datamash gave me 0.52 for Pearson. Which is "eh, maybe".
datamash gave me 0.52 for Pearson. Which is "eh, maybe".
I've reproduced dwaltrib's results using World Bank data on 251 countries, and I get a Pearson's r of 0.82 and a p value of 5.6e-61 (!). I.e. a strong correlation, with high confidence. It makes sense too -- larger countries generally have more people, and more people generally generate more economic activity.
Code if you want to try yourself:
import pandas as pd
gdp = pd.read_csv("~/Downloads/API_NY.GDP.MKTP.CD_DS2_en_csv_v2_5551501.csv").set_index("Country Name")
land_area = pd.read_csv("~/Downloads/API_AG.LND.TOTL.K2_DS2_en_csv_v2_5552158.csv").set_index("Country Name")
gdp["GDP"] = gdp["2020"]
gdp["Land"] = land_area["2020"]
gdp = gdp.dropna(subset=["GDP", "Land"])
from scipy import stats
print(stats.pearsonr(gdp.Land, gdp.GDP))
#+RESULTS: : PearsonRResult(statistic=0.8151313879150333, pvalue=5.621180589722219e-61)