im travaillant sur la fusion de jeux de données avec la fonction left_join()
.
Les ensembles de données jutilise sont ci-dessus:
> new_GemData<-lapply(GemData, head)
> dput(head(new_GemData))
list(cntry = c(".", "ABW", "AFG", "AGO", "AIA", "ALB"), all_tea = c(6.2942258871149,
NA, NA, 26.1555808326023, NA, NA), all_nes_entre = c(1.88915438310442,
NA, NA, 7.6296866239702, NA, NA), all_opp_entre = c(4.32969440907848,
NA, NA, 17.1323566956254, NA, NA), all_tea_male_entre = c(8.96311504196867,
NA, NA, 26.9322388085985, NA, NA), all_tea_female_entre = c(3.53006299869866,
NA, NA, 25.5152945703973, NA, NA))
> new_Hofstede<-lapply(Hofstede, head)
> dput(head(new_Hofstede))
list(ctr = c("ALB", "ALG", "AND", "ARE", "ARG", "ARM"), country = c("Albania",
"Algeria", "Andorra", "United Arab Emirates", "Argentina", "Armenia"
), `Power Distance` = c(".", ".", ".", "80", "49", "."), Individualism = c(".",
".", ".", "38", "46", "."), Masculinity = c(".", ".", ".", "53",
"56", "."), `Uncertainty Avoidance` = c(".", ".", ".", "68",
"86", "."))
> new_GpsData<-lapply(GpsData, head)
> dput(head(new_GpsData))
list(country = c("Afghanistan", "Algeria", "Argentina", "Australia",
"Austria", "Bangladesh"), isocode = c("AFG", "DZA", "ARG", "AUS",
"AUT", "BGD"), patience = c(-0.201360121369362, 0.0598152466118336,
-0.229307979345322, 0.65700376033783, 0.608285009860992, 0.0811367109417915
), risktaking = c(0.120764262974262, 0.391530483961105, 0.0415031686425209,
0.137136548757553, -0.0618291534483433, -0.198067754507065),
posrecip = c(0.2896409034729, -0.598255336284637, 0.159679308533669,
0.069660022854805, 0.161046594381332, 0.154367566108704),
negrecip = c(0.254712462425232, 0.254900813102722, -0.140457272529602,
0.0221897512674332, -0.0554154515266418, 0.113288171589375
))
La colonne commune dont j'ai besoin est les Noms de Pays, je sais que ISO3 est la méthode la plus appropriée pour les fusionner.
Ici, im essayant de les fusionner:
new_Hofstede$code=countrycode(new_Hofstede$`country`, origin = 'country.name', destination = 'iso3c')
merged_data2 <- new_Hofstede %>%
rename(iso3 = 'code') %>%
left_join(new_GemData, by = c('iso3' = 'cntry') )
all_data2 <- left_join(merged_data2, new_GpsData, by=c("iso3"="isocode"))
EDIT: je ne sais pas si la fusion que j'ai fait est correct et j'aimerais vos suggestions , des propositions sur la façon de fusionner ces ensembles de données, GEM, Hofstede et GPS.