I need a list of the central points (centroid) for all countries:
China: lat/long (coordinates of the most central point in China)
France: lat/long (coordinates of the most central point in France)
etc...
This has lots of information on the countries (incl. Centroids), and the possibility to download the data in several formats:
https://worldmap.harvard.edu/data/geonode:country_centroids_az8
You can retrieve this information using R
like this:
library(rgeos)
library(rworldmap)
# get world map
wmap <- getMap(resolution="high")
# get centroids
centroids <- gCentroid(wmap, byid=TRUE)
# get a data.frame with centroids
df <- as.data.frame(centroids)
head(df)
#> x y
#> Aruba -69.97345 12.51678
#> Afghanistan 66.00845 33.83627
#> Angola 17.53646 -12.29118
#> Anguilla -63.06082 18.22560
#> Albania 20.05399 41.14258
#> Aland 20.03715 60.20733
# plot
plot(centroids)
You can get country centroids using Python and GeoPandas.
import geopandas as gpd
import pandas as pd
# Access built-in Natural Earth data via GeoPandas
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
# Get a list (dataframe) of country centroids
centroids = world.centroid
centroid_list = pd.concat([world.name, centroids], axis=1)
# Plot the results
base = world.plot(column = 'name', cmap = 'Blues')
centroids.plot(ax = base, marker = 'o', color = 'red', markersize = 5)
In [1]: centroid_list
Out[1]:
name 0
0 Afghanistan POINT (66.08669022192834 33.85639928169076)
1 Angola POINT (17.47057255231345 -12.24586903613316)
2 Albania POINT (20.03242643144321 41.14135330604877)
3 United Arab Emirates POINT (54.20671476159633 23.86863365334761)
4 Argentina POINT (-65.17536077114174 -35.44682148949509)
5 Armenia POINT (45.00029001101479 40.21660761230144)
6 Antarctica POINT (20.57100056984261 -80.49198288284349)
... and so on ...
Here's a list that Google provides:
https://developers.google.com/public-data/docs/canonical/countries_csv
Here is an open data site that hosts the center point data in several formats: World Countries Centroids (direct links: CSV | GeoJSON)