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If you live in Excel, R, or a Jupyter notebook — stop scraping Stats NZ. Get CSV, DataFrames, and ggplot-ready tibbles for 1059+ NZ datasets, one line of code.
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CPI, unemployment, GDP, house prices, fiscal aggregates — all the usual NZ macro series.
df <- eolas_get("nz_cpi")
SA1, SA2, TA, Region, Urban Area — every Stats NZ Geospatial polygon, in WKT or sf.
sa2 <- eolas_get("sa2_2023")
2023, 2018, 2013 — joinable on SA1 / SA2 / Region. Demographics, housing, dwellings.
eolas_get("census_2023_housing_sa2")
Waka Kotahi traffic counts, crash data, road policing. Millions of records, streaming-safe.
eolas_get("nzta_tms_2024")
Same data, three idiomatic interfaces.
remotes::install_github(
"phildonovan/eolas-r"
)
library(eolas)
eolas_key("your_key")
df <- eolas_get_statsnz("nz_cpi",
start = "2015-01-01")
eolas_plot(df)
Returns a tibble; eolas_plot() hands back a ggplot you can extend with +.
pip install eolas-data
from eolas_data import Client
c = Client("your_key")
df = c.statsnz("nz_cpi",
start="2015-01-01")
df.plot_dataset()
pandas DataFrame subclass. Optional [polars], [geo], [plot] extras.
# From your terminal
pip install eolas-data[cli]
eolas auth set-key
eolas get nz_cpi \
--format csv \
--out cpi.csv
# Or download from
# eolas.fyi/datasets/nz_cpi
CSV downloads available on every dataset detail page. eolas schedule automates daily fetches.
eolas get nz_cpi --start 2020-01-01 --format csv --out cpi.csv
library(eolas); library(sf); library(ggplot2)
sa2 <- eolas_get("sa2_2023")
ggplot(sa2) + geom_sf()
eolas schedule add nz_cpi --cron "0 8 * * 3" --out ~/data/cpi.csv
Installs a cron entry that re-fetches the dataset. Removes cleanly with eolas schedule remove nz_cpi.
eolas datasets list --search cpi
eolas datasets info nz_cpi
eolas datasets preview nz_cpi
Or browse the catalog at eolas.fyi/datasets.
10 requests/month, all 1059+ datasets, no credit card. Upgrade to Starter ($10/mo) if you need more.
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