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country_name
stringlengths
4
12
country_iso3
stringlengths
3
3
year
int64
2.01k
2.02k
Share with a mobile money account
float64
0
58.8
Share with a mobile phone
float64
63
100
World region according to OWID
stringclasses
2 values
Afghanistan
AFG
2,014
0.304404
null
Asia
Afghanistan
AFG
2,017
0.913816
null
Asia
Afghanistan
AFG
2,021
0
67.83732
Asia
Armenia
ARM
2,014
0.657837
null
Asia
Armenia
ARM
2,017
9.755306
null
Asia
Armenia
ARM
2,021
16.742744
93.91802
Asia
Azerbaijan
AZE
2,022
null
84.871445
Asia
Bangladesh
BGD
2,014
2.691714
null
Asia
Bangladesh
BGD
2,017
21.24596
null
Asia
Bangladesh
BGD
2,021
29.005793
78.943146
Asia
Cambodia
KHM
2,014
13.294556
null
Asia
Cambodia
KHM
2,017
5.659509
null
Asia
Cambodia
KHM
2,021
6.598233
81.44287
Asia
China
CHN
2,021
null
100
Asia
Cyprus
CYP
2,021
null
93.780945
Europe
Georgia
GEO
2,017
2.201022
null
Asia
Georgia
GEO
2,021
8.231201
91.34007
Asia
India
IND
2,014
2.35221
null
Asia
India
IND
2,017
1.994543
null
Asia
India
IND
2,021
10.439687
65.56514
Asia
Indonesia
IDN
2,014
0.449631
null
Asia
Indonesia
IDN
2,017
3.123916
null
Asia
Indonesia
IDN
2,021
9.292318
73.174545
Asia
Iran
IRN
2,014
4.495691
null
Asia
Iran
IRN
2,017
26.29661
null
Asia
Iran
IRN
2,021
12.386351
87.45277
Asia
Iraq
IRQ
2,017
4.214756
null
Asia
Iraq
IRQ
2,021
4.805505
85.09519
Asia
Israel
ISR
2,021
null
95.970764
Asia
Japan
JPN
2,021
null
94.82453
Asia
Jordan
JOR
2,014
0.468666
null
Asia
Jordan
JOR
2,017
1.060968
null
Asia
Jordan
JOR
2,021
10.659783
100
Asia
Kazakhstan
KAZ
2,021
null
90.62531
Asia
Kyrgyzstan
KGZ
2,017
3.106876
null
Asia
Kyrgyzstan
KGZ
2,021
11.429437
91.36153
Asia
Laos
LAO
2,021
5.479982
82.80404
Asia
Lebanon
LBN
2,014
0.670738
null
Asia
Lebanon
LBN
2,021
null
98.62489
Asia
Malaysia
MYS
2,014
2.830211
null
Asia
Malaysia
MYS
2,017
10.876333
null
Asia
Malaysia
MYS
2,021
27.978859
91.69206
Asia
Maldives
MDV
2,017
23.300787
null
Asia
Mongolia
MNG
2,014
4.997987
null
Asia
Mongolia
MNG
2,017
21.897148
null
Asia
Mongolia
MNG
2,021
58.812492
98.54656
Asia
Myanmar
MMR
2,014
0.163792
null
Asia
Myanmar
MMR
2,017
0.6905
null
Asia
Myanmar
MMR
2,021
29.030704
96.16992
Asia
Nepal
NPL
2,014
0.336039
null
Asia
Nepal
NPL
2,021
6.091908
79.57426
Asia
Pakistan
PAK
2,014
5.799799
null
Asia
Pakistan
PAK
2,017
6.885558
null
Asia
Pakistan
PAK
2,021
8.537407
62.9907
Asia
Palestine
PSE
2,021
2.328128
84.15787
Asia
Philippines
PHL
2,014
4.225874
null
Asia
Philippines
PHL
2,017
4.521299
null
Asia
Philippines
PHL
2,021
21.738909
92.10741
Asia
Saudi Arabia
SAU
2,021
null
99.160835
Asia
Singapore
SGP
2,014
6.14946
null
Asia
Singapore
SGP
2,017
9.548008
null
Asia
Singapore
SGP
2,021
30.604267
96.807884
Asia
South Korea
KOR
2,021
null
97.1535
Asia
Sri Lanka
LKA
2,014
0.076637
null
Asia
Sri Lanka
LKA
2,017
2.42076
null
Asia
Sri Lanka
LKA
2,021
3.126422
95.93685
Asia

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

rows countries years license

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
  • Publisher: Our World in Data
  • License: cc-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

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

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

Time-series for a single indicator

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

Citation

@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.

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


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

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