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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  dataset_info:
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- features:
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- - name: date
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- dtype: timestamp[ns]
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- - name: admin1
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- dtype: string
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- - name: admin2
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- dtype: string
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- - name: market
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- dtype: string
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- - name: market_id
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- dtype: int64
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- - name: latitude
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- dtype: float64
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- - name: longitude
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- dtype: float64
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- - name: category
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- dtype: string
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- - name: commodity
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- dtype: string
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- - name: commodity_id
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- dtype: int64
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- - name: unit
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- dtype: string
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- - name: priceflag
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- dtype: string
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- - name: pricetype
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- dtype: string
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- - name: currency
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- dtype: string
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- - name: price
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- dtype: float64
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- - name: usdprice
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- dtype: float64
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- - name: esa_source
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- dtype: string
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- - name: esa_processed
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- dtype: string
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  splits:
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- - name: train
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- num_bytes: 6267437
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- num_examples: 34336
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- - name: test
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- num_bytes: 1566317
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- num_examples: 8584
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- download_size: 765745
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- dataset_size: 7833754
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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-*
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- - split: test
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- path: data/test-*
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ annotations_creators:
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+ - no-annotation
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+ language_creators:
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+ - found
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+ language:
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+ - en
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+ license: cc-by-4.0
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+ multilinguality:
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+ - monolingual
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+ size_categories:
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+ - 10K<n<100K
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+ source_datasets:
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+ - original
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+ task_categories:
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+ - tabular-regression
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+ - other
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+ task_ids: []
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+ tags:
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+ - africa
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+ - humanitarian
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+ - hdx
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+ - electric-sheep-africa
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+ - economics
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+ - food-security
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+ - indicators
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+ - markets
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+ - sen
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+ pretty_name: "Senegal - Food Prices"
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  dataset_info:
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  splits:
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+ - name: train
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+ num_examples: 34336
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+ - name: test
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+ num_examples: 8584
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+
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+ # Senegal - Food Prices
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+
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+ **Publisher:** WFP - World Food Programme · **Source:** [HDX](https://data.humdata.org/dataset/wfp-food-prices-for-senegal) · **License:** `cc-by-igo` · **Updated:** 2026-04-05
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+
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+ ---
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+
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+ ## Abstract
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+
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+ This dataset contains Food Prices data for Senegal, sourced from the World Food Programme Price Database. The World Food Programme Price Database covers foods such as maize, rice, beans, fish, and sugar for 98 countries and some 3000 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.
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+
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+ Each row in this dataset represents subnational administrative unit observations. Temporal coverage is indicated by the `date` column(s). Geographic scope: **SEN**.
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+
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+ *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
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+
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+ ---
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+
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+ ## Dataset Characteristics
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+
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+ | | |
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+ |---|---|
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+ | **Domain** | Food security and nutrition |
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+ | **Unit of observation** | Subnational administrative unit observations |
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+ | **Rows (total)** | 42,920 |
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+ | **Columns** | 18 (6 numeric, 11 categorical, 1 datetime) |
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+ | **Train split** | 34,336 rows |
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+ | **Test split** | 8,584 rows |
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+ | **Geographic scope** | SEN |
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+ | **Publisher** | WFP - World Food Programme |
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+ | **HDX last updated** | 2026-04-05 |
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+
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+ ---
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+
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+ ## Variables
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+
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+ **Geographic** — `admin1` (Fatick, Diourbel, Thies), `admin2` (Fatick, Dakar, Kolda), `latitude` (range 12.48–16.52), `longitude` (range -17.46–-11.95), `category` (cereals and tubers, pulses and nuts) and 4 others.
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+
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+ **Temporal** — `date`.
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+
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+ **Outcome / Measurement** — `priceflag` (actual), `price` (range 90.0–1816.5), `usdprice` (range 0.2–2.95).
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+
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+ **Identifier / Metadata** — `market_id` (range 405.0–5234.0), `esa_source` (HDX), `esa_processed`.
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+
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+ **Other** — `market` (Tilene, Kaolack, Louga), `unit` (KG).
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+
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+ ---
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+
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+ ## Quick Start
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ ds = load_dataset("electricsheepafrica/africa-wfp-food-prices-for-senegal")
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+ train = ds["train"].to_pandas()
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+ test = ds["test"].to_pandas()
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+
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+ print(train.shape)
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+ train.head()
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+ ```
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+
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+ ---
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+
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+ ## Schema
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+
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+ | Column | Type | Null % | Range / Sample Values |
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+ |---|---|---|---|
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+ | `date` | datetime64[ns] | 0.0% | |
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+ | `admin1` | object | 0.0% | Fatick, Diourbel, Thies |
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+ | `admin2` | object | 0.0% | Fatick, Dakar, Kolda |
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+ | `market` | object | 0.0% | Tilene, Kaolack, Louga |
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+ | `market_id` | int64 | 0.0% | 405.0 – 5234.0 (mean 480.9576) |
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+ | `latitude` | float64 | 0.0% | 12.48 – 16.52 (mean 14.3651) |
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+ | `longitude` | float64 | 0.0% | -17.46 – -11.95 (mean -15.6127) |
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+ | `category` | object | 0.0% | cereals and tubers, pulses and nuts |
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+ | `commodity` | object | 0.0% | Rice (imported), Millet, Maize (local) |
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+ | `commodity_id` | int64 | 0.0% | 56.0 – 201.0 (mean 87.4315) |
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+ | `unit` | object | 0.0% | KG |
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+ | `priceflag` | object | 0.0% | actual |
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+ | `pricetype` | object | 0.0% | Retail |
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+ | `currency` | object | 0.0% | XOF |
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+ | `price` | float64 | 0.0% | 90.0 – 1816.5 (mean 326.903) |
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+ | `usdprice` | float64 | 0.0% | 0.2 – 2.95 (mean 0.5878) |
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+ | `esa_source` | object | 0.0% | HDX |
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+ | `esa_processed` | object | 0.0% | |
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+
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+ ---
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+
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+ ## Numeric Summary
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+
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+ | Column | Min | Max | Mean | Median |
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+ |---|---|---|---|---|
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+ | `market_id` | 405.0 | 5234.0 | 480.9576 | 431.0 |
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+ | `latitude` | 12.48 | 16.52 | 14.3651 | 14.54 |
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+ | `longitude` | -17.46 | -11.95 | -15.6127 | -16.17 |
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+ | `commodity_id` | 56.0 | 201.0 | 87.4315 | 71.0 |
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+ | `price` | 90.0 | 1816.5 | 326.903 | 275.0 |
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+ | `usdprice` | 0.2 | 2.95 | 0.5878 | 0.51 |
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+
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+ ---
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+
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+ ## Curation
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+
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+ 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`. 1 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.
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+
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+ ---
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+
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+ ## Limitations
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+
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+ - Data originates from WFP - World Food Programme and has not been independently validated by ESA.
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+ - Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
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+ - Refer to the [original HDX dataset page](https://data.humdata.org/dataset/wfp-food-prices-for-senegal) for the publisher's own methodology notes and caveats.
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+
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+ ---
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @dataset{hdx_africa_wfp_food_prices_for_senegal,
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+ title = {Senegal - Food Prices},
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+ author = {WFP - World Food Programme},
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+ year = {2026},
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+ url = {https://data.humdata.org/dataset/wfp-food-prices-for-senegal},
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+ note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
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+ }
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+ ```
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+
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+ ---
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+
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+ *[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*