| --- |
| license: cc-by-4.0 |
| language: |
| - en |
| task_categories: |
| - tabular-regression |
| - time-series-forecasting |
| multilinguality: monolingual |
| size_categories: |
| - 10K<n<100K |
| tags: |
| - tabular |
| - csv |
| - africa |
| - congo |
| - official-statistics |
| - open-data |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-00000-of-00001.parquet |
| pretty_name: "Congo: Greenhouse Gas and Air Pollutant Emissions | Africa (Congo official open data)" |
| --- |
| |
| # Congo: Greenhouse Gas and Air Pollutant Emissions | Africa (Congo official open data) |
|
|
| 30,888 rows - 1 Africa country - 2024-2026 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica) |
|
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|
|
| ## TL;DR |
|
|
| This dataset packages one official `CSV` resource from **Congo** as |
| ML-ready Parquet. The source file is the provenance boundary; all usable |
| indicators or tabular columns from the resource stay together in this repo. |
|
|
| ## About the source |
|
|
| - **Source:** [Congo: Greenhouse Gas and Air Pollutant Emissions](https://data.humdata.org/dataset/cog-climate-trace) |
| - **Publisher:** Climate TRACE |
| - **Resource:** [cog_co2e_20yr_city.csv](https://data.humdata.org/dataset/90235eee-452c-401e-b8b0-a9d4ae4d91b1/resource/1130752c-cc24-450d-b994-78a629c397c3/download/cog_co2e_20yr_city.csv) |
| - **Format:** `CSV` |
| - **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
| - **Packaging mode:** `indicator_long` |
|
|
| ## Geographic coverage |
|
|
| 1 Africa country: |
|
|
| | Country | Rows | First year | Last year | Name | |
| |---------|-----:|-----------:|----------:|------| |
| | `COG` | 30,888 | 2024 | 2026 | `Congo` | |
|
|
| ## Indicators or Resource Contents |
|
|
| - `congo-greenhouse-gas-and-air-pollutant-emissions-month-3202e812` - Congo: Greenhouse Gas and Air Pollutant Emissions - month |
| - `congo-greenhouse-gas-and-air-pollutant-emissions-emissionsquantity-a38e3552` - Congo: Greenhouse Gas and Air Pollutant Emissions - emissionsquantity |
|
|
| ## Schema |
|
|
| | Column | Type | Description | Example | |
| |--------|------|-------------|---------| |
| | `indicator_id` | `string` | Stable indicator identifier. | `congo-greenhouse-gas-and-air-pollutant-emissions-month-3202e812` | |
| | `indicator_name` | `string` | Human-readable indicator name. | `Congo: Greenhouse Gas and Air Pollutant Emissions - month` | |
| | `country_iso3` | `string` | ISO3 country code. | `COG` | |
| | `country_name` | `string` | Country name. | `Congo` | |
| | `year` | `Int64` | Observation year. | `2024` | |
| | `value` | `float64` | Numeric observation value. | `8.0` | |
| | `unit` | `string` | Measurement unit, when available. | `source_units_unspecified` | |
| | `dimension_id` | `string` | Source dimension. | `ghs-fua_1758` | |
| | `dimension_name` | `string` | Source dimension. | `Bétou Urban Area, COG` | |
| | `dimension_country` | `string` | Source dimension. | `COG` | |
| | `dimension_alternatenames` | `string` | Source dimension. | `['Bétou']` | |
| | `dimension_sector` | `string` | Source dimension. | `agriculture` | |
| | `dimension_gas` | `string` | Source dimension. | `co2e_20yr` | |
| | `source_period_start_year` | `Int64` | First year inferred from source resource metadata. | `2015` | |
| | `source_period_end_year` | `Int64` | Last year inferred from source resource metadata. | `2021` | |
| | `source_period_label` | `category` | Human-readable period inferred from source resource metadata. | `2015-2021` | |
| | `source_provider` | `category` | Publishing organization. | `Climate TRACE` | |
| | `source_dataset` | `category` | Source package title. | `Congo: Greenhouse Gas and Air Pollutant Emissions` | |
| | `source_resource` | `category` | Source resource title. | `cog_co2e_20yr_city.csv` | |
| | `source_package_id` | `category` | CKAN package UUID. | `90235eee-452c-401e-b8b0-a9d4ae4d91b1` | |
| | `source_resource_id` | `category` | CKAN resource UUID. | `1130752c-cc24-450d-b994-78a629c397c3` | |
| | `source_url` | `category` | Original source resource URL. | `https://data.humdata.org/dataset/90235eee-452c-401e-b8b0-a9d4ae4d91b1/re` | |
| | `license_id` | `category` | Source license identifier. | `cc-by` | |
| | `retrieved_at` | `category` | UTC retrieval timestamp. | `2026-08-16T12:36:20Z` | |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("electricsheepafrica/africa-congo-congo-greenhouse-gas-and-air-pollutant-emissions-2b8a7b27") |
| df = ds["train"].to_pandas() |
| print(df.head()) |
| ``` |
|
|
| ### Filter to one country |
|
|
| ```python |
| sample_country = df[df["country_iso3"] == "COG"] |
| ``` |
|
|
| ### Work with indicators |
|
|
| ```python |
| if "indicator_id" in df.columns: |
| print(df["indicator_id"].value_counts().head()) |
| sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns]) |
| ``` |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{electric_sheep_africa_africa_congo_congo_greenhouse_gas_and_air_pollutant_emissions_2b8a7b27_2026, |
| title = {Congo: Greenhouse Gas and Air Pollutant Emissions | Africa (Congo official open data)}, |
| author = {Climate TRACE}, |
| year = {2026}, |
| url = {https://data.humdata.org/dataset/cog-climate-trace}, |
| publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa}, |
| howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-congo-congo-greenhouse-gas-and-air-pollutant-emissions-2b8a7b27}} |
| } |
| ``` |
|
|
| ## License |
|
|
| Released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). |
|
|
| Original data (c) Climate TRACE. 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 Hugging Face. 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](https://huggingface.co/electricsheepafrica) |
|
|
| --- |
|
|
| Provenance: ingested 2026-08-16 via the Electric Sheep pipeline. Source URL: |
| https://data.humdata.org/dataset/90235eee-452c-401e-b8b0-a9d4ae4d91b1/resource/1130752c-cc24-450d-b994-78a629c397c3/download/cog_co2e_20yr_city.csv |
| |
