country_name stringlengths 4 11 | country_iso3 stringlengths 3 3 | year int64 2.01k 2.02k | Adequacy of social safety net programs (% of total welfare of beneficiary households) float64 0.17 48.1 |
|---|---|---|---|
Afghanistan | AFG | 2,007 | 27.620964 |
Armenia | ARM | 2,008 | 15.151555 |
Armenia | ARM | 2,009 | 16.967255 |
Armenia | ARM | 2,010 | 18.38447 |
Armenia | ARM | 2,011 | 15.534431 |
Armenia | ARM | 2,012 | 18.205938 |
Armenia | ARM | 2,013 | 17.067692 |
Armenia | ARM | 2,014 | 16.98853 |
Armenia | ARM | 2,015 | 15.892346 |
Armenia | ARM | 2,016 | 15.575439 |
Armenia | ARM | 2,017 | 17.513397 |
Armenia | ARM | 2,018 | 18.298536 |
Armenia | ARM | 2,019 | 29.293491 |
Armenia | ARM | 2,020 | 48.1281 |
Armenia | ARM | 2,021 | 22.632856 |
Armenia | ARM | 2,022 | 29.985796 |
Azerbaijan | AZE | 2,015 | 6.081878 |
Bangladesh | BGD | 2,005 | 19.71067 |
Bangladesh | BGD | 2,010 | 3.99774 |
Bangladesh | BGD | 2,016 | 2.59535 |
Bangladesh | BGD | 2,022 | 1.620616 |
Bhutan | BTN | 2,007 | 2.103454 |
Bhutan | BTN | 2,022 | 12.140232 |
China | CHN | 2,013 | 2.337669 |
East Timor | TLS | 2,007 | 9.814421 |
Georgia | GEO | 2,011 | 29.178883 |
Georgia | GEO | 2,012 | 28.799316 |
Georgia | GEO | 2,013 | 30.806484 |
Georgia | GEO | 2,014 | 35.43946 |
Georgia | GEO | 2,015 | 33.84235 |
Georgia | GEO | 2,016 | 37.640545 |
Georgia | GEO | 2,017 | 34.340614 |
Georgia | GEO | 2,018 | 34.063343 |
Georgia | GEO | 2,019 | 35.873425 |
Georgia | GEO | 2,020 | 42.121002 |
Georgia | GEO | 2,021 | 42.33938 |
India | IND | 2,011 | 7.402832 |
Indonesia | IDN | 2,015 | 15.943313 |
Indonesia | IDN | 2,016 | 4.013755 |
Indonesia | IDN | 2,017 | 3.167402 |
Indonesia | IDN | 2,018 | 3.693826 |
Indonesia | IDN | 2,019 | 4.862389 |
Indonesia | IDN | 2,020 | 5.389443 |
Indonesia | IDN | 2,021 | 5.296991 |
Indonesia | IDN | 2,022 | 9.375052 |
Iran | IRN | 2,017 | 7.657255 |
Iran | IRN | 2,018 | 6.623115 |
Iran | IRN | 2,019 | 5.813283 |
Iran | IRN | 2,020 | 25.779295 |
Iraq | IRQ | 2,006 | 2.286436 |
Iraq | IRQ | 2,012 | 2.753124 |
Jordan | JOR | 2,006 | 6.675276 |
Jordan | JOR | 2,010 | 3.981736 |
Kazakhstan | KAZ | 2,007 | 3.251413 |
Kazakhstan | KAZ | 2,010 | 6.290282 |
Kazakhstan | KAZ | 2,014 | 35.73579 |
Kazakhstan | KAZ | 2,015 | 12.596169 |
Kazakhstan | KAZ | 2,017 | 16.590696 |
Kazakhstan | KAZ | 2,018 | 16.990355 |
Kazakhstan | KAZ | 2,019 | 19.105917 |
Kazakhstan | KAZ | 2,020 | 20.513708 |
Kazakhstan | KAZ | 2,021 | 19.817673 |
Kyrgyzstan | KGZ | 2,006 | 9.206789 |
Kyrgyzstan | KGZ | 2,011 | 8.410479 |
Kyrgyzstan | KGZ | 2,012 | 10.000693 |
Kyrgyzstan | KGZ | 2,013 | 11.152781 |
Kyrgyzstan | KGZ | 2,014 | 13.92022 |
Kyrgyzstan | KGZ | 2,015 | 17.857021 |
Kyrgyzstan | KGZ | 2,016 | 14.227838 |
Kyrgyzstan | KGZ | 2,017 | 15.337955 |
Kyrgyzstan | KGZ | 2,018 | 17.730883 |
Kyrgyzstan | KGZ | 2,019 | 15.832272 |
Kyrgyzstan | KGZ | 2,020 | 16.870518 |
Malaysia | MYS | 2,008 | 1.745788 |
Malaysia | MYS | 2,012 | 0.755081 |
Malaysia | MYS | 2,014 | 2.163032 |
Malaysia | MYS | 2,016 | 3.03563 |
Maldives | MDV | 2,009 | 24.72657 |
Maldives | MDV | 2,016 | 18.142 |
Maldives | MDV | 2,019 | 18.318258 |
Mongolia | MNG | 2,007 | 6.289463 |
Mongolia | MNG | 2,009 | 6.820538 |
Mongolia | MNG | 2,010 | 5.932642 |
Mongolia | MNG | 2,011 | 10.982182 |
Mongolia | MNG | 2,012 | 11.065214 |
Mongolia | MNG | 2,014 | 4.463906 |
Mongolia | MNG | 2,016 | 4.811442 |
Mongolia | MNG | 2,018 | 6.523912 |
Mongolia | MNG | 2,020 | 9.801428 |
Myanmar | MMR | 2,017 | 1.207447 |
Nepal | NPL | 2,010 | 2.512116 |
Pakistan | PAK | 2,007 | 17.924421 |
Pakistan | PAK | 2,009 | 12.002831 |
Pakistan | PAK | 2,013 | 7.908932 |
Pakistan | PAK | 2,015 | 5.702304 |
Pakistan | PAK | 2,018 | 4.940313 |
Palestine | PSE | 2,009 | 20.669527 |
Palestine | PSE | 2,016 | 4.101665 |
Philippines | PHL | 2,013 | 11.64435 |
Philippines | PHL | 2,015 | 5.458818 |
Adequacy Of Social Safety Net Programs | Asia (Our World in Data)
🌏 139 observations · 30 Asia countries · 2004–2022 · Repackaged by Electric Sheep Asia
TL;DR
This dataset contains 139 observations of Adequacy Of Social Safety Net Programs data across 30 Asia countries, spanning 2004–2022.
About the source
- Source: Our World in Data
- Publisher: Our World in Data
- License: cc-by-4.0
- Topic: Adequacy Of Social Safety Net Programs
Geographic coverage
30 Asia countries · top rows shown below, sorted by row count:
| Country | Rows | First year | Last year |
|---|---|---|---|
TUR |
16 | 2004 | 2019 |
ARM |
15 | 2008 | 2022 |
KGZ |
11 | 2006 | 2020 |
GEO |
11 | 2011 | 2021 |
MNG |
9 | 2007 | 2020 |
KAZ |
9 | 2007 | 2021 |
IDN |
8 | 2015 | 2022 |
THA |
7 | 2006 | 2021 |
VNM |
6 | 2006 | 2020 |
PAK |
5 | 2007 | 2018 |
LKA |
5 | 2006 | 2019 |
MYS |
4 | 2008 | 2016 |
IRN |
4 | 2017 | 2020 |
BGD |
4 | 2005 | 2022 |
MDV |
3 | 2009 | 2019 |
| ... | 15 more countries |
Schema
| Column | Type | Description | Example |
|---|---|---|---|
country_name |
string |
— | Afghanistan |
country_iso3 |
string |
— | AFG |
year |
int64 |
— | 2007 |
Adequacy of social safety net programs (% of total welfare of beneficiary households) |
float64 |
— | 27.620964 |
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepasia/asia-owid-adequacy-of-social-safety-net-programs")
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="Adequacy of social safety net programs (% of total welfare of beneficiary households)")
Citation
@misc{asia_owid_adequacy_of_social_safety_net_programs_2022,
title = {Adequacy Of Social Safety Net Programs | Asia (Our World in Data)},
author = {Our World in Data},
year = {2022},
url = {https://ourworldindata.org/grapher/adequacy-of-social-safety-net-programs},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-owid-adequacy-of-social-safety-net-programs}}
}
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/adequacy-of-social-safety-net-programs
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