library(gapminder)
head(gapminder)

    # A tibble: 6 x 6
  country     continent  year lifeExp      pop gdpPercap
  <fct>       <fct>     <int>   <dbl>    <int>     <dbl>
1 Afghanistan Asia       1952    28.8  8425333      779.
2 Afghanistan Asia       1957    30.3  9240934      821.
3 Afghanistan Asia       1962    32.0 10267083      853.
4 Afghanistan Asia       1967    34.0 11537966      836.
5 Afghanistan Asia       1972    36.1 13079460      740.
6 Afghanistan Asia       1977    38.4 14880372      786.

y <- unique(gapminder$country, incomparables = FALSE)
    length(y)
    [1] 142
    df.names <- paste(y, sep = "")

for(i in 1:length(y)){
  d.frame[,i] <- gapminder$pop %>% filter(gapminder$country==y[i])
  assign(df.names[i], d.frame)
}