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country_name
stringclasses
42 values
country_iso3
stringclasses
42 values
year
int64
1.99k
2.02k
Absolute deaths from ambient PM2.5 air pollution- State of Global Air
int64
100
79.4k
Algeria
DZA
1,990
6,800
Algeria
DZA
1,995
7,000
Algeria
DZA
2,000
7,600
Algeria
DZA
2,005
8,000
Algeria
DZA
2,010
8,800
Algeria
DZA
2,015
12,000
Angola
AGO
1,990
8,600
Angola
AGO
1,995
8,900
Angola
AGO
2,000
9,700
Angola
AGO
2,005
9,000
Angola
AGO
2,010
9,200
Angola
AGO
2,015
10,200
Benin
BEN
1,990
4,100
Benin
BEN
1,995
4,500
Benin
BEN
2,000
4,700
Benin
BEN
2,005
4,100
Benin
BEN
2,010
4,300
Benin
BEN
2,015
4,300
Botswana
BWA
1,990
400
Botswana
BWA
1,995
500
Botswana
BWA
2,000
600
Botswana
BWA
2,005
700
Botswana
BWA
2,010
600
Botswana
BWA
2,015
700
Burkina Faso
BFA
1,990
7,700
Burkina Faso
BFA
1,995
7,900
Burkina Faso
BFA
2,000
8,200
Burkina Faso
BFA
2,005
7,400
Burkina Faso
BFA
2,010
7,300
Burkina Faso
BFA
2,015
6,700
Burundi
BDI
1,990
5,000
Burundi
BDI
1,995
5,200
Burundi
BDI
2,000
4,700
Burundi
BDI
2,005
3,900
Burundi
BDI
2,010
3,700
Burundi
BDI
2,015
4,600
Cameroon
CMR
1,990
10,000
Cameroon
CMR
1,995
11,600
Cameroon
CMR
2,000
13,500
Cameroon
CMR
2,005
12,800
Cameroon
CMR
2,010
12,800
Cameroon
CMR
2,015
12,900
Cape Verde
CPV
1,990
200
Cape Verde
CPV
1,995
200
Cape Verde
CPV
2,000
200
Cape Verde
CPV
2,005
200
Cape Verde
CPV
2,010
200
Cape Verde
CPV
2,015
200
Central African Republic
CAF
1,990
3,000
Central African Republic
CAF
1,995
3,300
Central African Republic
CAF
2,000
3,600
Central African Republic
CAF
2,005
3,700
Central African Republic
CAF
2,010
3,800
Central African Republic
CAF
2,015
4,100
Chad
TCD
1,990
4,900
Chad
TCD
1,995
5,600
Chad
TCD
2,000
7,000
Chad
TCD
2,005
7,200
Chad
TCD
2,010
8,100
Chad
TCD
2,015
7,800
Comoros
COM
1,990
200
Comoros
COM
1,995
200
Comoros
COM
2,000
200
Comoros
COM
2,005
100
Comoros
COM
2,010
100
Comoros
COM
2,015
100
Congo
COG
1,990
1,800
Congo
COG
1,995
2,100
Congo
COG
2,000
2,400
Congo
COG
2,005
2,100
Congo
COG
2,010
2,100
Congo
COG
2,015
2,400
Cote d'Ivoire
CIV
1,990
6,100
Cote d'Ivoire
CIV
1,995
8,000
Cote d'Ivoire
CIV
2,000
8,700
Cote d'Ivoire
CIV
2,005
7,700
Cote d'Ivoire
CIV
2,010
7,800
Cote d'Ivoire
CIV
2,015
7,700
Djibouti
DJI
1,990
300
Djibouti
DJI
1,995
300
Djibouti
DJI
2,000
400
Djibouti
DJI
2,005
400
Djibouti
DJI
2,010
400
Djibouti
DJI
2,015
400
Egypt
EGY
1,990
52,300
Egypt
EGY
1,995
47,600
Egypt
EGY
2,000
43,100
Egypt
EGY
2,005
48,300
Egypt
EGY
2,010
57,400
Egypt
EGY
2,015
60,200
Equatorial Guinea
GNQ
1,990
400
Equatorial Guinea
GNQ
1,995
400
Equatorial Guinea
GNQ
2,000
400
Equatorial Guinea
GNQ
2,005
300
Equatorial Guinea
GNQ
2,010
300
Equatorial Guinea
GNQ
2,015
400
Eritrea
ERI
1,990
1,900
Eritrea
ERI
1,995
1,400
Eritrea
ERI
2,000
1,400
Eritrea
ERI
2,005
1,600
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Absolute Number Of Deaths From Ambient Particulate Air Pollution | Africa (Our World in Data)

🌍 308 observations · 52 Africa countries · 1990–2015 · Repackaged by Electric Sheep Africa

rows countries years license

TL;DR

This dataset contains 308 observations of Absolute Number Of Deaths From Ambient Particulate Air Pollution data across 52 Africa countries, spanning 1990–2015.

About the source

  • Source: Our World in Data
  • Publisher: Our World in Data
  • License: cc-by-4.0
  • Topic: Absolute Number Of Deaths From Ambient Particulate Air Pollution

Geographic coverage

52 Africa countries · top rows shown below, sorted by row count:

Country Rows First year Last year
AGO 6 1990 2015
BDI 6 1990 2015
BEN 6 1990 2015
BFA 6 1990 2015
BWA 6 1990 2015
CAF 6 1990 2015
CIV 6 1990 2015
CMR 6 1990 2015
COG 6 1990 2015
COM 6 1990 2015
CPV 6 1990 2015
DJI 6 1990 2015
DZA 6 1990 2015
EGY 6 1990 2015
ERI 6 1990 2015
... 37 more countries

Schema

Column Type Description Example
country_name string Algeria
country_iso3 string DZA
year int64 1990
Absolute deaths from ambient PM2.5 air pollution- State of Global Air int64 6800

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-owid-absolute-number-of-deaths-from-ambient-particulate-air-pollution")
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="Absolute deaths from ambient PM2.5 air pollution- State of Global Air")

Citation

@misc{africa_owid_absolute_number_of_deaths_from_ambient_particulate_air_pollution_2015,
  title        = {Absolute Number Of Deaths From Ambient Particulate Air Pollution | Africa (Our World in Data)},
  author       = {Our World in Data},
  year         = {2015},
  url          = {https://ourworldindata.org/grapher/absolute-number-of-deaths-from-ambient-particulate-air-pollution},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-owid-absolute-number-of-deaths-from-ambient-particulate-air-pollution}}
}

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/absolute-number-of-deaths-from-ambient-particulate-air-pollution

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