File size: 7,014 Bytes
9456206
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
---
license: cc-by-4.0
language:
- en
task_categories:
- tabular-classification
- tabular-regression
multilinguality: monolingual
size_categories:
- n<1K
tags:
- tabular
- xlsx
- africa
- libya
- official-statistics
- open-data
- population
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-00000-of-00001.parquet
pretty_name: "Libya: Population Statistics | Africa (Libya official open data)"
---

# Libya: Population Statistics | Africa (Libya official open data)

507 rows - 1 Africa country - 2021 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

![rows](https://img.shields.io/badge/rows-507-blue)
![countries](https://img.shields.io/badge/countries-1-green)
![years](https://img.shields.io/badge/years-2021-orange)
![indicators](https://img.shields.io/badge/indicators-0-purple)
![license](https://img.shields.io/badge/license-cc-by-4.0-lightgrey)

## TL;DR

This dataset packages one official `XLSX` resource from **Libya** as
ML-ready Parquet. The source file is the provenance boundary; all usable
indicators or tabular columns from the resource stay together in this repo.

## About the source

- **Source:** [Libya: Population Statistics](https://data.humdata.org/dataset/libya-total-population-by-mantika)
- **Publisher:** OCHA Libya (inactive)
- **Resource:** [LBY_POP_2021](https://data.humdata.org/dataset/d3b4d8cf-a9db-48d5-afe3-065011ab5ab2/resource/7b1e5eff-b760-4df0-9a95-2503f0cecb79/download/pop-consolidated_sadd_for_hno_28aug2021.xlsx)
- **Format:** `XLSX`
- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
- **Packaging mode:** `tabular_resource`

## Geographic coverage

1 Africa country:

| Country | Rows | First year | Last year | Name |
|---------|-----:|-----------:|----------:|------|
| `LBY` | 507 | 2021 | 2021 | `Libya` |

## Indicators or Resource Contents

- This source file is packaged as a normalized tabular resource.

## Schema

| Column | Type | Description | Example |
|--------|------|-------------|---------|
| `source_record_id` | `string` | Stable row identifier for tabular resources. | `7b1e5eff-b760-4df0-9a95-2503f0cecb79:pop-pivot:0` |
| `country_iso3` | `category` | ISO3 country code. | `LBY` |
| `country_name` | `category` | Country name. | `Libya` |
| `source_sheet` | `string` | Workbook sheet name, when the source is a spreadsheet. | `Pop pivot` |
| `year` | `Int64` | Observation year. | `2021` |
| `row_labels` | `string` | Source column. | `IDPs` |
| `sum_of_individuals` | `float64` | Source column. | `212593.0` |
| `sum_of_male_below_18` | `float64` | Source column. | `41925.0` |
| `sum_of_male_18_59` | `float64` | Source column. | `59200.0` |
| `sum_of_male_60` | `float64` | Source column. | `6000.0` |
| `sum_of_female_below_18` | `float64` | Source column. | `45290.0` |
| `sum_of_female_18_59` | `float64` | Source column. | `54514.0` |
| `sum_of_female_60` | `float64` | Source column. | `5664.0` |
| `source_period_start_year` | `Int64` | First year inferred from source resource metadata. | `2021` |
| `source_period_end_year` | `Int64` | Last year inferred from source resource metadata. | `2021` |
| `source_period_label` | `category` | Human-readable period inferred from source resource metadata. | `2021` |
| `source_provider` | `category` | Publishing organization. | `OCHA Libya (inactive)` |
| `source_dataset` | `category` | Source package title. | `Libya: Population Statistics` |
| `source_resource` | `category` | Source resource title. | `LBY_POP_2021` |
| `source_package_id` | `category` | CKAN package UUID. | `d3b4d8cf-a9db-48d5-afe3-065011ab5ab2` |
| `source_resource_id` | `category` | CKAN resource UUID. | `7b1e5eff-b760-4df0-9a95-2503f0cecb79` |
| `source_url` | `category` | Original source resource URL. | `https://data.humdata.org/dataset/d3b4d8cf-a9db-48d5-afe3-065011ab5ab2/re` |
| `license_id` | `category` | Source license identifier. | `cc-by` |
| `retrieved_at` | `category` | UTC retrieval timestamp. | `2026-08-17T13:13:43Z` |
| `mantika_pcode` | `string` | Source column. | `` |
| `adm2_mantika_en` | `string` | Source column. | `` |
| `baladiya_pcode` | `string` | Source column. | `` |
| `adm3_baladiya_en` | `string` | Source column. | `` |
| `population_group` | `string` | Source column. | `` |
| `individuals` | `float64` | Source column. | `` |
| `male_below_18` | `float64` | Source column. | `` |
| `male_18_59` | `float64` | Source column. | `` |
| `male_60` | `float64` | Source column. | `` |
| `female_below_18` | `float64` | Source column. | `` |
| `female_18_59` | `float64` | Source column. | `` |
| `female_60` | `float64` | Source column. | `` |
| `male_below_18_2` | `float64` | Source column. | `` |
| `male_18_59_2` | `float64` | Source column. | `` |
| `male_60_2` | `float64` | Source column. | `` |
| `female_below_18_2` | `float64` | Source column. | `` |
| `female_18_59_2` | `float64` | Source column. | `` |
| `female_60_2` | `float64` | Source column. | `` |

## Usage

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-libya-libya-population-statistics-13ed2671")
df = ds["train"].to_pandas()
print(df.head())
```

### Filter to one country

```python
sample_country = df[df["country_iso3"] == "LBY"]
```

### Work with indicators

```python
if "indicator_id" in df.columns:
    print(df["indicator_id"].value_counts().head())
    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])
```

## Citation

```bibtex
@misc{electric_sheep_africa_africa_libya_libya_population_statistics_13ed2671_2021,
  title        = {Libya: Population Statistics | Africa (Libya official open data)},
  author       = {OCHA Libya (inactive)},
  year         = {2021},
  url          = {https://data.humdata.org/dataset/libya-total-population-by-mantika},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-libya-libya-population-statistics-13ed2671}}
}
```

## License

Released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).

Original data (c) OCHA Libya (inactive). When using this dataset, please cite both the
original source above and the Electric Sheep Africa repackaging.

## About Electric Sheep

Electric Sheep Africa is part of the Electric Sheep mission: a unified,
ML-ready data layer for Africa on Hugging Face. We pull data from authoritative
open sources, normalize the schemas, package as Parquet, and publish with
consistent dataset cards so researchers and developers can use `load_dataset()`
to start working in seconds.

Browse the full collection: [huggingface.co/electricsheepafrica](https://huggingface.co/electricsheepafrica)

---

Provenance: ingested 2026-08-17 via the Electric Sheep pipeline. Source URL:
https://data.humdata.org/dataset/d3b4d8cf-a9db-48d5-afe3-065011ab5ab2/resource/7b1e5eff-b760-4df0-9a95-2503f0cecb79/download/pop-consolidated_sadd_for_hno_28aug2021.xlsx