CoolFace
Datasetpublic

letrinhan/vn-provinces-investment-construction-master

Vietnam investment and construction master panel by locality Wide geo×year master joining NSO Investment and Construction locality packs: FDI licensed and stock (where published), housing floor area completed, and related construction series. Outer join on geo_code×year. Province names follow ar_core.vn_geo. Figures Hero Comparison Color key Files provinces (945 rows) data/provinces.csv data/provinces.dta data/provinces.xlsx regions (90 rows)… See the full description on the dataset page: https://huggingface.co/datasets/letrinhan/vn-provinces-investment-construction-master.

sourceHugging Faceotherupdated 9h agoView on Hugging Face
0likes102downloads
Dataset Card

Vietnam investment and construction master panel by locality

Wide geo×year master joining NSO Investment and Construction locality packs: FDI licensed and stock (where published), housing floor area completed, and related construction series. Outer join on geocode×year. Province names follow arcore.vn_geo.

Figures

Hero

[image]

Comparison

[image]

Color key

[image]

Files

provinces (945 rows)

  • —data/provinces.csv
  • —data/provinces.dta
  • —data/provinces.xlsx

regions (90 rows)

  • —data/regions.csv
  • —data/regions.dta
  • —data/regions.xlsx

national (15 rows)

  • —data/national.csv
  • —data/national.dta
  • —data/national.xlsx

Load

Stata:

stata
use "data/provinces.dta", clear

R:

r
df <- read.csv("data/provinces.csv")

SPSS: open the .xlsx or .csv file.

Source

National Statistics Office of Vietnam (NSO/GSO). Built by outer-joining investment and construction locality packs.

Method: outer-join leaf packs on geocode×year with English geo labels via arcore.vn_geo. Cleaning and joins are automated in this repository (Python).

Citation

bibtex
@misc{nso_vn_provinces_investment_construction_master,
  title = {Vietnam investment and construction master panel by locality},
  author = {{National Statistics Office of Vietnam}},
  note = {FDI stock/flow 2024; housing floor area series.},
  year = {2024}
}

Built 2026-09-26 UTC.