country_name stringclasses 2
values | country_m49 int64 480 504 | item stringclasses 2
values | year int64 2k 2.02k | value float64 -3.54 45.2 | unit stringclasses 1
value | flag stringclasses 2
values |
|---|---|---|---|---|---|---|
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,003 | 45.242215 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,004 | 25.773196 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,005 | 27.394439 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,006 | 23.874197 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,007 | 6.181627 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,008 | 0.606787 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,009 | 0.067893 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,010 | 0.251918 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,011 | 8.769054 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,012 | 12.543705 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,013 | 8.326618 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,014 | 4.224181 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,015 | 4.481328 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,016 | 6.47433 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,017 | 8.732594 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,018 | 8.02076 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,019 | 1.473009 | % | X |
Mauritius | 480 | FDI outflows to Agriculture, Forestry and Fishing | 2,020 | 1.740464 | % | X |
Morocco | 504 | FDI outflows to Agriculture, Forestry and Fishing | 2,011 | 0.081876 | % | X |
Morocco | 504 | FDI outflows to Agriculture, Forestry and Fishing | 2,013 | -0.430108 | % | X |
Morocco | 504 | FDI outflows to Agriculture, Forestry and Fishing | 2,015 | 0.031353 | % | X |
Morocco | 504 | FDI outflows to Agriculture, Forestry and Fishing | 2,016 | 0.246262 | % | X |
Morocco | 504 | FDI outflows to Agriculture, Forestry and Fishing | 2,017 | -0.010106 | % | X |
Morocco | 504 | FDI outflows to Agriculture, Forestry and Fishing | 2,018 | 0.054488 | % | X |
Morocco | 504 | FDI outflows to Agriculture, Forestry and Fishing | 2,019 | 0.221239 | % | X |
Morocco | 504 | FDI outflows to Agriculture, Forestry and Fishing | 2,020 | -0.137836 | % | X |
Morocco | 504 | FDI outflows to Agriculture, Forestry and Fishing | 2,021 | 0.138098 | % | P |
Morocco | 504 | FDI outflows to Agriculture, Forestry and Fishing | 2,022 | 0.721744 | % | P |
Morocco | 504 | FDI outflows to Food, Beverages and Tobacco | 2,009 | 0.083357 | % | X |
Morocco | 504 | FDI outflows to Food, Beverages and Tobacco | 2,010 | 0.344924 | % | X |
Morocco | 504 | FDI outflows to Food, Beverages and Tobacco | 2,011 | 11.948067 | % | X |
Morocco | 504 | FDI outflows to Food, Beverages and Tobacco | 2,012 | 1.62254 | % | X |
Morocco | 504 | FDI outflows to Food, Beverages and Tobacco | 2,013 | 1.863799 | % | X |
Morocco | 504 | FDI outflows to Food, Beverages and Tobacco | 2,014 | 11.423119 | % | X |
Morocco | 504 | FDI outflows to Food, Beverages and Tobacco | 2,015 | 2.602289 | % | X |
Morocco | 504 | FDI outflows to Food, Beverages and Tobacco | 2,016 | -3.53562 | % | X |
Foreign Direct Investment (FDI) — Share of Total FDI outflows US$, 2015 prices | Africa (FAOSTAT)
🌍 46 observations · 3 Africa countries · 2003–2023 · Repackaged by Electric Sheep Africa
TL;DR
This dataset contains 46 observations of Investment data across 3 Africa countries, spanning 2003–2023, covering 2 distinct indicators.
About the source
- Source: FAOSTAT (FAO)
- Publisher: Food and Agriculture Organization of the United Nations (FAO)
- License: cc-by-4.0
- Topic: Investment
Geographic coverage
3 Africa countries · top rows shown below, sorted by row count:
| Country | Rows | First year | Last year |
|---|---|---|---|
Morocco |
25 | 2009 | 2023 |
Mauritius |
18 | 2003 | 2020 |
Zambia |
3 | 2016 | 2021 |
Indicators (sample)
FDI outflows to Agriculture, Forestry and FishingFDI outflows to Food, Beverages and Tobacco
Schema
| Column | Type | Description | Example |
|---|---|---|---|
country_name |
string |
— | Mauritius |
country_m49 |
int64 |
— | 480 |
item |
string |
— | FDI outflows to Agriculture, Forestry… |
year |
int64 |
— | 2003 |
value |
float64 |
— | 45.242215 |
unit |
string |
— | % |
flag |
string |
— | X |
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-foreign-direct-investment-fdi-share-of-total-fdi-outflows-us-2015-prices")
df = ds["train"].to_pandas()
print(df.head())
Filter to one country
kenya = df[df["country_name"] == "KEN"]
Time-series for a single indicator
sample = (df[df["item"] == "FDI outflows to Agriculture, Forestry and Fishing"]
.sort_values("year"))
sample.plot(x="year", y="value", title="FDI outflows to Agriculture, Forestry and Fishing")
Pivot to country × year matrix
matrix = (df[df["item"] == "FDI outflows to Agriculture, Forestry and Fishing"]
.pivot_table(index="year", columns="country_name", values="value"))
print(matrix.tail())
Citation
@misc{africa_foreign_direct_investment_fdi_share_of_total_fdi_outflows_us_2015_prices_2023,
title = {Foreign Direct Investment (FDI) — Share of Total FDI outflows US$, 2015 prices | Africa (FAOSTAT)},
author = {Food and Agriculture Organization of the United Nations (FAO)},
year = {2023},
url = {https://www.fao.org/faostat/en/#data/FDI},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-foreign-direct-investment-fdi-share-of-total-fdi-outflows-us-2015-prices}}
}
License
Released under cc-by-4.0.
Original data © Food and Agriculture Organization of the United Nations (FAO). 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 HuggingFace. 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
Provenance: ingested 2026-06-17 via the Electric Sheep pipeline. Source URL: https://www.fao.org/faostat/en/#data/FDI
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