electricsheepafrica/africa-world-bank-agriculture-and-rural-development-indicators-for-algeria

--- annotations_creators: - no-annotation language_creators: - found language: - en license: cc-by-4.0 multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - original task_categories: - tabular-regression task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - agriculture-livestock - development - indicators - dza pretty_name: "Algeria - Agriculture and Rural Development" dataset_info: splits: - name: train num_examples: 1364 - name: test num_examples: 341 --- # Algeria - Agriculture and Rural Development **Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-agriculture-and-rural-development-indicators-for-algeria) · **License:** `cc-by` · **Updated:** 2026-03-27 --- ## Abstract Contains data from the World Bank's [data portal](http://data.worldbank.org/). There is also a [consolidated country dataset](https://data.humdata.org/dataset/world-bank-combined-indicators-for-algeria) on HDX. For the 70 percent of the world's poor who live in rural areas, agriculture is the main source of income and employment. But depletion and degradation of land and water pose serious challenges to producing enough food and other agricultural products to sustain livelihoods here and meet the needs of urban populations. Data presented here include measures of agricultural inputs, outputs, and productivity compiled by the UN's Food and Agriculture Organization. Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-27. Geographic scope: **DZA**. *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).* --- ## Dataset Characteristics | | | |---|---| | **Domain** | Food security and nutrition | | **Unit of observation** | Country-level aggregates | | **Rows (total)** | 1,706 | | **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) | | **Train split** | 1,364 rows | | **Test split** | 341 rows | | **Geographic scope** | DZA | | **Publisher** | World Bank Group | | **HDX last updated** | 2026-03-27 | --- ## Variables **Geographic** — `country_name` (Algeria), `country_iso3` (DZA), `year` (range 1960.0–2025.0). **Outcome / Measurement** — `value` (range -0.9894–37596599118.4309). **Identifier / Metadata** — `indicator_name` (Rural population (% of total population), Rural population, Rural population growth (annual %)), `indicator_code` (SP.RUR.TOTL.ZS, SP.RUR.TOTL, SP.RUR.TOTL.ZG), `esa_source` (HDX), `esa_processed` (2026-04-15). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-agriculture-and-rural-development-indicators-for-algeria") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ``` --- ## Schema | Column | Type | Null % | Range / Sample Values | |---|---|---|---| | `country_name` | object | 0.0% | Algeria | | `country_iso3` | object | 0.0% | DZA | | `year` | int64 | 0.0% | 1960.0 – 2025.0 (mean 1994.9578) | | `indicator_name` | object | 0.0% | Rural population (% of total population), Rural population, Rural population growth (annual %) | | `indicator_code` | object | 0.0% | SP.RUR.TOTL.ZS, SP.RUR.TOTL, SP.RUR.TOTL.ZG | | `value` | float64 | 0.0% | -0.9894 – 37596599118.4309 (mean 242524312.5719) | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-15 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `year` | 1960.0 | 2025.0 | 1994.9578 | 1997.0 | | `value` | -0.9894 | 37596599118.4309 | 242524312.5719 | 59.2733 | --- ## 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`. 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 World Bank Group 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/world-bank-agriculture-and-rural-development-indicators-for-algeria) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_world_bank_agriculture_and_rural_development_indicators_for_algeria, title = {Algeria - Agriculture and Rural Development}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-agriculture-and-rural-development-indicators-for-algeria}, 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.*注释创建者： - 无注释 语言创建者： - 爬取获取 语言： - 英语 许可证：CC BY 4.0 多语言属性： - 单语言 数据规模分类： - 1000 < 样本数 < 10000 源数据集： - 原创数据集 任务类别： - 表格回归 任务子项： - 无 标签： - 非洲 - 人道主义 - HDX（Humanitarian Data Exchange） - Electric Sheep Africa - 农业与畜牧业 - 发展 - 指标 - DZA（阿尔及利亚ISO 3166-1 alpha-3代码） 数据集名称："阿尔及利亚——农业与农村发展" 数据集信息： 数据划分： - 名称：训练集 样本数量：1364 - 名称：测试集 样本数量：341 # 阿尔及利亚——农业与农村发展 **发布方**：世界银行集团 · **来源**：[HDX](https://data.humdata.org/dataset/world-bank-agriculture-and-rural-development-indicators-for-algeria) · **许可证**：`cc-by` · **更新时间**：2026-03-27 --- ## 摘要 本数据集包含来自世界银行[数据门户](http://data.worldbank.org/)的相关数据。HDX平台上还提供了一份[整合后的国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-algeria)。 全球70%的贫困人口居住在农村地区，农业是其主要收入与就业来源。然而土地与水资源的耗竭与退化，对生产足够的粮食及其他农产品以维持当地生计、满足城市人口需求构成了严峻挑战。本数据集收录的内容包括由联合国粮食及农业组织汇编的农业投入、产出与生产率相关数据。 本数据集的每一行均代表国家层面的汇总数据。该数据集在HDX平台的最后更新时间为2026-03-27。地理覆盖范围：**DZA**。 *本数据集已由[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** | 粮食安全与营养 | | **观测单元** | 国家层面汇总数据 | | **总样本行数** | 1706 | | **列数** | 8（2个数值列、6个分类列、0个日期时间列） | | **训练集划分** | 1364行 | | **测试集划分** | 341行 | | **地理覆盖范围** | DZA | | **发布方** | 世界银行集团 | | **HDX最后更新时间** | 2026-03-27 | --- ## 变量说明 **地理类变量** — `country_name`（国家名称：阿尔及利亚）、`country_iso3`（国家ISO3代码：DZA）、`year`（年份范围：1960.0–2025.0）。 **结果/测量类变量** — `value`（数值范围：-0.9894–37596599118.4309）。 **标识符/元数据类变量** — `indicator_name`（指标名称：农村人口占总人口比例、农村总人口、农村人口年度增长率）、`indicator_code`（指标代码：SP.RUR.TOTL.ZS、SP.RUR.TOTL、SP.RUR.TOTL.ZG）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-15）。 --- ## 快速上手 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-agriculture-and-rural-development-indicators-for-algeria") 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 | 空值占比 | 取值范围/示例值 | |---|---|---|---| | `country_name` | 字符串型（object） | 0.0% | 阿尔及利亚 | | `country_iso3` | 字符串型（object） | 0.0% | DZA | | `year` | 64位整型（int64） | 0.0% | 1960.0 – 2025.0（均值：1994.9578） | | `indicator_name` | 字符串型（object） | 0.0% | 农村人口占总人口比例、农村总人口、农村人口年度增长率 | | `indicator_code` | 字符串型（object） | 0.0% | SP.RUR.TOTL.ZS、SP.RUR.TOTL、SP.RUR.TOTL.ZG | | `value` | 64位浮点型（float64） | 0.0% | -0.9894 – 37596599118.4309（均值：242524312.5719） | | `esa_source` | 字符串型（object） | 0.0% | HDX | | `esa_processed` | 字符串型（object） | 0.0% | 2026-04-15 | --- ## 数值型变量统计摘要 | 列名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `year` | 1960.0 | 2025.0 | 1994.9578 | 1997.0 | | `value` | -0.9894 | 37596599118.4309 | 242524312.5719 | 59.2733 | --- ## 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。列名均转换为小写并标准化为蛇形命名法（snake_case）。常见的缺失值标记符（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）被统一替换为`NaN`。本数据集以固定随机种子（42）按80/20的比例划分为训练集与测试集，并保存为Snappy压缩格式的Parquet文件。 --- ## 局限性说明 - 本数据集源自世界银行集团，Electric Sheep Africa未对其进行独立验证。 - 自动化清洗流程无法修正原始数据集中的错报值、定义不一致或原始采集过程中的抽样偏差问题。 - 如需了解发布方的方法论说明与注意事项，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/world-bank-agriculture-and-rural-development-indicators-for-algeria)。 --- ## 引用格式 bibtex @dataset{hdx_africa_world_bank_agriculture_and_rural_development_indicators_for_algeria, title = {Algeria - Agriculture and Rural Development}, author = {World Bank Group}, year = {2026}, url = {https://data.humdata.org/dataset/world-bank-agriculture-and-rural-development-indicators-for-algeria}, note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)} } --- *[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — 非洲的机器学习数据集基础设施。尼日利亚拉各斯。*