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Browse files- README.md +149 -0
- data/train-00000-of-00001.parquet +3 -0
- metadata/source_snapshot.json +60 -0
README.md
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| 1 |
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---
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| 2 |
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license: cc-by-4.0
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| 3 |
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language:
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- en
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| 5 |
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task_categories:
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- tabular-classification
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- tabular-regression
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multilinguality: monolingual
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size_categories:
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- 10K<n<100K
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tags:
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- tabular
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- csv
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- africa
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- mali
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- official-statistics
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- open-data
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-00000-of-00001.parquet
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pretty_name: "Small Business Surveys - Aggregated Data | Africa (Mali official open data)"
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---
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# Small Business Surveys - Aggregated Data | Africa (Mali official open data)
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19,776 rows - 1 Africa country - 2022 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
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## TL;DR
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This dataset packages one official `CSV` resource from **Mali** as
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ML-ready Parquet. The source file is the provenance boundary; all usable
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indicators or tabular columns from the resource stay together in this repo.
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## About the source
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- **Source:** [Small Business Surveys - Aggregated Data](https://data.humdata.org/dataset/future-of-business-survey-aggregated-data)
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- **Publisher:** AI for Good at Meta
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- **Resource:** [aggregate_smb_leaders.csv](https://data.humdata.org/dataset/8bd3d109-d33d-4349-90c4-464c9d7ccb66/resource/564d4e73-207b-462f-9bae-a80ee8780967/download/aggregate_smb_leaders.csv)
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- **Format:** `CSV`
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- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
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- **Packaging mode:** `tabular_resource`
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## Geographic coverage
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1 Africa country:
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| Country | Rows | First year | Last year | Name |
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|---------|-----:|-----------:|----------:|------|
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| `MLI` | 19,776 | 2022 | 2022 | `Mali` |
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## Indicators or Resource Contents
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- This source file is packaged as a normalized tabular resource.
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## Schema
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| Column | Type | Description | Example |
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|--------|------|-------------|---------|
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| `source_record_id` | `string` | Stable row identifier for tabular resources. | `564d4e73-207b-462f-9bae-a80ee8780967:0` |
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| `country_iso3` | `category` | ISO3 country code. | `MLI` |
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| `country_name` | `category` | Country name. | `Mali` |
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| `year` | `Int64` | Observation year. | `2022` |
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| `variable` | `string` | Source column. | `bus_chl_government_regulations` |
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| `value` | `string` | Numeric observation value. | `Checked: Government regulations (e.g., compliance, technical regulation,` |
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| `pop` | `string` | Source column. | `smb business leaders` |
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| `logged_iso2` | `string` | Source column. | `AE` |
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| `mean_w` | `float64` | Source column. | `0.12469869` |
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| `se_w` | `float64` | Source column. | `0.044790301` |
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| `count` | `float64` | Source column. | `11.0` |
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| `question_n` | `float64` | Source column. | `88.0` |
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| `question_text` | `string` | Source column. | `What are the most important challenges your business currently faces? (P` |
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| `source_period_start_year` | `Int64` | First year inferred from source resource metadata. | `2022` |
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| `source_period_end_year` | `Int64` | Last year inferred from source resource metadata. | `2022` |
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| `source_period_label` | `category` | Human-readable period inferred from source resource metadata. | `2022` |
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| `source_provider` | `category` | Publishing organization. | `AI for Good at Meta` |
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| `source_dataset` | `category` | Source package title. | `Small Business Surveys - Aggregated Data` |
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| `source_resource` | `category` | Source resource title. | `aggregate_smb_leaders.csv` |
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| `source_package_id` | `category` | CKAN package UUID. | `8bd3d109-d33d-4349-90c4-464c9d7ccb66` |
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| `source_resource_id` | `category` | CKAN resource UUID. | `564d4e73-207b-462f-9bae-a80ee8780967` |
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| `source_url` | `category` | Original source resource URL. | `https://data.humdata.org/dataset/8bd3d109-d33d-4349-90c4-464c9d7ccb66/re` |
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| `license_id` | `category` | Source license identifier. | `cc-by` |
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| `retrieved_at` | `category` | UTC retrieval timestamp. | `2026-08-12T23:12:09Z` |
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## Usage
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```python
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from datasets import load_dataset
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ds = load_dataset("electricsheepafrica/africa-mali-small-business-surveys-aggregated-data-8e9832e3")
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df = ds["train"].to_pandas()
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print(df.head())
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```
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### Filter to one country
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```python
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sample_country = df[df["country_iso3"] == "MLI"]
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```
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### Work with indicators
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```python
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if "indicator_id" in df.columns:
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print(df["indicator_id"].value_counts().head())
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sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])
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```
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## Citation
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```bibtex
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@misc{electric_sheep_africa_africa_mali_small_business_surveys_aggregated_data_8e9832e3_2022,
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title = {Small Business Surveys - Aggregated Data | Africa (Mali official open data)},
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author = {AI for Good at Meta},
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year = {2022},
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url = {https://data.humdata.org/dataset/future-of-business-survey-aggregated-data},
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publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
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howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mali-small-business-surveys-aggregated-data-8e9832e3}}
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}
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```
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## License
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Released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
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Original data (c) AI for Good at Meta. When using this dataset, please cite both the
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original source above and the Electric Sheep Africa repackaging.
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## About Electric Sheep
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Electric Sheep Africa is part of the Electric Sheep mission: a unified,
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ML-ready data layer for Africa on Hugging Face. We pull data from authoritative
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open sources, normalize the schemas, package as Parquet, and publish with
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consistent dataset cards so researchers and developers can use `load_dataset()`
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to start working in seconds.
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Browse the full collection: [huggingface.co/electricsheepafrica](https://huggingface.co/electricsheepafrica)
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---
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Provenance: ingested 2026-08-13 via the Electric Sheep pipeline. Source URL:
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https://data.humdata.org/dataset/8bd3d109-d33d-4349-90c4-464c9d7ccb66/resource/564d4e73-207b-462f-9bae-a80ee8780967/download/aggregate_smb_leaders.csv
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data/train-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:898ee774fa64124420bcaa5700b08bc87fe8a715359781999f5b15954fabb137
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size 464898
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metadata/source_snapshot.json
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{
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"columns": [
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"source_record_id",
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"country_iso3",
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"country_name",
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"year",
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"variable",
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| 8 |
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"value",
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| 9 |
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"pop",
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"logged_iso2",
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"mean_w",
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"se_w",
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"count",
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"question_n",
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"question_text",
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"source_period_start_year",
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"source_period_end_year",
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"source_period_label",
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"source_provider",
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"source_dataset",
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"source_resource",
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"source_package_id",
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"source_resource_id",
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"source_url",
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"license_id",
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| 26 |
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"retrieved_at"
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| 27 |
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],
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"generated_at": "2026-08-12T23:56:11Z",
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| 29 |
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"indicator_count": 0,
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| 30 |
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"mode": "tabular_resource",
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| 31 |
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"repo_id": "electricsheepafrica/africa-mali-small-business-surveys-aggregated-data-8e9832e3",
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| 32 |
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"rows": 19776,
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"source": {
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"api_base_url": "https://data.humdata.org/api/3/action",
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"country_iso3": "MLI",
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| 36 |
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"country_name": "Mali",
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"group_names": "ago,arg,aus,bgd,bel,ben,bfa,bdi,cpv,khm,cmr,can,caf,tcd,chn,hkg,col,cri,civ,cze,cod,dnk,dji,ecu,egy,gnq,est,eth,fra,gab,gmb,deu,gha,grc,gin,gnb,hun,ind,idn,irq,irl,isr,ita,jpn,ken,lbn,lso,lbr,lby,mwi,mli,mrt,mus,mex,moz,mmr,nam,nld,ner,nga,nor,pak,per,phl,pol,prt,kor,reu,rou,rus,rwa,stp,sau,sen,syc,sle,sgp,zaf,esp,swe,che,twn,tha,tgo,tur,uga,are,gbr,tza,usa,vnm,zmb",
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| 38 |
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"license_id": "cc-by",
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| 39 |
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"license_title": "Creative Commons Attribution International (CC BY)",
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| 40 |
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"license_url": "http://www.opendefinition.org/licenses/cc-by",
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| 41 |
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"organization_name": "meta",
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| 42 |
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"organization_title": "AI for Good at Meta",
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| 43 |
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"package_id": "8bd3d109-d33d-4349-90c4-464c9d7ccb66",
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| 44 |
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"package_name": "future-of-business-survey-aggregated-data",
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"package_notes": "More than 200 million businesses use Facebook globally. The goal of our Small Business Surveys has been to learn about the unique perspectives, challenges and opportunities of small and medium-sized businesses (SMBs). Through 2022, the Future of Business Survey and the Global State of Small Business (GSoSB) Survey were conducted in partnership with the World Bank and Organisation for Economic Cooperation and Development. Aggregated country level data for each survey wave is available to the public on HDX and controlled access microdata is available to Data for Good at Meta partners. Please visit https://ai.meta.com/ai-for-good/datasets/small-business-surveys/ to apply for access to microdata or contact aiforgood@meta.com for any questions. This dataset regularly updated until 2023-03-24 and is no longer expecting additional data.",
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"package_page_url": "https://data.humdata.org/dataset/future-of-business-survey-aggregated-data",
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| 47 |
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"package_title": "Small Business Surveys - Aggregated Data",
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| 48 |
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"portal_url": "https://data.humdata.org",
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| 49 |
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"resource_description": "Weighted country level data for the Future of Business Survey, fielded in October 2022.",
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| 50 |
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"resource_format": "CSV",
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| 51 |
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"resource_id": "564d4e73-207b-462f-9bae-a80ee8780967",
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| 52 |
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"resource_last_modified": "2023-03-24T01:53:31.575129",
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| 53 |
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"resource_name": "aggregate_smb_leaders.csv",
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| 54 |
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"resource_position": "1",
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| 55 |
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"resource_url": "https://data.humdata.org/dataset/8bd3d109-d33d-4349-90c4-464c9d7ccb66/resource/564d4e73-207b-462f-9bae-a80ee8780967/download/aggregate_smb_leaders.csv",
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| 56 |
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"tag_names": "covid-19,economics,gender,trade,water sanitation and hygiene-wash"
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| 57 |
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},
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| 58 |
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"year_max": 2022,
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| 59 |
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"year_min": 2022
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| 60 |
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}
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