Raw annual irradiation of the 34 prefecture seats (GHI, DNI, DHI)

Kuma ScienceAnnual34 locationsSatellite or reanalysisCC BY 4.0

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34 rows selected

This is the Parquet file the table reads. It opens in pandas, R, DuckDB or QGIS.

Parquet (2.7 KB) SHA-256 28a8b4d2e833887a9fd1bf6c132385f88ffff1620d5d3c4267067d3f5868b66f

The Parquet file can be read straight from its URL, without downloading it first.

import pandas as pd

df = pd.read_parquet("https://kumascience.com/data/jeux/chefs-lieux-rds.parquet")
df.head()

library(arrow)

df <- read_parquet("https://kumascience.com/data/jeux/chefs-lieux-rds.parquet")
head(df)

INSTALL httpfs; LOAD httpfs;

SELECT *
FROM read_parquet('https://kumascience.com/data/jeux/chefs-lieux-rds.parquet')
LIMIT 10;

The layer is served by the Atlas map server. You can add it to QGIS or query it over WFS.

Layer: kuma_ouvert:rds_chefs_lieux
WFS GetCapabilities: https://atlas.kumascience.com/geoserver/kuma_ouvert/ows?service=WFS&version=2.0.0&request=GetCapabilities
GeoJSON: https://atlas.kumascience.com/geoserver/kuma_ouvert/ows?service=WFS&version=2.0.0&request=GetFeature&typeNames=kuma_ouvert:rds_chefs_lieux&outputFormat=application/json&count=10

CC BY 4.0. Atlas solaire de la Guinée, opéré par Kuma Science, CC BY 4.0.