README.md

---
license: cc-by-4.0
language:
- en
task_categories:
- tabular-classification
- tabular-regression
- time-series-forecasting
multilinguality: monolingual
size_categories:
- n<1K
tags:
- tabular
- asia
- our-world-in-data
- adoption-of-mobile-money-accounts-vs-adoption-of-mobile-phones
- owid
- long-run-series
- time-series
pretty_name: "Adoption Of Mobile Money Accounts Vs Adoption Of Mobile Phones | Asia (Our World in Data)"
---

# Adoption Of Mobile Money Accounts Vs Adoption Of Mobile Phones | Asia (Our World in Data)

🌏 **83 observations** · **39 Asia countries** · **2014–2022** · *Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)*

![rows](https://img.shields.io/badge/rows-83-blue) ![countries](https://img.shields.io/badge/countries-39-green) ![years](https://img.shields.io/badge/years-2014–2022-orange) ![license](https://img.shields.io/badge/license-cc-by-4.0-lightgrey)

## TL;DR

This dataset contains **83 observations** of `Adoption Of Mobile Money Accounts Vs Adoption Of Mobile Phones` data across **39 Asia countries**, spanning **2014–2022**.

## About the source

- **Source:** [Our World in Data](https://ourworldindata.org/grapher/adoption-of-mobile-money-accounts-vs-adoption-of-mobile-phones)
- **Publisher:** Our World in Data
- **License:** [cc-by-4.0](https://creativecommons.org/licenses/by/4.0/)
- **Topic:** Adoption Of Mobile Money Accounts Vs Adoption Of Mobile Phones

## Geographic coverage

39 Asia countries · top rows shown below, sorted by row count:

| Country | Rows | First year | Last year |
|---------|-----:|-----------:|----------:|
| `AFG` | 3 | 2014 | 2021 |
| `ARE` | 3 | 2014 | 2021 |
| `ARM` | 3 | 2014 | 2021 |
| `BGD` | 3 | 2014 | 2021 |
| `IRN` | 3 | 2014 | 2021 |
| `IND` | 3 | 2014 | 2021 |
| `IDN` | 3 | 2014 | 2021 |
| `SGP` | 3 | 2014 | 2021 |
| `THA` | 3 | 2014 | 2021 |
| `TUR` | 3 | 2014 | 2021 |
| `JOR` | 3 | 2014 | 2021 |
| `LKA` | 3 | 2014 | 2021 |
| `KHM` | 3 | 2014 | 2021 |
| `MNG` | 3 | 2014 | 2021 |
| `VNM` | 3 | 2014 | 2022 |
| ... | _24 more countries_ | | |

## Schema

| Column | Type | Description | Example |
|--------|------|-------------|---------|
| `country_name` | `string` | — | `Afghanistan` |
| `country_iso3` | `string` | — | `AFG` |
| `year` | `int64` | — | `2014` |
| `Share with a mobile money account` | `float64` | — | `0.3044038` |
| `Share with a mobile phone` | `float64` | — | `67.83732` |
| `World region according to OWID` | `string` | — | `Asia` |

## Data quality & caveats

- `Share with a mobile money account` column has 14.5% null values (filtered to non-null in this dataset).

## Usage

```python
from datasets import load_dataset

ds = load_dataset("electricsheepasia/asia-owid-adoption-of-mobile-money-accounts-vs-adoption-of-mobile-phones")
df = ds["train"].to_pandas()
print(df.head())
```

### Filter to one country

```python
indonesia = df[df["country_iso3"] == "IDN"]
```

### Time-series for a single indicator

```python
sample = df.sort_values("year")
sample.plot(x="year", y="Share with a mobile money account")
```

## Citation

```bibtex
@misc{asia_owid_adoption_of_mobile_money_accounts_vs_adoption_of_mobile_phones_2022,
  title        = {Adoption Of Mobile Money Accounts Vs Adoption Of Mobile Phones | Asia (Our World in Data)},
  author       = {Our World in Data},
  year         = {2022},
  url          = {https://ourworldindata.org/grapher/adoption-of-mobile-money-accounts-vs-adoption-of-mobile-phones},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-owid-adoption-of-mobile-money-accounts-vs-adoption-of-mobile-phones}}
}
```

## License

Released under [cc-by-4.0](https://creativecommons.org/licenses/by/4.0/).

Original data © Our World in Data. When using this dataset, please cite both the original source above and the Electric Sheep Asia repackaging.

## About Electric Sheep

Electric Sheep Asia is part of the Electric Sheep mission: a unified, ML-ready data layer for Asia 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/electricsheepasia](https://huggingface.co/electricsheepasia)

---

_Provenance: ingested 2026-06-02 via the Electric Sheep pipeline. Source URL: https://ourworldindata.org/grapher/adoption-of-mobile-money-accounts-vs-adoption-of-mobile-phones_