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electricsheepafrica/africa-world-bank-private-sector-indicators-for-federal-republic-of-somalia

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Hugging Face2026-04-07 更新2026-04-12 收录
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https://hf-mirror.com/datasets/electricsheepafrica/africa-world-bank-private-sector-indicators-for-federal-republic-of-somalia
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--- 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 - economics - hxl - indicators - som pretty_name: "Federal Republic of Somalia - Private Sector" dataset_info: splits: - name: train num_examples: 1540 - name: test num_examples: 385 --- # Federal Republic of Somalia - Private Sector **Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-private-sector-indicators-for-federal-republic-of-somalia) · **License:** `cc-by` · **Updated:** 2025-11-04 --- ## 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-federal-republic-of-somalia) on HDX. Private markets drive economic growth, tapping initiative and investment to create productive jobs and raise incomes. Trade is also a driver of economic growth as it integrates developing countries into the world economy and generates benefits for their people. Data on the private sector and trade are from the World Bank Group's Private Participation in Infrastructure Project Database, Enterprise Surveys, and Doing Business Indicators, as well as from the International Monetary Fund's Balance of Payments database and International Financial Statistics, the UN Commission on Trade and Development, the World Trade Organization, and various other sources. Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2025-11-04. Geographic scope: **SOM**. *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).* --- ## Dataset Characteristics | | | |---|---| | **Domain** | Market and price monitoring | | **Unit of observation** | Country-level aggregates | | **Rows (total)** | 1,925 | | **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) | | **Train split** | 1,540 rows | | **Test split** | 385 rows | | **Geographic scope** | SOM | | **Publisher** | World Bank Group | | **HDX last updated** | 2025-11-04 | --- ## Variables **Geographic** — `country_name` (Federal Republic of Somalia, #country+name), `country_iso3` (SOM, #country+code), `year` (range 1960.0–2024.0). **Outcome / Measurement** — `value` (range -0.0–4458000000.0). **Identifier / Metadata** — `indicator_name` (Merchandise imports by the reporting economy (current US$), Merchandise exports to low- and middle-income economies in Middle East & North Africa (% of total merchandise exports), Merchandise imports by the reporting economy, residual (% of total merchandise imports)), `indicator_code` (TM.VAL.MRCH.WL.CD, TX.VAL.MRCH.R4.ZS, TM.VAL.MRCH.RS.ZS), `esa_source` (HDX), `esa_processed` (2026-04-07). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-world-bank-private-sector-indicators-for-federal-republic-of-somalia") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ``` --- ## Schema | Column | Type | Null % | Range / Sample Values | |---|---|---|---| | `country_name` | object | 0.0% | Federal Republic of Somalia, #country+name | | `country_iso3` | object | 0.0% | SOM, #country+code | | `year` | float64 | 0.1% | 1960.0 – 2024.0 (mean 1995.5463) | | `indicator_name` | object | 0.0% | Merchandise imports by the reporting economy (current US$), Merchandise exports to low- and middle-income economies in Middle East & North Africa (% of total merchandise exports), Merchandise imports by the reporting economy, residual (% of total merchandise imports) | | `indicator_code` | object | 0.0% | TM.VAL.MRCH.WL.CD, TX.VAL.MRCH.R4.ZS, TM.VAL.MRCH.RS.ZS | | `value` | float64 | 0.1% | -0.0 – 4458000000.0 (mean 63783237.8639) | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-07 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `year` | 1960.0 | 2024.0 | 1995.5463 | 1997.0 | | `value` | -0.0 | 4458000000.0 | 63783237.8639 | 10.9619 | --- ## 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`. 2 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). 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-private-sector-indicators-for-federal-republic-of-somalia) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_world_bank_private_sector_indicators_for_federal_republic_of_somalia, title = {Federal Republic of Somalia - Private Sector}, author = {World Bank Group}, year = {2025}, url = {https://data.humdata.org/dataset/world-bank-private-sector-indicators-for-federal-republic-of-somalia}, 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.*
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