Datasets:

electricsheepafrica
/

hdx-climate-change-opinion-survey

@@ -1,163 +1,147 @@
 ---
-annotations_creators:
-- no-annotation
-language_creators:
-- found
 language:
 - en
-license: other
-multilinguality:
-- monolingual
-size_categories:
-- 1K<n<10K
-source_datasets:
-- original
 task_categories:
 - tabular-classification
 - tabular-regression
-task_ids: []
 tags:
-- africa
-- humanitarian
-- hdx
-- electric-sheep-africa
-- climate-weather
-- environment
-- alb
-- dza
-- asm
-- ago
-- aia
-pretty_name: "Climate Change Opinion Survey"
-dataset_info:
-  splits:
-    - name: train
-      num_examples: 4112
-    - name: test
-      num_examples: 1028
 ---
-# Climate Change Opinion Survey
-**Publisher:** AI for Good at Meta · **Source:** [HDX](https://data.humdata.org/dataset/climate-change-opinion-survey) · **License:** `other-pd-nr` · **Updated:** 2026-03-26
----
-## Abstract
-In partnership with Yale, Meta launched a climate change opinion survey that explores public climate change knowledge, attitudes, policy preferences, and behaviors. 2023 aggregated survey responses now available.
- The 2022 survey includes respondents from nearly 200 countries and territories. We are sharing country level data from this survey, providing policymakers, research institutions, and nonprofits with an international view of public climate change opinion.
-For more information please see  https://ai.meta.com/ai-for-good/datasets/climate-change-opinion-survey/
-If you're interested in becoming a research partner and accessing record level data, please email aiforgood@meta.com.
-Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-03-26. Geographic scope: **ALB, DZA, ASM, AGO, AIA, ATG, ARG, ARM, and 185 others**.
-*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
----
-## Dataset Characteristics
-| | |
 |---|---|
-| **Domain** | Climate and environment |
-| **Unit of observation** | First-level administrative unit observations |
-| **Rows (total)** | 5,140 |
-| **Columns** | 11 (4 numeric, 7 categorical, 0 datetime) |
-| **Train split** | 4,112 rows |
-| **Test split** | 1,028 rows |
-| **Geographic scope** | ALB, DZA, ASM, AGO, AIA, ATG, ARG, ARM, and 185 others |
-| **Publisher** | AI for Good at Meta |
-| **HDX last updated** | 2026-03-26 |
----
-## Variables
-**Geographic** — `region` (Europe, Asia, Southwest Asia & North Africa), `country_code` (hk, jp, no), `country` (Hong Kong, Japan, Norway).
-**Outcome / Measurement** — `pct` (range 0.0–86.5244).
-**Identifier / Metadata** — `esa_source` (HDX), `esa_processed` (2026-04-04).
-**Other** — `response` (I have not done this, I have done this, Not applicable), `freq` (range 0.0–2155.7138), `n` (range 12.4363–2836.0), `prop` (range 0.0–0.8652), `variable` (barriers_heatpump_haventadopted, barriers_ev_haventadopted, barriers_solar_haventadopted).
----
-## Quick Start
 ```python
 from datasets import load_dataset
-ds    = load_dataset("electricsheepafrica/hdx-climate-change-opinion-survey")
-train = ds["train"].to_pandas()
-test  = ds["test"].to_pandas()
-print(train.shape)
-train.head()
 ```
----
-## Schema
-| Column | Type | Null % | Range / Sample Values |
-|---|---|---|---|
-| `region` | object | 0.0% | Europe, Asia, Southwest Asia & North Africa |
-| `country_code` | object | 0.0% | hk, jp, no |
-| `country` | object | 0.0% | Hong Kong, Japan, Norway |
-| `response` | object | 0.0% | I have not done this, I have done this, Not applicable |
-| `freq` | float64 | 0.0% | 0.0 – 2155.7138 (mean 100.6589) |
-| `n` | float64 | 0.0% | 12.4363 – 2836.0 (mean 608.2886) |
-| `prop` | float64 | 0.0% | 0.0 – 0.8652 (mean 0.1557) |
-| `pct` | float64 | 0.0% | 0.0 – 86.5244 (mean 15.5693) |
-| `variable` | object | 0.0% | barriers_heatpump_haventadopted, barriers_ev_haventadopted, barriers_solar_haventadopted |
-| `esa_source` | object | 0.0% | HDX |
-| `esa_processed` | object | 0.0% | 2026-04-04 |
----
-## Numeric Summary
-| Column | Min | Max | Mean | Median |
-|---|---|---|---|---|
-| `freq` | 0.0 | 2155.7138 | 100.6589 | 39.2444 |
-| `n` | 12.4363 | 2836.0 | 608.2886 | 551.0772 |
-| `prop` | 0.0 | 0.8652 | 0.1557 | 0.0955 |
-| `pct` | 0.0 | 86.5244 | 15.5693 | 9.5545 |
----
-## 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 AI for Good at Meta and has not been independently validated by ESA.
-- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
-- This dataset spans 193 countries; geographic and methodological inconsistencies across national boundaries may affect cross-country comparability.
-- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/climate-change-opinion-survey) for the publisher's own methodology notes and caveats.
----
 ## Citation
 ```bibtex
-@dataset{hdx_hdx_climate_change_opinion_survey,
-  title     = {Climate Change Opinion Survey},
-  author    = {AI for Good at Meta},
-  year      = {2026},
-  url       = {https://data.humdata.org/dataset/climate-change-opinion-survey},
-  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.*

 ---
+license: other
 language:
 - en
 task_categories:
 - tabular-classification
 - tabular-regression
+multilinguality: monolingual
+size_categories:
+- 1K<n<10K
 tags:
+- "africa"
+- "electric-sheep-africa"
+- "open-data"
+- "metadata-backed"
+- "climate-environment"
+- "parquet"
+- "tabular"
+- "text"
+- "humanitarian"
+- "hdx"
+- "climate-weather"
+- "environment"
+- "alb"
+- "dza"
+- "asm"
+- "ago"
+- "aia"
+- "climate"
+- "weather"
+pretty_name: "Climate Change Opinion Survey | Africa (original)"
 ---
+# Climate Change Opinion Survey | Africa (original)
+**Size category:** `1K<n<10K` - **Formats:** `parquet` - **Sector:** climate_environment - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*
+![size](https://img.shields.io/badge/size-1K%3Cn%3C10K-blue)
+![sector](https://img.shields.io/badge/sector-climate_environment-green)
+![downloads](https://img.shields.io/badge/HF_downloads-25-orange)
+![license](https://img.shields.io/badge/license-other-lightgrey)
+## TL;DR
+This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
+## What This Dataset Covers
+Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.
+Dataset context from the existing Hugging Face card: Climate Change Opinion Survey Publisher: AI for Good at Meta · Source: HDX · License: other-pd-nr · Updated: 2026-03-26 Abstract In partnership with Yale, Meta launched a climate change opinion survey that explores public climate change knowledge, attitudes, policy preferences, and behaviors. 2023 aggregated survey responses now available. The 2022 survey includes respondents from nearly 200 countries and territories. We are sharing country level data from this survey… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/hdx-climate-change-opinion-survey.
+## Dataset Profile
+| Field | Value |
 |---|---|
+| Hugging Face repo | [`electricsheepafrica/hdx-climate-change-opinion-survey`](https://huggingface.co/datasets/electricsheepafrica/hdx-climate-change-opinion-survey) |
+| Sector | climate_environment |
+| Topic tags | humanitarian, hdx, electric-sheep-africa, climate-weather, environment, alb, dza, asm, ago, aia |
+| Modalities | `tabular`, `text` |
+| Formats | `parquet` |
+| Size category | `1K<n<10K` |
+| Countries | Africa-wide or source-defined African coverage |
+| ISO3 coverage | `not declared` |
+| Last modified on HF | `2026-04-04 09:46:11+00:00` |
+| Inventory snapshot | `2026-07-16T16:00:34Z` |
+## How To Read This Dataset
+- Start from the repository files and the dataset viewer when available.
+- Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
+- Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
+- Preserve missing values until you have a defensible imputation rule.
+## Usage
 ```python
 from datasets import load_dataset
+ds = load_dataset("electricsheepafrica/hdx-climate-change-opinion-survey")
+print(ds)
+split_name = next(iter(ds))
+table = ds[split_name]
+print(table.features)
+print(table[:3])
 ```
+### Convert To Pandas When Tabular
+```python
+from datasets import Dataset
+first_split = ds[next(iter(ds))]
+if isinstance(first_split, Dataset):
+    df = first_split.to_pandas()
+    print(df.head())
+```
+## Data Quality Notes
+- This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
+- Exact schema, row counts, and source files should be inspected in the repository data files.
+- Metadata gaps from the inventory: country, upstream_publisher.
+- Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.
+## Source And Provenance
+- **Source context:** original
+- **Publisher/source attribution:** original
+- **License:** Source-specific or other license
+- **Hugging Face URL:** [https://huggingface.co/datasets/electricsheepafrica/hdx-climate-change-opinion-survey](https://huggingface.co/datasets/electricsheepafrica/hdx-climate-change-opinion-survey)
+- **Inventory retrieved at:** `2026-07-16T16:00:34Z`
+## Suggested Analyses
+- Inspect schema and missingness before modeling.
+- Profile variables by geography, time, and subgroup columns where present.
+- Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
+- Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.
 ## Citation
 ```bibtex
+@misc{electric_sheep_africa_hdx_climate_change_opinion_survey_2026,
+  title        = {Climate Change Opinion Survey | Africa (original)},
+  author       = {original},
+  year         = {2026},
+  url          = {https://huggingface.co/datasets/electricsheepafrica/hdx-climate-change-opinion-survey},
+  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
+  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/hdx-climate-change-opinion-survey}}
 }
 ```
+## License
+Released under Source-specific or other license.
+Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.
+## About Electric Sheep Africa
+Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.
 ---
+Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: `catalog/esa_metadata_inventory/master_metadata.jsonl`.