Standardize Electric Sheep Africa dataset card
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README.md
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task_categories:
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- tabular-classification
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- tabular-regression
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multilinguality:
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size_categories:
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- 1K<n<10K
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tags:
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- tabular
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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: "
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---
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#
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1,313 rows - 1 Africa country -
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## TL;DR
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This dataset
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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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##
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## Geographic
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|------
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| `TCD` | 1,313 |
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## Indicators
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- This source
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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
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| `country_iso3` | `
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| `country_name` | `
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| `country_name_2` | `string` | Source column. | `#country` |
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| `admin1_name` | `string` | Source column. | `#adm1+name` |
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| `latitude` | `
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| `longitude` | `
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| `aggregation` | `string` | Source column. | `` |
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| `indicator` | `string` | Source column. | `#indicator+name` |
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| `value` | `
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| `source_period_start_year` | `
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| `source_period_end_year` | `
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| `source_period_label` | `string` |
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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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| `retrieved_at` | `
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## Usage
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print(df.head())
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```
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###
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```python
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```
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###
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```python
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if "
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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_chad_litpop_humanitarian_response_plan_hrp_countries_exposure_d_16639944_2026,
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title = {
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author = {ETH Zürich - Weather and Climate Risks},
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year = {2026},
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url = {https://data.humdata.org/dataset/climada-litpop-dataset},
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publisher = {
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howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-chad-litpop-humanitarian-response-plan-hrp-countries-exposure-d-16639944}}
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}
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```
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Released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
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Original data
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## About Electric Sheep
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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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---
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Provenance:
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https://data.humdata.org/dataset/3527869c-8fe9-4289-9d57-1811e789bf60/resource/2d3c933d-1fa0-4689-b383-83c519dc2852/download/haiti-admin1-litpop.csv
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task_categories:
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- tabular-classification
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- tabular-regression
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multilinguality: multilingual
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size_categories:
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- 1K<n<10K
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tags:
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- "tabular"
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- "africa"
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- "open-data"
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- "official-statistics"
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- "chad"
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- "eth-zurich-weather-and-climate-risks"
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- "afg"
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- "bfa"
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- "bdi"
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- "cmr"
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- "caf"
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- "tcd"
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- "col"
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- "cod"
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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: "Litpop Humanitarian Response Plan Hrp Countries Exposure D | Africa (ETH Zürich - Weather and Climate Risks)"
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---
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# Litpop Humanitarian Response Plan Hrp Countries Exposure D | Africa (ETH Zürich - Weather and Climate Risks)
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**1,313 rows** - **1 Africa country/area** - **detected** - **source table** - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*
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## TL;DR
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This dataset contains **1,313 rows** from **ETH Zürich - Weather and Climate Risks**, covering **Litpop Humanitarian Response Plan Hrp Countries Exposure D**. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.
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## What This Dataset Measures
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Official statistics datasets help analysts inspect public data as published by governments, national statistical systems, and regional data portals.
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Source-provided context: Gridded LitPop data for Haiti with admin1 name column
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## How To Read This Dataset
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- **One row means:** one source record from the original tabular resource, with Electric Sheep Africa provenance columns added where available.
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- **Primary geography column:** `country_iso3`.
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- **Best time column:** `source_period_start_year`.
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- **Time coverage basis:** source_period_start_year.
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- **Recommended join keys:** `country_iso3` where available plus source-specific keys.
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## Coverage
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| Dimension | Value |
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|---|---:|
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| Rows | 1,313 |
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| Countries/areas | 1 |
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| First period | detected |
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| Last period | detected |
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| Indicators | 0 |
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| Columns | 21 |
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| Source format | CSV |
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## Geographic Coverage
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Top areas shown below, sorted by row count when available:
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| Area | Rows | First year | Last year | Name |
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|------|-----:|-----------:|----------:|------|
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| `TCD` | 1,313 | detected | detected | `Chad` |
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## Indicators, Variables, Or Resource Contents
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- This repo preserves one source tabular resource with its usable columns kept together.
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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 assigned during Electric Sheep Africa engineering. | `2d3c933d-1fa0-4689-b383-83c519dc2852:0` |
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| `country_iso3` | `dictionary<values=string, indices=int8, ordered=0>` | ISO3 country or area code. | `TCD` |
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| `country_name` | `dictionary<values=string, indices=int8, ordered=0>` | Country or area name. | `Chad` |
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| `country_name_2` | `string` | Source column from the original resource. | `#country` |
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| `admin1_name` | `string` | Source column from the original resource. | `#adm1+name` |
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| `latitude` | `double` | Source column from the original resource. | `` |
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| `longitude` | `double` | Source column from the original resource. | `` |
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| `aggregation` | `string` | Source column from the original resource. | `` |
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| `indicator` | `string` | Source column from the original resource. | `#indicator+name` |
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| `value` | `double` | Numeric observation value. | `` |
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| `source_period_start_year` | `int64` | Start year inferred from source metadata. | `` |
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| `source_period_end_year` | `int64` | End year inferred from source metadata. | `` |
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| `source_period_label` | `string` | Source column from the original resource. | `` |
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| `source_provider` | `dictionary<values=string, indices=int8, ordered=0>` | Publishing organization. | `ETH Zürich - Weather and Climate Risks` |
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| `source_dataset` | `dictionary<values=string, indices=int8, ordered=0>` | Source dataset or package title. | `LitPop: Humanitarian Response Plan (HRP) Countries Exposure Data for ...` |
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| `source_resource` | `dictionary<values=string, indices=int8, ordered=0>` | Source resource title, table name, or file name. | `haiti-admin1-litpop.csv` |
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| `source_package_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source package identifier. | `3527869c-8fe9-4289-9d57-1811e789bf60` |
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| `source_resource_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source resource identifier. | `2d3c933d-1fa0-4689-b383-83c519dc2852` |
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| `source_url` | `dictionary<values=string, indices=int8, ordered=0>` | Original source URL or download URL. | `https://data.humdata.org/dataset/3527869c-8fe9-4289-9d57-1811e789bf60...` |
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| `license_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source license identifier. | `cc-by` |
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| `retrieved_at` | `dictionary<values=string, indices=int8, ordered=0>` | UTC source retrieval timestamp from the Electric Sheep Africa pipeline. | `2026-08-10T22:51:43Z` |
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## Usage
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print(df.head())
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```
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### Inspect Columns
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```python
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print(df.info())
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print(df.head())
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```
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### Filter By Geography
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```python
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if "country_iso3" in df.columns:
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sample = df[df["country_iso3"] == "TCD"]
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```
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### Time-Series Pattern
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```python
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if "value" in df.columns and "source_period_start_year" in df.columns:
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trend = df.sort_values("source_period_start_year")
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```
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### Pivot For Analysis
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```python
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if {"indicator_id", "year", "value"}.issubset(df.columns):
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matrix = df.pivot_table(index="year", columns="indicator_id", values="value")
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print(matrix.tail())
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```
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## Data Quality Notes
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- Canonical time field: `source_period_start_year`.
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- Missing values are preserved rather than silently imputed.
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- Column names are standardized for machine use; source meanings are preserved where known.
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- Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use.
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## Source And Provenance
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- **Source:** [ETH Zürich - Weather and Climate Risks](https://data.humdata.org/dataset/climada-litpop-dataset)
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- **Publisher:** ETH Zürich - Weather and Climate Risks
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- **Portal:** [https://data.humdata.org](https://data.humdata.org)
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- **Resource:** [haiti-admin1-litpop.csv](https://data.humdata.org/dataset/3527869c-8fe9-4289-9d57-1811e789bf60/resource/2d3c933d-1fa0-4689-b383-83c519dc2852/download/haiti-admin1-litpop.csv)
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- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
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- **Retrieved/generated:** `2026-08-11T00:10:36Z`
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- **Hugging Face repo:** [electricsheepafrica/africa-chad-litpop-humanitarian-response-plan-hrp-countries-exposure-d-16639944](https://huggingface.co/datasets/electricsheepafrica/africa-chad-litpop-humanitarian-response-plan-hrp-countries-exposure-d-16639944)
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## Transformations Applied
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- Converted the source table to Parquet for efficient analytics and ML workflows.
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- Added or preserved source provenance columns where available.
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- Standardized README metadata, dataset loading configuration, schema documentation, and citation format.
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- Preserved source-reported values without analytical imputation.
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## Suggested Analyses
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- Profile the distribution of values
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- Compare categories or geographies
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- Join with complementary public datasets
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- Build time-series views and period-over-period comparisons
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- Check missingness before modeling
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- Use `country_iso3` as the safest geography join key when present
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## Citation
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```bibtex
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@misc{electric_sheep_africa_africa_chad_litpop_humanitarian_response_plan_hrp_countries_exposure_d_16639944_2026,
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title = {Litpop Humanitarian Response Plan Hrp Countries Exposure D | Africa (ETH Zürich - Weather and Climate Risks)},
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author = {ETH Zürich - Weather and Climate Risks},
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year = {2026},
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url = {https://data.humdata.org/dataset/climada-litpop-dataset},
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publisher = {Hugging Face Datasets, engineered by Electric Sheep Africa},
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howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-chad-litpop-humanitarian-response-plan-hrp-countries-exposure-d-16639944}}
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}
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```
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Released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
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Original data is published by ETH Zürich - Weather and Climate Risks. Electric Sheep Africa
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engineering standardizes the data for discovery, loading, and analysis on
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Hugging Face. Cite both the original source and this ML-ready dataset when used.
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## About Electric Sheep Africa
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Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.
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---
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Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.humdata.org/dataset/climada-litpop-dataset
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