Kossisoroyce commited on
Commit
4739809
·
verified ·
1 Parent(s): dd37925

Add README.md

Browse files
Files changed (1) hide show
  1. README.md +161 -52
README.md CHANGED
@@ -1,56 +1,165 @@
1
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2
  dataset_info:
3
- features:
4
- - name: date
5
- dtype: timestamp[ns]
6
- - name: admin1
7
- dtype: string
8
- - name: admin2
9
- dtype: string
10
- - name: market
11
- dtype: string
12
- - name: market_id
13
- dtype: int64
14
- - name: latitude
15
- dtype: float64
16
- - name: longitude
17
- dtype: float64
18
- - name: category
19
- dtype: string
20
- - name: commodity
21
- dtype: string
22
- - name: commodity_id
23
- dtype: int64
24
- - name: unit
25
- dtype: string
26
- - name: priceflag
27
- dtype: string
28
- - name: pricetype
29
- dtype: string
30
- - name: currency
31
- dtype: string
32
- - name: price
33
- dtype: float64
34
- - name: usdprice
35
- dtype: float64
36
- - name: esa_source
37
- dtype: string
38
- - name: esa_processed
39
- dtype: string
40
  splits:
41
- - name: train
42
- num_bytes: 300799
43
- num_examples: 1507
44
- - name: test
45
- num_bytes: 75223
46
- num_examples: 377
47
- download_size: 42843
48
- dataset_size: 376022
49
- configs:
50
- - config_name: default
51
- data_files:
52
- - split: train
53
- path: data/train-*
54
- - split: test
55
- path: data/test-*
56
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
+ annotations_creators:
3
+ - no-annotation
4
+ language_creators:
5
+ - found
6
+ language:
7
+ - en
8
+ license: cc-by-4.0
9
+ multilinguality:
10
+ - monolingual
11
+ size_categories:
12
+ - 1K<n<10K
13
+ source_datasets:
14
+ - original
15
+ task_categories:
16
+ - tabular-regression
17
+ - other
18
+ task_ids: []
19
+ tags:
20
+ - africa
21
+ - humanitarian
22
+ - hdx
23
+ - electric-sheep-africa
24
+ - economics
25
+ - food-security
26
+ - indicators
27
+ - markets
28
+ - cpv
29
+ pretty_name: "Cabo Verde - Food Prices"
30
  dataset_info:
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
31
  splits:
32
+ - name: train
33
+ num_examples: 1507
34
+ - name: test
35
+ num_examples: 376
 
 
 
 
 
 
 
 
 
 
 
36
  ---
37
+
38
+ # Cabo Verde - Food Prices
39
+
40
+ **Publisher:** WFP - World Food Programme · **Source:** [HDX](https://data.humdata.org/dataset/wfp-food-prices-for-cabo-verde) · **License:** `cc-by-igo` · **Updated:** 2026-04-05
41
+
42
+ ---
43
+
44
+ ## Abstract
45
+
46
+ This dataset contains Food Prices data for Cape Verde, 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.
47
+
48
+ Each row in this dataset represents subnational administrative unit observations. Temporal coverage is indicated by the `date` column(s). Geographic scope: **CPV**.
49
+
50
+ *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
51
+
52
+ ---
53
+
54
+ ## Dataset Characteristics
55
+
56
+ | | |
57
+ |---|---|
58
+ | **Domain** | Food security and nutrition |
59
+ | **Unit of observation** | Subnational administrative unit observations |
60
+ | **Rows (total)** | 1,884 |
61
+ | **Columns** | 18 (6 numeric, 11 categorical, 1 datetime) |
62
+ | **Train split** | 1,507 rows |
63
+ | **Test split** | 376 rows |
64
+ | **Geographic scope** | CPV |
65
+ | **Publisher** | WFP - World Food Programme |
66
+ | **HDX last updated** | 2026-04-05 |
67
+
68
+ ---
69
+
70
+ ## Variables
71
+
72
+ **Geographic** — `admin1` (Santo Antao, Sao Vicente, Santiago), `admin2` (Concelho de Porto Novo, Sao Vicente, Sao Domingos), `latitude` (range 14.99–17.02), `longitude` (range -25.07–-23.52), `category` (cereals and tubers) and 4 others.
73
+
74
+ **Temporal** — `date`.
75
+
76
+ **Outcome / Measurement** — `priceflag` (actual), `price` (range 27.41–346.67), `usdprice` (range 0.34–4.27).
77
+
78
+ **Identifier / Metadata** — `market_id` (range 533.0–535.0), `esa_source` (HDX), `esa_processed`.
79
+
80
+ **Other** — `market` (Santo Antao, Sao Vicente, Santiago), `unit` (KG).
81
+
82
+ ---
83
+
84
+ ## Quick Start
85
+
86
+ ```python
87
+ from datasets import load_dataset
88
+
89
+ ds = load_dataset("electricsheepafrica/africa-wfp-food-prices-for-cabo-verde")
90
+ train = ds["train"].to_pandas()
91
+ test = ds["test"].to_pandas()
92
+
93
+ print(train.shape)
94
+ train.head()
95
+ ```
96
+
97
+ ---
98
+
99
+ ## Schema
100
+
101
+ | Column | Type | Null % | Range / Sample Values |
102
+ |---|---|---|---|
103
+ | `date` | datetime64[ns] | 0.0% | |
104
+ | `admin1` | object | 0.0% | Santo Antao, Sao Vicente, Santiago |
105
+ | `admin2` | object | 0.0% | Concelho de Porto Novo, Sao Vicente, Sao Domingos |
106
+ | `market` | object | 0.0% | Santo Antao, Sao Vicente, Santiago |
107
+ | `market_id` | int64 | 0.0% | 533.0 – 535.0 (mean 533.5483) |
108
+ | `latitude` | float64 | 0.0% | 14.99 – 17.02 (mean 16.8717) |
109
+ | `longitude` | float64 | 0.0% | -25.07 – -23.52 (mean -24.9647) |
110
+ | `category` | object | 0.0% | cereals and tubers |
111
+ | `commodity` | object | 0.0% | Wheat flour, Rice (long grain), Cassava |
112
+ | `commodity_id` | int64 | 0.0% | 56.0 – 162.0 (mean 101.5478) |
113
+ | `unit` | object | 0.0% | KG |
114
+ | `priceflag` | object | 0.0% | actual |
115
+ | `pricetype` | object | 0.0% | Retail |
116
+ | `currency` | object | 0.0% | CVE |
117
+ | `price` | float64 | 0.0% | 27.41 – 346.67 (mean 88.55) |
118
+ | `usdprice` | float64 | 0.0% | 0.34 – 4.27 (mean 1.0213) |
119
+ | `esa_source` | object | 0.0% | HDX |
120
+ | `esa_processed` | object | 0.0% | |
121
+
122
+ ---
123
+
124
+ ## Numeric Summary
125
+
126
+ | Column | Min | Max | Mean | Median |
127
+ |---|---|---|---|---|
128
+ | `market_id` | 533.0 | 535.0 | 533.5483 | 534.0 |
129
+ | `latitude` | 14.99 | 17.02 | 16.8717 | 16.88 |
130
+ | `longitude` | -25.07 | -23.52 | -24.9647 | -24.98 |
131
+ | `commodity_id` | 56.0 | 162.0 | 101.5478 | 68.0 |
132
+ | `price` | 27.41 | 346.67 | 88.55 | 75.0 |
133
+ | `usdprice` | 0.34 | 4.27 | 1.0213 | 0.87 |
134
+
135
+ ---
136
+
137
+ ## Curation
138
+
139
+ 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.
140
+
141
+ ---
142
+
143
+ ## Limitations
144
+
145
+ - Data originates from WFP - World Food Programme and has not been independently validated by ESA.
146
+ - Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
147
+ - Refer to the [original HDX dataset page](https://data.humdata.org/dataset/wfp-food-prices-for-cabo-verde) for the publisher's own methodology notes and caveats.
148
+
149
+ ---
150
+
151
+ ## Citation
152
+
153
+ ```bibtex
154
+ @dataset{hdx_africa_wfp_food_prices_for_cabo_verde,
155
+ title = {Cabo Verde - Food Prices},
156
+ author = {WFP - World Food Programme},
157
+ year = {2026},
158
+ url = {https://data.humdata.org/dataset/wfp-food-prices-for-cabo-verde},
159
+ note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
160
+ }
161
+ ```
162
+
163
+ ---
164
+
165
+ *[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*