99.49 | 83.92 | Africa |
Congo | COG | 2,009 | 91.18 | 85.03 | Africa |
Cote d'Ivoire | CIV | 2,012 | 98.55 | 92.15 | Africa |
Cote d'Ivoire | CIV | 2,013 | 99.52 | 96.21 | Africa |
Cote d'Ivoire | CIV | 2,016 | 98.44 | 88.53 | Africa |
Cote d'Ivoire | CIV | 2,017 | 89.32 | 84.75 | Africa |
Cote d'Ivoire | CIV | 2,019 | 98.82 | 85.91 | Africa |
Cote d'Ivoire | CIV | 2,022 | 99.12 | 85.67 | Africa |
Democratic Republic of Congo | COD | 2,005 | 99.56 | 96.25 | Africa |
Democratic Republic of Congo | COD | 2,012 | 99.44 | 93.91 | Africa |
Djibouti | DJI | 2,017 | 81.57 | 50.13 | Africa |
Egypt | EGY | 2,008 | 93.43 | 38.3 | Africa |
Egypt | EGY | 2,009 | 92.78 | 39.44 | Africa |
Egypt | EGY | 2,010 | 94.58 | 43.11 | Africa |
Egypt | EGY | 2,011 | 94.9 | 43.83 | Africa |
Egypt | EGY | 2,012 | 94.45 | 41.62 | Africa |
Egypt | EGY | 2,013 | 95.62 | 42.86 | Africa |
Egypt | EGY | 2,015 | 96.1 | 47.2 | Africa |
Egypt | EGY | 2,016 | 95.37 | 50.36 | Africa |
Egypt | EGY | 2,017 | 96.48 | 52.8 | Africa |
Egypt | EGY | 2,018 | 97.59 | 54.38 | Africa |
Egypt | EGY | 2,019 | 96.86 | 59.02 | Africa |
Egypt | EGY | 2,023 | 97.85 | 65.64 | Africa |
Eswatini | SWZ | 2,016 | 69.87 | 57.15 | Africa |
Eswatini | SWZ | 2,021 | 53.72 | 51.17 | Africa |
Ethiopia | ETH | 2,021 | 94.58 | 68.93 | Africa |
Gambia | GMB | 2,012 | 96.21 | 68.19 | Africa |
Gambia | GMB | 2,018 | 97 | 62.52 | Africa |
Gambia | GMB | 2,023 | 97.89 | 78.5 | Africa |
Ghana | GHA | 2,013 | 99.62 | 85.95 | Africa |
Ghana | GHA | 2,015 | 97.56 | 67.48 | Africa |
Guinea-Bissau | GNB | 2,018 | 99.25 | 98.18 | Africa |
Guinea-Bissau | GNB | 2,022 | 99.61 | 86.67 | Africa |
Kenya | KEN | 2,019 | 97.11 | 81.12 | Africa |
Lesotho | LSO | 2,019 | 99.1 | 73.1 | Africa |
Liberia | LBR | 2,010 | 97 | 77.58 | Africa |
Liberia | LBR | 2,017 | 97.31 | 87.86 | Africa |
Madagascar | MDG | 2,012 | 99.24 | 87.38 | Africa |
Madagascar | MDG | 2,015 | 99.09 | 83.86 | Africa |
Madagascar | MDG | 2,022 | 99.45 | 88.22 | Africa |
Malawi | MWI | 2,013 | 95.34 | 73.96 | Africa |
Mali | MLI | 2,013 | 99.33 | 84.05 | Africa |
Mali | MLI | 2,014 | 98.71 | 88.47 | Africa |
Mali | MLI | 2,015 | 99.09 | 91.24 | Africa |
Mali | MLI | 2,016 | 97.29 | 90.49 | Africa |
Mali | MLI | 2,017 | 97.11 | 90.62 | Africa |
Mali | MLI | 2,018 | 97.6 | 89.82 | Africa |
Mali | MLI | 2,020 | 97.55 | 86.52 | Africa |
Mali | MLI | 2,022 | 99.77 | 87.61 | Africa |
Mauritania | MRT | 2,017 | 99.09 | 92.37 | Africa |
Mauritania | MRT | 2,019 | 97.28 | 85.27 | Africa |
Mauritius | MUS | 2,012 | 70.33 | 49.74 | Africa |
Mauritius | MUS | 2,013 | 74.3 | 49.78 | Africa |
Mauritius | MUS | 2,014 | 78.9 | 52.81 | Africa |
Mauritius | MUS | 2,015 | 75.61 | 51.52 | Africa |
Mauritius | MUS | 2,016 | 74.59 | 51.18 | Africa |
Mauritius | MUS | 2,017 | 75.84 | 50.41 | Africa |
Mauritius | MUS | 2,018 | 70.84 | 52.39 | Africa |
Mauritius | MUS | 2,019 | 73.37 | 52.31 | Africa |
Mauritius | MUS | 2,021 | 59.63 | 30.25 | Africa |
Mauritius | MUS | 2,022 | 58.48 | 30.98 | Africa |
Mauritius | MUS | 2,023 | 69.12 | 32.03 | Africa |
Mozambique | MOZ | 2,015 | 99.15 | 86.71 | Africa |
Namibia | NAM | 2,012 | 87.81 | 41.51 | Africa |
Namibia | NAM | 2,013 | 88.28 | 46.26 | Africa |
Namibia | NAM | 2,014 | 86.75 | 43.98 | Africa |
Namibia | NAM | 2,016 | 90.38 | 61.07 | Africa |
Namibia | NAM | 2,018 | 85.89 | 46.97 | Africa |
Niger | NER | 2,011 | 98.07 | 86.35 | Africa |
Niger | NER | 2,017 | 88.06 | 67.18 | Africa |
Niger | NER | 2,022 | 99.91 | 94.49 | Africa |
Nigeria | NGA | 2,022 | 99.58 | 90.92 | Africa |
Nigeria | NGA | 2,023 | 99.65 | 89.41 | Africa |
Rwanda | RWA | 2,017 | 98.42 | 68.25 | Africa |
Rwanda | RWA | 2,018 | 98.91 | 68.69 | Africa |
Rwanda | RWA | 2,019 | 99.23 | 68.9 | Africa |
Rwanda | RWA | 2,020 | 99.35 | 72.28 | Africa |
Rwanda | RWA | 2,021 | 99.69 | 71.03 | Africa |
Rwanda | RWA | 2,022 | 99.45 | 71.11 | Africa |
Agriculture Vs Non Agriculture Share In Informal Employment | Africa (Our World in Data)
🌍 164 observations · 44 Africa countries · 2000–2024 · Repackaged by Electric Sheep Africa
TL;DR
This dataset contains 164 observations of Agriculture Vs Non Agriculture Share In Informal Employment data across 44 Africa countries, spanning 2000–2024.
About the source
- Source: Our World in Data
- Publisher: Our World in Data
- License: cc-by-4.0
- Topic: Agriculture Vs Non Agriculture Share In Informal Employment
Geographic coverage
44 Africa countries · top rows shown below, sorted by row count:
| Country | Rows | First year | Last year |
|---|---|---|---|
ZAF |
25 | 2000 | 2024 |
EGY |
12 | 2008 | 2023 |
MUS |
11 | 2012 | 2023 |
MLI |
8 | 2013 | 2022 |
UGA |
7 | 2010 | 2021 |
RWA |
7 | 2017 | 2023 |
ZMB |
7 | 2017 | 2023 |
ZWE |
6 | 2011 | 2023 |
CIV |
6 | 2012 | 2022 |
AGO |
5 | 2004 | 2022 |
BWA |
5 | 2019 | 2023 |
SEN |
5 | 2011 | 2022 |
NAM |
5 | 2012 | 2018 |
BFA |
3 | 2018 | 2023 |
MDG |
3 | 2012 | 2022 |
| ... | 29 more countries |
Schema
| Column | Type | Description | Example |
|---|---|---|---|
country_name |
string |
— | Angola |
country_iso3 |
string |
— | AGO |
year |
int64 |
— | 2004 |
Share of workers in informal employment in the agricultural sector |
float64 |
— | 98.47 |
Share of workers in informal employment in the non-agricultural sector |
float64 |
— | 68.22 |
World region according to OWID |
string |
— | Africa |
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-owid-agriculture-vs-non-agriculture-share-in-informal-employment")
df = ds["train"].to_pandas()
print(df.head())
Filter to one country
kenya = df[df["country_iso3"] == "KEN"]
Time-series for a single indicator
sample = df.sort_values("year")
sample.plot(x="year", y="Share of workers in informal employment in the agricultural sector")
Citation
@misc{africa_owid_agriculture_vs_non_agriculture_share_in_informal_employment_2024,
title = {Agriculture Vs Non Agriculture Share In Informal Employment | Africa (Our World in Data)},
author = {Our World in Data},
year = {2024},
url = {https://ourworldindata.org/grapher/agriculture-vs-non-agriculture-share-in-informal-employment},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-owid-agriculture-vs-non-agriculture-share-in-informal-employment}}
}
License
Released under cc-by-4.0.
Original data © Our World in Data. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.
About Electric Sheep
Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on HuggingFace. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.
Browse the full collection: huggingface.co/electricsheepafrica
Provenance: ingested 2026-06-01 via the Electric Sheep pipeline. Source URL: https://ourworldindata.org/grapher/agriculture-vs-non-agriculture-share-in-informal-employment
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