electricsheepafrica/africa-ben-climate-trace

--- annotations_creators: - no-annotation language_creators: - found language: - en license: cc-by-4.0 multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - tabular-classification - tabular-regression task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - climate-weather - environment - points-of-interest-poi - ben pretty_name: "Benin: Greenhouse Gas and Air Pollutant Emissions" dataset_info: splits: - name: train num_examples: 8666 - name: test num_examples: 2166 --- # Benin: Greenhouse Gas and Air Pollutant Emissions **Publisher:** Climate TRACE · **Source:** [HDX](https://data.humdata.org/dataset/ben-climate-trace) · **License:** `cc-by` · **Updated:** 2026-03-30 --- ## Abstract Climate TRACE is a non-profit coalition of organizations building a timely, open, and accessible inventory of exactly where greenhouse gas emissions are coming from. Climate TRACE estimates greenhouse gas (GHG) and air pollutant emissions for over 2.7 million sources (from over 744 million assets), and every single country globally. The Climate TRACE emissions inventory includes: - Annual country-level emissions by sub-sector and by gas beginning in 2015 - Monthly source-level emissions by sub-sector and gas beginning in 2021 and confidence - Emissions source ownership where and when available. Each row in this dataset represents time-series observations. Data was last updated on HDX on 2026-03-30. Geographic scope: **BEN**. *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).* --- ## Dataset Characteristics | | | |---|---| | **Domain** | Climate and environment | | **Unit of observation** | Time-series observations | | **Rows (total)** | 10,833 | | **Columns** | 13 (4 numeric, 9 categorical, 0 datetime) | | **Train split** | 8,666 rows | | **Test split** | 2,166 rows | | **Geographic scope** | BEN | | **Publisher** | Climate TRACE | | **HDX last updated** | 2026-03-30 | --- ## Variables **Geographic** — `year` (range 2024.0–2026.0), `emissionsquantity` (range 0.0–19335.3887). **Temporal** — `month` (range 1.0–12.0). **Identifier / Metadata** — `full_name` (Benin, Ouémé Department, BEN, Collines Department, BEN), `id` (BEN, BEN.10_1, BEN.5_1), `level_0_id` (BEN), `level_1_id` (BEN.10_1, BEN.5_1, BEN.3_1), `name` (Benin, Ouémé Department, Collines Department) and 2 others. **Other** — `level` (range 0.0–1.0), `sector` (agriculture, waste, transportation), `gas` (ch4). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-ben-climate-trace") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ``` --- ## Schema | Column | Type | Null % | Range / Sample Values | |---|---|---|---| | `full_name` | object | 0.0% | Benin, Ouémé Department, BEN, Collines Department, BEN | | `id` | object | 0.0% | BEN, BEN.10_1, BEN.5_1 | | `level` | int64 | 0.0% | 0.0 – 1.0 (mean 0.9154) | | `level_0_id` | object | 0.0% | BEN | | `level_1_id` | object | 8.5% | BEN.10_1, BEN.5_1, BEN.3_1 | | `name` | object | 0.0% | Benin, Ouémé Department, Collines Department | | `year` | int64 | 0.0% | 2024.0 – 2026.0 (mean 2024.6106) | | `month` | int64 | 0.0% | 1.0 – 12.0 (mean 6.7019) | | `sector` | object | 0.0% | agriculture, waste, transportation | | `gas` | object | 0.0% | ch4 | | `emissionsquantity` | float64 | 0.0% | 0.0 – 19335.3887 (mean 200.2801) | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-05 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `level` | 0.0 | 1.0 | 0.9154 | 1.0 | | `year` | 2024.0 | 2026.0 | 2024.6106 | 2025.0 | | `month` | 1.0 | 12.0 | 6.7019 | 7.0 | | `emissionsquantity` | 0.0 | 19335.3887 | 200.2801 | 0.3102 | --- ## Curation Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`) were unified to `NaN`. 1 column(s) with >80% missing values were removed: `level_2_id`. 11,293 exact duplicate rows were removed. The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet. --- ## Limitations - Data originates from Climate TRACE and has not been independently validated by ESA. - Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection. - Refer to the [original HDX dataset page](https://data.humdata.org/dataset/ben-climate-trace) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_ben_climate_trace, title = {Benin: Greenhouse Gas and Air Pollutant Emissions}, author = {Climate TRACE}, year = {2026}, url = {https://data.humdata.org/dataset/ben-climate-trace}, note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)} } ``` --- *[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*--- annotations_creators: - 无注释（no-annotation） language_creators: - 获取型（found） language: - 英语（en） license: 知识共享署名4.0（cc-by-4.0） multilinguality: - 单语言（monolingual） size_categories: - 10K<n<100K（1万至10万条数据） source_datasets: - 原始数据集（original） task_categories: - 表格分类（tabular-classification） - 表格回归（tabular-regression） task_ids: [] tags: - 非洲（africa） - 人道主义（humanitarian） - HDX - Electric Sheep Africa（electric-sheep-africa） - 气候与天气（climate-weather） - 环境（environment） - 兴趣点（points-of-interest-poi） - 贝宁国家代码（ben） pretty_name: "贝宁：温室气体与空气污染物排放（Benin: Greenhouse Gas and Air Pollutant Emissions）" dataset_info: splits: - name: train num_examples: 8666 - name: test num_examples: 2166 --- # 贝宁：温室气体与空气污染物排放 **发布方**：Climate TRACE · **数据源**：[HDX](https://data.humdata.org/dataset/ben-climate-trace) · **许可证**：`cc-by` · **最后更新时间**：2026-03-30 --- ## 摘要 Climate TRACE是一个由多家机构组成的非营利性联盟，致力于构建及时、开放且可获取的温室气体排放源精准清单。该联盟针对全球所有国家的超270万个排放源（源自超7.44亿个资产点）估算温室气体（GHG）与空气污染物排放量。 Climate TRACE的排放清单包含以下内容： - 2015年起按子行业与气体类型划分的年度国家级排放量数据 - 2021年起按子行业与气体类型划分的月度排放源级排放量数据及置信度信息 - 可获取时的排放源所属权信息。 本数据集的每一行均代表时序观测数据。该数据最后于2026-03-30在HDX平台更新。地理覆盖范围：**BEN（贝宁）**。 *本数据集由[Electric Sheep Africa](https://huggingface.co/electricsheepafrica)整理为适合机器学习的Parquet格式。* --- ## 数据集特征 | | | |---|---| | **领域** | 气候与环境 | | **观测单元** | 时序观测数据 | | **总数据行数** | 10833 | | **列数** | 13列（4个数值型、9个分类型、0个日期时间型） | | **训练集划分** | 8666条数据 | | **测试集划分** | 2166条数据 | | **地理覆盖范围** | BEN（贝宁） | | **发布方** | Climate TRACE | | **HDX平台最后更新时间** | 2026-03-30 | --- ## 字段说明 **地理相关字段** — `year`（年份，取值范围2024.0–2026.0）、`emissionsquantity`（排放量，取值范围0.0–19335.3887）。 **时间相关字段** — `month`（月份，取值范围1.0–12.0）。 **标识符/元数据字段** — `full_name`（完整名称，如贝宁、韦梅省、BEN、丘陵省、BEN）、`id`（标识符，如BEN、BEN.10_1、BEN.5_1）、`level_0_id`（层级0标识符，如BEN）、`level_1_id`（层级1标识符，如BEN.10_1、BEN.5_1、BEN.3_1）、`name`（名称，如贝宁、韦梅省、丘陵省）等共2个额外字段。 **其他字段** — `level`（层级，取值范围0.0–1.0）、`sector`（行业领域，涵盖农业、废弃物处理、交通运输）、`gas`（气体类型，仅甲烷ch4）。 --- ## 快速上手 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-ben-climate-trace") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() --- ## 数据结构 | 列名 | 数据类型 | 缺失占比 | 取值范围/示例值 | |---|---|---|---| | `full_name` | 对象型（object） | 0.0% | 贝宁、韦梅省、BEN、丘陵省、BEN | | `id` | 对象型（object） | 0.0% | BEN、BEN.10_1、BEN.5_1 | | `level` | 整型（int64） | 0.0% | 0.0 – 1.0（均值0.9154） | | `level_0_id` | 对象型（object） | 0.0% | BEN | | `level_1_id` | 对象型（object） | 8.5% | BEN.10_1、BEN.5_1、BEN.3_1 | | `name` | 对象型（object） | 0.0% | 贝宁、韦梅省、丘陵省 | | `year` | 整型（int64） | 0.0% | 2024.0 – 2026.0（均值2024.6106） | | `month` | 整型（int64） | 0.0% | 1.0 – 12.0（均值6.7019） | | `sector` | 对象型（object） | 0.0% | 农业、废弃物处理、交通运输 | | `gas` | 对象型（object） | 0.0% | 甲烷（ch4） | | `emissionsquantity` | 浮点型（float64） | 0.0% | 0.0 – 19335.3887（均值200.2801） | | `esa_source` | 对象型（object） | 0.0% | HDX | | `esa_processed` | 对象型（object） | 0.0% | 2026-04-05 | --- ## 数值型字段统计 | 列名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `level` | 0.0 | 1.0 | 0.9154 | 1.0 | | `year` | 2024.0 | 2026.0 | 2024.6106 | 2025.0 | | `month` | 1.0 | 12.0 | 6.7019 | 7.0 | | `emissionsquantity` | 0.0 | 19335.3887 | 200.2801 | 0.3102 | --- ## 数据整理流程 原始数据通过CKAN API从HDX平台下载并转换为Parquet格式。列名被统一转为小写并标准化为蛇形命名法（snake_case）。常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）被统一替换为`NaN`。移除了1列缺失值占比超过80%的字段：`level_2_id`。移除了11293条完全重复的数据行。本数据集使用固定随机种子（42）按80/20的比例划分为训练集与测试集，并以Snappy压缩的Parquet格式存储。 --- ## 局限性说明 - 本数据集源自Climate TRACE，尚未经Electric Sheep Africa（ESA）独立验证。 - 自动化清洗流程无法修正原始数据集中的错报值、定义不一致或采样偏差问题。 - 如需查看发布方的方法说明与免责条款，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/ben-climate-trace)。 --- ## 引用格式 bibtex @dataset{hdx_africa_ben_climate_trace, title = {Benin: Greenhouse Gas and Air Pollutant Emissions}, author = {Climate TRACE}, year = {2026}, url = {https://data.humdata.org/dataset/ben-climate-trace}, note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)} } --- *[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — 非洲机器学习数据集基础设施。尼日利亚拉各斯。*