electricsheepafrica/africa-county-government-expenditure-2013-2014

--- annotations_creators: - no-annotation language_creators: - found language: - en license: other multilinguality: - monolingual size_categories: - n<1K source_datasets: - original task_categories: - tabular-regression task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - economics - governance-and-civil-society - ken pretty_name: "County Government Expenditure 2013_2014" dataset_info: splits: - name: train num_examples: 37 - name: test num_examples: 9 --- # County Government Expenditure 2013_2014 **Publisher:** Kenya National Bureau of Statistics (inactive) · **Source:** [HDX](https://data.humdata.org/dataset/county-government-expenditure-2013-2014) · **License:** `other-pd-nr` · **Updated:** 2025-02-06 --- ## Abstract The County Government Expenditure for the financial years of 2013_2014 Each row in this dataset represents tabular records. Data was last updated on HDX on 2025-02-06. Geographic scope: **KEN**. *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).* --- ## Dataset Characteristics | | | |---|---| | **Domain** | Humanitarian and development data | | **Unit of observation** | Tabular records | | **Rows (total)** | 47 | | **Columns** | 17 (14 numeric, 3 categorical, 0 datetime) | | **Train split** | 37 rows | | **Test split** | 9 rows | | **Geographic scope** | KEN | | **Publisher** | Kenya National Bureau of Statistics (inactive) | | **HDX last updated** | 2025-02-06 | --- ## Variables **Geographic** — `county` (Baringo, Nyeri, Migori), `compensation_of_employees` (range 76.4756–4573.1104), `debt_repayment_pending_bills` (range 0.0–1806.4711), `hospitality_supplies_and_services` (range 2.5702–76.0747), `other_operating_expenses` (range 0.0–534.7113) and 2 others. **Outcome / Measurement** — `transportation_costs` (range 13.1841–131.1065). **Identifier / Metadata** — `esa_source` (HDX), `esa_processed` (2026-04-07). **Other** — `acquisition_of_non_financial_assets` (range 0.0–1427.0577), `communication_supplies_and_services` (range 0.0–20.2), `fuel_oil_and_lubricants` (range 0.0–29.6458), `office_and_general_supplies_and_services` (range 0.0–111.709), `printing_advertising_and_information_supplies_and_services` (range 0.0–65.7295) and 2 others. --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-county-government-expenditure-2013-2014") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ``` --- ## Schema | Column | Type | Null % | Range / Sample Values | |---|---|---|---| | `county` | object | 0.0% | Baringo, Nyeri, Migori | | `acquisition_of_non_financial_assets` | float64 | 0.0% | 0.0 – 1427.0577 (mean 154.19) | | `communication_supplies_and_services` | float64 | 0.0% | 0.0 – 20.2 (mean 4.7657) | | `compensation_of_employees` | float64 | 0.0% | 76.4756 – 4573.1104 (mean 462.9877) | | `debt_repayment_pending_bills` | float64 | 0.0% | 0.0 – 1806.4711 (mean 46.818) | | `fuel_oil_and_lubricants` | float64 | 0.0% | 0.0 – 29.6458 (mean 10.5228) | | `hospitality_supplies_and_services` | float64 | 0.0% | 2.5702 – 76.0747 (mean 19.3012) | | `office_and_general_supplies_and_services` | float64 | 0.0% | 0.0 – 111.709 (mean 14.8917) | | `other_operating_expenses` | float64 | 0.0% | 0.0 – 534.7113 (mean 83.4789) | | `printing_advertising_and_information_supplies_and_services` | float64 | 0.0% | 0.0 – 65.7295 (mean 14.1381) | | `routine_maintenance` | float64 | 0.0% | 0.0 – 93.0878 (mean 20.7169) | | `total_expenditure` | float64 | 0.0% | 169.9241 – 8450.7911 (mean 918.4539) | | `training_expenses` | float64 | 0.0% | 0.02 – 45.8874 (mean 12.1757) | | `transportation_costs` | float64 | 0.0% | 13.1841 – 131.1065 (mean 60.7137) | | `utilities_supplies_and_services` | float64 | 0.0% | 0.0 – 142.8074 (mean 13.7533) | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-07 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `acquisition_of_non_financial_assets` | 0.0 | 1427.0577 | 154.19 | 103.3798 | | `communication_supplies_and_services` | 0.0 | 20.2 | 4.7657 | 2.7118 | | `compensation_of_employees` | 76.4756 | 4573.1104 | 462.9877 | 308.559 | | `debt_repayment_pending_bills` | 0.0 | 1806.4711 | 46.818 | 0.0 | | `fuel_oil_and_lubricants` | 0.0 | 29.6458 | 10.5228 | 8.4745 | | `hospitality_supplies_and_services` | 2.5702 | 76.0747 | 19.3012 | 16.6931 | | `office_and_general_supplies_and_services` | 0.0 | 111.709 | 14.8917 | 8.0412 | | `other_operating_expenses` | 0.0 | 534.7113 | 83.4789 | 54.152 | | `printing_advertising_and_information_supplies_and_services` | 0.0 | 65.7295 | 14.1381 | 9.9243 | | `routine_maintenance` | 0.0 | 93.0878 | 20.7169 | 13.5212 | | `total_expenditure` | 169.9241 | 8450.7911 | 918.4539 | 691.3839 | | `training_expenses` | 0.02 | 45.8874 | 12.1757 | 9.9596 | | `transportation_costs` | 13.1841 | 131.1065 | 60.7137 | 53.6236 | | `utilities_supplies_and_services` | 0.0 | 142.8074 | 13.7533 | 4.8487 | --- ## 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 Kenya National Bureau of Statistics (inactive) 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/county-government-expenditure-2013-2014) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_county_government_expenditure_2013_2014, title = {County Government Expenditure 2013_2014}, author = {Kenya National Bureau of Statistics (inactive)}, year = {2025}, url = {https://data.humdata.org/dataset/county-government-expenditure-2013-2014}, 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 language_creators: - 爬取获取 language: - 英语 license: - 其他 multilinguality: - 单语言 size_categories: - 少于1000条 source_datasets: - 原创数据集 task_categories: - 表格回归 task_ids: - 无 tags: - 非洲 - 人道主义 - HDX（Humanitarian Data Exchange） - Electric Sheep Africa - 经济学 - 治理与公民社会 - 肯尼亚（KEN） pretty_name: "2013_2014年县政府支出" dataset_info: splits: - name: train num_examples: 37 - name: test num_examples: 9 # 2013_2014年县政府支出 **发布方**：肯尼亚国家统计局（已停用） · **数据源**：[HDX（Humanitarian Data Exchange）](https://data.humdata.org/dataset/county-government-expenditure-2013-2014) · **许可证**：`other-pd-nr` · **最后更新**：2025-02-06 --- ## 摘要 本数据集收录2013至2014财年的县政府支出数据。 数据集中每一行均代表一条表格记录。本数据最后于HDX平台更新于2025年2月6日。地理覆盖范围：**肯尼亚（KEN）**。 *本数据集经[Electric Sheep Africa](https://huggingface.co/electricsheepafrica)整理为适配机器学习的Parquet格式。* --- ## 数据集特征 | | | |---|---| | **领域** | 人道主义与发展数据 | | **观测单元** | 表格记录 | | **总行数** | 47 | | **列数** | 17（14个数值型、3个分类型、0个日期时间型） | | **训练集划分** | 37条记录 | | **测试集划分** | 9条记录 | | **地理覆盖范围** | 肯尼亚（KEN） | | **发布方** | 肯尼亚国家统计局（已停用） | | **HDX平台最后更新时间** | 2025-02-06 | --- ## 变量 **地理类** — `county`（巴宁戈、涅里、米格里等郡名）、`compensation_of_employees`（值域76.4756–4573.1104）、`debt_repayment_pending_bills`（值域0.0–1806.4711）、`hospitality_supplies_and_services`（值域2.5702–76.0747）、`other_operating_expenses`（值域0.0–534.7113）及另外2个字段。 **结果/测量类** — `transportation_costs`（值域13.1841–131.1065）。 **标识符/元数据类** — `esa_source`（HDX）、`esa_processed`（2026-04-07）。 **其他类** — `acquisition_of_non_financial_assets`（值域0.0–1427.0577）、`communication_supplies_and_services`（值域0.0–20.2）、`fuel_oil_and_lubricants`（值域0.0–29.6458）、`office_and_general_supplies_and_services`（值域0.0–111.709）、`printing_advertising_and_information_supplies_and_services`（值域0.0–65.7295）及另外2个字段。 --- ## 快速上手 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-county-government-expenditure-2013-2014") 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 | 值域/示例值 | |---|---|---|---| | `county` | 字符串型（object） | 0.0% | 巴宁戈、涅里、米格里 | | `acquisition_of_non_financial_assets` | 浮点型（float64） | 0.0% | 0.0 – 1427.0577（均值154.19） | | `communication_supplies_and_services` | 浮点型（float64） | 0.0% | 0.0 – 20.2（均值4.7657） | | `compensation_of_employees` | 浮点型（float64） | 0.0% | 76.4756 – 4573.1104（均值462.9877） | | `debt_repayment_pending_bills` | 浮点型（float64） | 0.0% | 0.0 – 1806.4711（均值46.818） | | `fuel_oil_and_lubricants` | 浮点型（float64） | 0.0% | 0.0 – 29.6458（均值10.5228） | | `hospitality_supplies_and_services` | 浮点型（float64） | 0.0% | 2.5702 – 76.0747（均值19.3012） | | `office_and_general_supplies_and_services` | 浮点型（float64） | 0.0% | 0.0 – 111.709（均值14.8917） | | `other_operating_expenses` | 浮点型（float64） | 0.0% | 0.0 – 534.7113（均值83.4789） | | `printing_advertising_and_information_supplies_and_services` | 浮点型（float64） | 0.0% | 0.0 – 65.7295（均值14.1381） | | `routine_maintenance` | 浮点型（float64） | 0.0% | 0.0 – 93.0878（均值20.7169） | | `total_expenditure` | 浮点型（float64） | 0.0% | 169.9241 – 8450.7911（均值918.4539） | | `training_expenses` | 浮点型（float64） | 0.0% | 0.02 – 45.8874（均值12.1757） | | `transportation_costs` | 浮点型（float64） | 0.0% | 13.1841 – 131.1065（均值60.7137） | | `utilities_supplies_and_services` | 浮点型（float64） | 0.0% | 0.0 – 142.8074（均值13.7533） | | `esa_source` | 字符串型（object） | 0.0% | HDX | | `esa_processed` | 字符串型（object） | 0.0% | 2026-04-07 | --- ## 数值统计摘要 | 列名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `acquisition_of_non_financial_assets` | 0.0 | 1427.0577 | 154.19 | 103.3798 | | `communication_supplies_and_services` | 0.0 | 20.2 | 4.7657 | 2.7118 | | `compensation_of_employees` | 76.4756 | 4573.1104 | 462.9877 | 308.559 | | `debt_repayment_pending_bills` | 0.0 | 1806.4711 | 46.818 | 0.0 | | `fuel_oil_and_lubricants` | 0.0 | 29.6458 | 10.5228 | 8.4745 | | `hospitality_supplies_and_services` | 2.5702 | 76.0747 | 19.3012 | 16.6931 | | `office_and_general_supplies_and_services` | 0.0 | 111.709 | 14.8917 | 8.0412 | | `other_operating_expenses` | 0.0 | 534.7113 | 83.4789 | 54.152 | | `printing_advertising_and_information_supplies_and_services` | 0.0 | 65.7295 | 14.1381 | 9.9243 | | `routine_maintenance` | 0.0 | 93.0878 | 20.7169 | 13.5212 | | `total_expenditure` | 169.9241 | 8450.7911 | 918.4539 | 691.3839 | | `training_expenses` | 0.02 | 45.8874 | 12.1757 | 9.9596 | | `transportation_costs` | 13.1841 | 131.1065 | 60.7137 | 53.6236 | | `utilities_supplies_and_services` | 0.0 | 142.8074 | 13.7533 | 4.8487 | --- ## 数据整理 原始数据通过CKAN API从HDX平台下载，并转换为Parquet格式。列名统一转换为小写并采用蛇形命名法（snake_case）进行标准化。常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）被统一替换为`NaN`。本数据集使用固定随机种子（42）按照80/20的比例划分为训练集与测试集，并以Snappy压缩格式的Parquet文件保存。 --- ## 局限性 - 本数据源自肯尼亚国家统计局（已停用），未经过Electric Sheep Africa的独立验证。 - 自动化清洗流程无法修正原始数据收集中的错报值、定义不一致或抽样偏差问题。 - 请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/county-government-expenditure-2013-2014)获取发布方提供的方法论说明与免责声明。 --- ## 引用 bibtex @dataset{hdx_africa_county_government_expenditure_2013_2014, title = {2013_2014年县政府支出}, author = {肯尼亚国家统计局（已停用)}, year = {2025}, url = {https://data.humdata.org/dataset/county-government-expenditure-2013-2014}, note = {经Electric Sheep Africa（https://huggingface.co/electricsheepafrica）重新打包以适配机器学习应用} } --- *[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。*