country_name stringlengths 4 28 | country_iso3 stringlengths 3 3 | year int64 2.01k 2.02k | Account ownership at a financial institution or with a mobile-money-service provider (% of population ages 15+) float64 1.52 90.5 |
|---|---|---|---|
Algeria | DZA | 2,011 | 33.286114 |
Algeria | DZA | 2,014 | 50.475792 |
Algeria | DZA | 2,017 | 42.776627 |
Algeria | DZA | 2,021 | 44.097023 |
Algeria | DZA | 2,024 | 35.290108 |
Angola | AGO | 2,011 | 39.20354 |
Angola | AGO | 2,014 | 29.318121 |
Benin | BEN | 2,011 | 10.463937 |
Benin | BEN | 2,014 | 16.620834 |
Benin | BEN | 2,017 | 38.48922 |
Benin | BEN | 2,021 | 48.60553 |
Benin | BEN | 2,024 | 51.843204 |
Botswana | BWA | 2,011 | 30.260014 |
Botswana | BWA | 2,014 | 51.96457 |
Botswana | BWA | 2,017 | 51.03245 |
Botswana | BWA | 2,022 | 58.763195 |
Botswana | BWA | 2,024 | 61.43847 |
Burkina Faso | BFA | 2,011 | 13.353092 |
Burkina Faso | BFA | 2,014 | 14.357596 |
Burkina Faso | BFA | 2,017 | 43.159992 |
Burkina Faso | BFA | 2,021 | 36.108536 |
Burkina Faso | BFA | 2,024 | 51.42749 |
Burundi | BDI | 2,011 | 7.237985 |
Burundi | BDI | 2,014 | 7.105759 |
Cameroon | CMR | 2,011 | 14.809612 |
Cameroon | CMR | 2,014 | 12.177734 |
Cameroon | CMR | 2,017 | 34.59079 |
Cameroon | CMR | 2,021 | 51.65481 |
Cameroon | CMR | 2,024 | 60.87379 |
Central African Republic | CAF | 2,011 | 3.300809 |
Central African Republic | CAF | 2,017 | 13.745947 |
Chad | TCD | 2,011 | 8.959745 |
Chad | TCD | 2,014 | 12.433345 |
Chad | TCD | 2,017 | 21.759193 |
Chad | TCD | 2,022 | 23.651333 |
Chad | TCD | 2,024 | 20.89836 |
Comoros | COM | 2,011 | 21.694674 |
Comoros | COM | 2,022 | 34.25017 |
Comoros | COM | 2,024 | 45.459396 |
Congo | COG | 2,011 | 10.048057 |
Congo | COG | 2,014 | 17.069597 |
Congo | COG | 2,017 | 26.092749 |
Congo | COG | 2,021 | 47.142155 |
Congo | COG | 2,024 | 55.57604 |
Cote d'Ivoire | CIV | 2,014 | 34.32202 |
Cote d'Ivoire | CIV | 2,017 | 41.330956 |
Cote d'Ivoire | CIV | 2,021 | 50.76229 |
Cote d'Ivoire | CIV | 2,024 | 57.567627 |
Democratic Republic of Congo | COD | 2,011 | 3.696726 |
Democratic Republic of Congo | COD | 2,014 | 17.476984 |
Democratic Republic of Congo | COD | 2,017 | 25.825676 |
Democratic Republic of Congo | COD | 2,022 | 27.441132 |
Democratic Republic of Congo | COD | 2,024 | 39.214012 |
Djibouti | DJI | 2,011 | 12.273882 |
Egypt | EGY | 2,011 | 9.71998 |
Egypt | EGY | 2,014 | 14.126797 |
Egypt | EGY | 2,017 | 32.78436 |
Egypt | EGY | 2,021 | 27.444006 |
Egypt | EGY | 2,024 | 43.113438 |
Eswatini | SWZ | 2,011 | 28.56944 |
Eswatini | SWZ | 2,022 | 66.175804 |
Eswatini | SWZ | 2,024 | 65.11603 |
Ethiopia | ETH | 2,014 | 21.791582 |
Ethiopia | ETH | 2,017 | 34.827568 |
Ethiopia | ETH | 2,022 | 46.48007 |
Ethiopia | ETH | 2,024 | 48.830276 |
Gabon | GAB | 2,011 | 18.946518 |
Gabon | GAB | 2,014 | 33.014183 |
Gabon | GAB | 2,017 | 58.601997 |
Gabon | GAB | 2,021 | 66.08997 |
Gabon | GAB | 2,024 | 68.18126 |
Gambia | GMB | 2,017 | 28.560482 |
Gambia | GMB | 2,022 | 33.011017 |
Gambia | GMB | 2,024 | 38.160904 |
Ghana | GHA | 2,011 | 29.425354 |
Ghana | GHA | 2,014 | 40.505795 |
Ghana | GHA | 2,017 | 57.717525 |
Ghana | GHA | 2,021 | 68.23039 |
Ghana | GHA | 2,024 | 81.24303 |
Guinea | GIN | 2,011 | 3.68785 |
Guinea | GIN | 2,014 | 6.960017 |
Guinea | GIN | 2,017 | 23.486034 |
Guinea | GIN | 2,021 | 30.440336 |
Guinea | GIN | 2,024 | 36.048023 |
Kenya | KEN | 2,011 | 42.343456 |
Kenya | KEN | 2,014 | 74.65783 |
Kenya | KEN | 2,017 | 81.567566 |
Kenya | KEN | 2,021 | 79.19516 |
Kenya | KEN | 2,024 | 90.11992 |
Lesotho | LSO | 2,011 | 18.497025 |
Lesotho | LSO | 2,017 | 45.563816 |
Lesotho | LSO | 2,022 | 63.63491 |
Lesotho | LSO | 2,024 | 61.571045 |
Liberia | LBR | 2,011 | 18.801466 |
Liberia | LBR | 2,017 | 35.71384 |
Liberia | LBR | 2,021 | 51.631145 |
Liberia | LBR | 2,024 | 52.213932 |
Libya | LBY | 2,017 | 65.66752 |
Libya | LBY | 2,024 | 33.11909 |
Madagascar | MDG | 2,011 | 5.523222 |
Account At Financial Institution | Africa (Our World in Data)
🌍 195 observations · 48 Africa countries · 2011–2024 · Repackaged by Electric Sheep Africa
TL;DR
This dataset contains 195 observations of Account At Financial Institution data across 48 Africa countries, spanning 2011–2024.
About the source
- Source: Our World in Data
- Publisher: Our World in Data
- License: cc-by-4.0
- Topic: Account At Financial Institution
Geographic coverage
48 Africa countries · top rows shown below, sorted by row count:
| Country | Rows | First year | Last year |
|---|---|---|---|
BFA |
5 | 2011 | 2024 |
BEN |
5 | 2011 | 2024 |
CMR |
5 | 2011 | 2024 |
BWA |
5 | 2011 | 2024 |
DZA |
5 | 2011 | 2024 |
EGY |
5 | 2011 | 2024 |
COG |
5 | 2011 | 2024 |
COD |
5 | 2011 | 2024 |
GAB |
5 | 2011 | 2024 |
MLI |
5 | 2011 | 2024 |
MRT |
5 | 2011 | 2024 |
MUS |
5 | 2011 | 2024 |
NER |
5 | 2011 | 2024 |
KEN |
5 | 2011 | 2024 |
GIN |
5 | 2011 | 2024 |
| ... | 33 more countries |
Schema
| Column | Type | Description | Example |
|---|---|---|---|
country_name |
string |
— | Algeria |
country_iso3 |
string |
— | DZA |
year |
int64 |
— | 2011 |
Account ownership at a financial institution or with a mobile-money-service provider (% of population ages 15+) |
float64 |
— | 33.286114 |
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-owid-account-at-financial-institution")
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="Account ownership at a financial institution or with a mobile-money-service provider (% of population ages 15+)")
Citation
@misc{africa_owid_account_at_financial_institution_2024,
title = {Account At Financial Institution | Africa (Our World in Data)},
author = {Our World in Data},
year = {2024},
url = {https://ourworldindata.org/grapher/account-at-financial-institution},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-owid-account-at-financial-institution}}
}
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/account-at-financial-institution
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